15041 results for "cancer studies using rna-seq"

in 39.17 milliseconds.

• Human skin cancer (BCC, SCC, melanoma) and healthy control skin

  Smart-seq2 single cell RNA sequencing of human BCC, SCC, melanoma (ALM) and healthy control skin samples.

  Dataset EGAD50000000540

• Analysis of IDHwt-glioblastoma samples from paired primary and recurrent tumor samples

  IDHwt-glioblastomas rapidly recur after initial treatment. To study genetic evolution in glioblastoma, we analyzed whole genomes of 21 pairs of primary and recurrent tumor samples using next generation sequencing. In addition we sequenced RNA from 16 tumor pairs and a panel of 50 glioma-associated genes in tumor pairs from 43 patients (including 14 of the 21 patients included in the WGS discovery set). Glioblastoma subtypes were determined using 450k/EPIC methylation arrays. This study was supported within the e:med program of the German Ministry of Education and Research (BMBF) by the collaborative research project ‘SYS-GLIO - Systems-based prediction of the biological and clinical behavior of gliomas’ (https://www.sys-med.de/de/demonstratoren/sys-glio/) This study is part of the Heidelberg Center for Personalized Oncology - HIPO-043

  Study EGAS00001003184

• Salivary Gland Cancer TSO500 dataset

  DNA was extracted from archival tissue of 119 patients with various SGC subtypes and sequenced using a targeted NGS panel encompassing 523 cancer related genes (TruSight Oncology 500, TSO500). This dataset belongs to the publication entitled: 'Identification of fusion genes and targets for genetically matched therapies in a large cohort of salivary gland cancer patients'.

  Dataset EGAD00001008759

• Exome sequencing of United Kingdom Brain Expression Consortium samples

  The United Kingdom Brain Expression Consortium studies regulation of gene expression through common and rare variation. One of the main set of samples is compound by bulk brain tissue from 10 brain regions obtained from 134 controls.

  Study EGAS00001002113

• Exome_sequencing_of_UK_Birth_Cohorts___Avon_Longitudinal_Study_of_Parents_and_Children

  We propose to exome sequence birth cohorts with near complete population coverage (thus addressing the ascertainment biases of previous studies), which have detailed longitudinal cognitive and educational data on parents and children, and for which genotyping chip data are readily available.

  Study EGAS00001005273

• Insights from genome-wide data from Thailand and Laos

  We provide the first detailed insights into the genetic profiles of Thai/Lao ethnolinguistic groups, which should be helpful for reconstructing human genetic history in MSEA and selecting populations for participation in ongoing whole genome sequence and biomedical studies

  Study EGAS00001006053

• Study of Korean Parkinson's disease

  Single nucleotide variants (SNVs) associated with Parkinson’s disease (PD) have been investigated mainly through genome-wide association studies. Here, we conducted whole genome sequencing of 410 PD patients and 200 healthy individuals of the Korean population and identified disease-related SNVs.

  Study EGAS00001006811

• Exome_sequencing_of_UK_Birth_Cohorts___Born_in_Bradford

  We propose to exome sequence birth cohorts with near complete population coverage (thus addressing the ascertainment biases of previous studies), which have detailed longitudinal cognitive and educational data on parents and children, and for which genotyping chip data are readily available.

  Study EGAS00001006978

• Exome_sequencing_of_UK_Birth_Cohorts___Millennium_Cohort_Study

  We propose to exome sequence birth cohorts with near complete population coverage (thus addressing the ascertainment biases of previous studies), which have detailed longitudinal cognitive and educational data on parents and children, and for which genotyping chip data are readily available.

  Study EGAS00001007789

• Integrative analysis of whole genome sequencing, RNA sequencing and methylome array of 20 carcinosarcomas.

  Carcinosarcomas of the female genital tract, or GCS, are uncommon but clinically highly aggressive neoplasms with biphasic histology of carcinomatous (C) and sarcomatous (S) elements. These tumors represent a unique model to study the genetic and phenotypic diversity of cancer cells and the link between cellular plasticity and resistance to therapy. The aim of ICGC GCS program is to genomically characterize C and S components of 20 tumors, from endometrium or ovary, through an integrative analysis of whole genome sequencing, RNA sequencing and methylome array.

  Study EGAS00001002271

• The genomic landscape of cutaneous squamous cell carcinoma from immunosuppressed and immunocompetent patients reveals common drivers and a novel mutational signature associated with chronic azathioprine exposure

  Cutaneous squamous cell carcinoma (cSCC) has a high tumour mutational burden (50 mutations per megabase DNA pair). Combining whole exome analyses from 40 primary cSCC tumours, comprising 20 well differentiated and 20 moderately/poorly differentiated tumours, with accompanying clinical data from a longitudinal study of immunosuppressed and immunocompetent patients, coupled with integration of independent gene expression studies has allowed the identification of commonly mutated genes and altered pathways and processes. Mutational signature analysis revealed the presence of a novel signature (signature 32), which was found exclusively in the tumours from immunosuppressed patients who had been exposed to azathioprine. Characterisation of a panel of 15 keratinocyte cancer cell lines derived from tumours from immunocompetent and immunosuppressed patients reveals that they accurately reflect the mutational signatures and genomic alterations of primary tumours and provide a resource for the validation of tumour drivers and therapeutic targets.

  Study EGAS00001002612

• Genes for Non-Syndromic Congenital Heart Disease

  Congenital heart defects (CHDs) are the most common serious birth defect and a leading cause of infant mortality. Affected individuals who survive infancy require substantial medical care and experience lifelong morbidity and early mortality. Despite their prevalence and impact upon public health, the etiology of CHDs is poorly understood. Our long-term goal is to better define the genetic basis of CHDs and using this information, develop preventive measures and provide precise medical management based on genotype. As CHDs are a heterogeneous group of conditions, we have focused our studies on cases with conotruncal heart defects (CTDs) that comprise at least 36% of all CHDs and are a prominent feature of the 22q11.2 deletion syndrome (22q11DS). We have conducted both SNP- and CNV-based genome-wide association studies as part of our previous and current P01 (HD070454). Our current analyses of genes and gene-sets provide new insights regarding the contribution of common and rare inherited genetic variants to CTDs. Specifically, based on the results from our studies as well as recently published findings, we hypothesize that: (1) CTDs are influenced by the full range of genetic variability (rare to common; de novo and inherited) in relevant gene-sets; (2) the number of disease-related variants within these gene-sets varies directly with CTD severity; and (3) gene-sets associated with CTDs in nonsyndromic individuals are also associated with CTDs in individuals with the 22q11DS. To augment our existing cohorts and thus substantially improve the statistical power of our proposed analyses, application was made to complete array genotyping of a set of patients with CTDs and in particular, those with mild disease represented by isolated aortic arch anomalies. The new cases with CTD and some with an isolated aortic arch anomaly were ascertained at the Children's Hospital of Philadelphia (CHOP) while some of the cases with isolated aortic arch anomalies were ascertained by the Pediatric Cardiac Genomics Consortium (PCGC). A small group of cases with left-sided obstructive lesions from CHOP were included to combine with our existing datasets to serve as a comparison to those with CTD. The additional genotype data will augment the statistical power of the proposed common variant analyses. We anticipate that this work will reduce the gaps in our understanding of CTDs by identifying an explicit set of genes associated with CTD-risk by way of common variants. This work will also help define the genetic architecture for the full clinical spectrum of these common birth defects.

  Study phs002059

• DAC for BillionToOne

  This is the Data Access Committee for studies published by BillionToOne.

  Dac EGAC50000000418

• Genomic Analysis of Nucleic Acid Sequences from Pancreatic Cancer

  Our study aims to perform multi-omics analysis of pancreatic ductal adenocarcinoma. We performed dual single-cell RNA sequencing and whole genome sequencing on fresh tumor specimens and dual bulk RNA-sequencing and 16S amplicon sequencing on frozen tumor specimens to identify human and non-human nucleic acid sequences. Additionally, we identified microbial sequences and found that bacterial taxonomic profiles from the same sample strongly correlated across technologies.

  Study phs003035

• Single-cell RNA sequencing of 16 NPM1 mutated AML patients

  NPM1 mutated AML is the largest class in WHO classification, however several subtypes within NPM1 were already reported. Here, we sequence 16 NPM1 mutated AML samples with single-cell RNA-sequencing and multi-color flow cytometry from three major NPM1 subtypes we previously identified, totaling more than half a million cells. We show that the differences among three NPM1 subtypes are mainly driven by cell composition, and these differences are also reflected at cell surface protein level. With the re-analysis of CITE-seq data from another cohort and single cell variant calling on our data, we also report two distinct stem cell phenotypes: one with leukemic (CD34dimCD38-CD45RA+) and another with pre-leukemic (CD34+CD38-CD45RA-) origin. We believe that our data and findings provide novel insights regarding the etiology of NPM1 mutated AML.

  Study EGAS50000000332

• Point-of-care monitoring of head and neck cancer treatment response and recurrence development using nanopore-based ctDNA consensus sequencing

  Study EGAS00001007090

• A Population Genomics Study Using a Disease-Targeted Cell model: Integration of

  The common genetic variants associated with complex traits typically lie in non-coding DNA and may alter gene regulation in a cell type-specific manner. Consequently, the choice of tissue or cell model in the dissection of disease associations is important. We carried out an expression quantitative trait loci (eQTL) study of primary human osteoblasts (HOb) derived from 95 unrelated donors of Swedish origin, each represented by two independently derived primary lines to provide biological replication. We combined our data with publicly available information from a genome-wide association study (GWAS) of bone mineral density (BMD). The top 2000 BMD-associated SNPs were tested for cis-association of gene expression in HObs and in lymphoblastoid cell lines (LCLs) using publicly available data and showed that HObs have a significantly greater enrichment (threefold) of converging cis-eQTLs as compared to LCLs. The top 10 BMD loci with SNPs showing strong cis-effects on gene expression in HObs were selected for further validation using a staged design in two cohorts of Caucasian male subjects. All 10 variants were tested in the Swedish MrOS Cohort (n = 3014), providing evidence for two novel BMD loci (SRR and MSH3). These variants were then tested in the Rotterdam Study (n = 2090), yielding converging evidence for BMD association at the 17p13.3 SRR locus. The cis-regulatory effect was further fine-mapped to the proximal promoter of the SRR gene (rs3744270). Our results suggest that primary cells relevant to disease phenotypes complement traditional approaches for prioritization and validation of GWAS hits for follow-up studies. Reprinted from Grundberg E, Kwan T, Ge B et al., Genome Res Nov 2009, with permission from Genome Research, Cold Spring Harbor Press, PMID:19654370.

  Study phs000225

• Center for Craniofacial and Dental Genetics: Exome Sequencing of Orofacial Cleft Families

  Orofacial Clefts (OFCs) are genetically complex structural birth defects caused by genetic factors, environmental exposures, and their interactions. OFCs are the most common craniofacial anomalies in humans. Affect about 1 in 800 newborns, OFCs are also one of the most common structural birth defects worldwide. OFCs can impose a substantial personal cost resulting from the associated emotional and financial burden. On average a child undergoes 6 surgeries, spends 30 days in hospital, receives 5 years of orthodontic treatment, and participates in ongoing speech therapy, leading to an estimated total lifetime treatment cost of about $200,000. Individuals born with an OFC have higher infant mortality (especially in developing countries with limited access to care), higher mortality rates at all other stages of life, increased incidence of mental health problems, and higher risk for other disorders (notably including breast, brain, and colon cancers). Prior genetic studies have focused on the contribution of common genetic variants through genome-wide linkage and association studies. These studies have revealed a significant etiologic heterogeneity. One promising approach to dissect the etiology of OFCs into focus on subclinical phenotypic features present in the non-cleft family members of affected individuals. These subclinical features are subtle phenotypic features that may represent mild manifestations of the same risk genes; thus, their inclusion in family-based studies may clarify the inheritance patterns in OFC families. In this project, we conducted whole exome sequencing in multiplex families with both overt OFCs and subclinical phenotypes to identify high-impact genes causing OFCs.

  Study phs001675

• 10X single cell RNA- and feature barcode sequencing of 38 AML samples

  This dataset contains fastq-files from single cell 3' RNA- and feature barcode sequencing of AML samples using 10X technology (Chromium Single Cell 3ʹ Reagent Kit v3). In total, the dataset contains data from 38 AML samples from either bone marrow or peripheral blood, representing the following genetic subtypes: NPM1-mutated, myelodysplasia related, TP53-mutated, CBFB::MYH11, RUNX1::RUNX1T1, AML without class-defining mutations, and AML meeting criteria of two subtypes. The data consists of sequenced gene expression libraries from 38 samples and feature barcoding libraries covering a panel of 10-14 surface proteins for 34 samples.

  Dataset EGAD50000001577

• scRNA transcriptome and TCR sequencing data modeling treatment responses in eight renal cell carcinoma patient

  Single cell RNA sequencing and coupled TCR sequencing data generated following immunological treatments in patient-derived ex vivo tumor models. Dataset consist of 46 sequencing samples originating from eight individual patient-derived ex vivo models. Single cell RNA and TCR sequencing data is generated using 10X Genomics platform with 5´ sequencing. The submission contains 46 Fastq files where each patient-derived ex vivo model and it's transcriptomic response to specified treatment is a unique sequencing run. TCR sequencing runs are submitted as one file per individual model, gathering all the treatment conditions.

  Dataset EGAD50000001934

• cfDNA dataset from the urine supernatant of ovarian cancer patients and healthy controls

  Background Ovarian cancer is the deadliest gynecological malignancy worldwide, due to frequent diagnosis at advanced stage. Simple and non-invasive methods for earlier and accurate detection are urgently needed. Here, the presence of tumor-derived DNA in home-collected urine, cervicovaginal self-samples and clinician-taken cervical scrapes of ovarian cancer patients was explored by DNA methylation and copy number analysis. Methods A total of 428 samples (urine, cervicovaginal self-samples, and clinician-taken cervical scrapes) of 110 healthy controls and 54 patients with benign (n=25) or malignant (n=29) ovarian masses were analyzed. Different urine fractions were examined (full void urine, urine supernatant, and urine sediment). All samples were tested for 12 methylation markers by quantitative methylation-specific PCR. Shallow whole-genome sequencing was performed to detect copy number aberrations and verify the presence of tumor-derived DNA. Results Full void urine was most discriminatory between healthy controls and ovarian cancer patients (C2CD4D, p=0.008; CDO1, p=0.022; MAL, p=0.008), followed by cervical scrapes (C2CD4D, p=0.001; CDO1, p=0.004). A significant difference between benign and malignant ovarian masses was only observed for GHSR in the urine sediment (p=0.024). Methylation levels in cervicovaginal self-samples did not discriminate between healthy controls, benign and malignant ovarian masses. Copy number changes were identified in 17% of urine supernatant samples and smaller fragment sizes were seen in urine supernatant samples with a high tumor fraction. Conclusions This study demonstrates the presence of ovarian cancer-derived DNA in home-collected urine. Additional studies are warranted to further explore the clinical applicability of this approach.

  Study EGAS00001007238

• INCLUDE Data Hub: NDA GUIDs for Down Syndrome Research

  The INCLUDE (INvestigation of Co-occurring conditions across the Lifespan to Understand Down syndromE) Project is an NIH-wide collaboration that seeks to improve health and quality of life for people with Down syndrome. The INCLUDE Project Data Coordinating Center (DCC) and partners created the INCLUDE Data Hub, a centralized data resource that allows access to large-scale clinical and multi-omics datasets specific to Down syndrome and supports collaborative, cloud-based analysis to accelerate scientific discoveries related to Down syndrome and its co-occurring conditions. The INCLUDE Data Hub includes an innovative researcher data repository, a portal, and a cloud-based platform for data analysis. The portal provides access to de-identified demographics and clinical metadata, as well as multi-omics datasets, including whole genome sequences, transcriptomes, proteomes, and metabolomes. The INCLUDE Data Hub uses a 'registered access' model, whereby users can access the portal and associated data after agreeing to terms of use. From the Data Hub, users can also reach 'controlled access' data (e.g., whole genome sequences) only for those studies for which they have obtained approval by an NIH Data Access Committee through the corresponding dbGaP study. A thoughtful linkage strategy to identify duplicate participants across studies enables researchers to merge multiple datasets and data types to create richer datasets and reduce costly redundancies in large-scale data generation (e.g., -omics) while mitigating potential risks introduced by linkage.Based on recommendations from the NICHD Office of Data Science and Sharing, which completed a comprehensive assessment of existing Privacy Protecting Record Linkage (PPRL) and associated data governance solutions, the INCLUDE DCC and the associated NIH Steering Committee have implemented NIMH Data Archive Global Unique Identifiers (NDA GUIDs) in the INCLUDE Data Hub. The NDA GUID Tool is a government-owned and operated PPRL technology that enables researchers to link data from multiple sources to the same individual without revealing personally identifiable information (PII). With the NDA GUID Tool, the same participant information will return the same GUID whenever or wherever it is entered. The GUID itself is not personally identifiable information or protected health information. Sharing data with NDA GUIDs allows approved researchers to link together data on a single participant, even if the data were collected at different locations or through different studies or are distributed from different data repositories. This dbGaP study enables researchers to access an INCLUDE GUID Mapping File that includes all available NDA GUIDs and their associations to study-specific Participant IDs across studies in the INCLUDE Data Hub. This dbGaP study only distributes NDA GUIDs associated with the INCLUDE Data Hub datasets. To access the associated controlled-access datasets, add the corresponding dbGaP studies to your Data Access Request. A list of these studies is available on the INCLUDE Data Hub Portal: https://portal.includedcc.org/studies.

  Study phs003678

• Synergy study: "Tissue resident CD8+ T cell clonal expansion in advanced triple negative breast cancer is associated with response to chemoimmunotherapy"

  Dataset of the study "Synergy study: "Tissue resident CD8+ T cell clonal expansion in advanced triple negative breast cancer is associated with response to chemoimmunotherapy". This dataset contains the cellranger's gene-expression matrices for the 5 prime single-cell RNA sequencing experiments

  Dataset EGAD50000000748

• Exploiting evolutionary steering in cancer therapy

  Drug resistance, mediated by intra-tumour heterogeneity and clonal evolution, is arguably the biggest problem in cancer therapy today. However, evolving resistance to one drug may come at the cost of increased sensitivity to another due to so-called evolutionary trade-offs. This weakness can be exploited in the clinic using an approach called ‘evolutionary herding’ that aims at controlling the tumour cell population to delay or prevent resistance. However, model systems able to recapitulate cancer evolution experimentally are lacking and current in vitro techniques based on small populations, re-plating and escalating dose, are unsuitable to develop evolutionary herding strategies. We present a novel methodology for evolutionary herding in vitro and ex vivo using patient-derived organoids. Our approach is based on a combination of single-cell barcoding, very large populations of 108-109 cells grown without re-plating, realistic high drug doses, time-course monitoring of cancer clones, and mathematical modelling of tumour evolutionary dynamics. We demonstrate evolutionary herding in non-small cell lung cancer in vitro and in patient-derived colorectal cancer organoids (PDO). We show that herding causes controlled evolutionary bottlenecks that lead to collateral sensitivity. Through genomic analysis, we were also able to determine the mechanisms that drive such sensitivity. Our approach allows modelling evolutionary trade-offs experimentally to test patient-specific evolutionary herding strategies that can be translated into the clinic to control treatment resistance.

  Study EGAS00001003200

• Bulk RNASeq of metastatic colorectal cancer organoids with ATOH1 knockout

  Bulk RNA sequencing was performed on mCRC organoids subjected to cetuximab treatment, comparing ATOH1 knockout and control conditions. The dataset is intended to elucidate the contribution of ATOH1-regulated secretory cell population to cetuximab persistence mechanisms.

  Study EGAS50000001421

• Bulk RNA sequencing data of high-grade serous ovarian cancer samples (set 18-19)

  The dataset contains RNA sequencing data of 66 high-grade serous carcinoma (HGSC) patients sequenced with Novoseq 6000. The 155 samples are fresh frozen tissue samples that have been collected from different tissues and time points before and during treatment. The files provided are paired fastq files.

  Dataset EGAD50000002370

• Multi-region RNA sequencing of tumour regions and tumour-adjacent normal lung tissue

  TRACERx (TRAcking Cancer Evolution through therapy (Rx)) is a prospective cohort study designed to investigate intratumor heterogeneity (ITH) in relation to clinical outcome, and to determine the clonal nature of driver events and evolutionary processes in early stage non-small cell lung cancer (NSCLC).

  Study EGAS00001006517

• Chordoma Sequencing Project RNAseq

  This is a continuation of the Chordoma Sequencing Project. All cancers arise due to somatically acquired abnormalities in DNA sequence. Systematic sequencing of cancer genomes allows acquisition of complete catalogues of all classes of somatic mutation present in cancer. These mutation catalogues will allow identification of the somatically mutated cancer genes that are operative and characterise patterns of somatic mutation that may reflect previous exogenous and endogenous mutagenic exposures. In this application, we aim to perform whole genome sequencing on 10 chordoma matched genome pairs. RNA Sequencing/Methylation and SNP6 and an additional sequencing of three cancer cell lines will be added to this work.

  Dataset EGAD00001000653

• Primary breast cancers and paired brain metastases

  Targeted next-generation-sequencing of 494 cancer-associated genes was done in a series of 14 frozen pairs of matched primary breast cancers and brain metastases (28 samples). DNA libraries of all coding exons were prepared using the Haloplex Target Enrichment System. Sequencing was done using the 2*150bp paired-end technology on the Illumina NextSeq500 platform.

  Dataset EGAD00001004309

• Active-Seq of CRC patients

  This dataset contains 48 fastq files of samples derived from CRC patients, including colorectal cancer tissue, normal adjacent tissue and cfDNA samples, processed with the Illumina platform NovaSeq6000.

  Dataset EGAD50000001746

• Asthma in the Lives of Families Today (ALOFT)

  Social interactions and the overall psychosocial environment have a demonstrated impact on health, particularly for people living in disadvantaged urban areas. Here we investigated the effect of psychosocial experiences on gene expression in peripheral blood immune cells of 251 children with asthma in Metro Detroit. Participants were included from an ongoing longitudinal study Asthma in the Lives of Families Today (ALOFT; recruited from November 2010-July 2018. The ALOFT project was established to identify the behavioral and biological pathways through which family social environments impact youth with asthma.In version 1 we used RNA-sequencing and a new machine learning approach to identify transcriptional signatures of 19 variables including psychosocial factors, blood cell composition and asthma symptoms. Using longitudinal data collected from a subset of the participants we showed that transcriptional signatures track the longitudinal changes in measured phenotypes. Importantly, we found 169 genes associated with asthma that are regulated by psychosocial factors, and 344 significant gene-environment interactions for gene expression levels. These results demonstrate that immune gene expression mediates the link between negative psychosocial experiences and asthma risk.In version 2, we focused on pubertal development. We identified substantial gene expression changes associated with age and pubertal development. We showed that genetic effects on gene expression change dynamically during pubertal development. Gene expression changes during puberty are correlated with gene expression changes associated with asthma and may explain sex differences in prevalence. Our results show that molecular data used to study the genetics of early onset diseases should consider pubertal development as an important factor that modifies the transcriptome.Version 3 uses single cell RNA-seq to study the dynamics of the transcriptional response to glucocorticoids in activated Peripheral Blood Mononuclear Cells from 96 African American children. We employed novel statistical approaches to calculate a mean-independent measure of gene expression variability and a measure of transcriptional response pseudotime. Using these approaches, we demonstrated that glucocorticoids reverse the effects of immune stimulation on both gene expression mean and variability. Our novel measure of gene expression response dynamics, based on the diagonal linear discriminant analysis, separated individual cells by response status on the basis of their transcriptional profiles and allowed us to identify different dynamic patterns of gene expression along the response pseudotime. We identified genetic variants regulating gene expression mean and variability, including treatment-specific effects, and demonstrated widespread genetic regulation of the transcriptional dynamics of the gene expression response.Version 4 adds scATAC-seq in activated peripheral blood mononuclear cells (PBMC) from 16 children with asthma with phytohemagglutinin (PHA) or lipopolysaccharide (LPS), and treated with dexamethasone (DEX), an anti-inflammatory glucocorticoid. We analyzed changes in chromatin accessibility, measured transcription factor motif activity, and identified treatment and cell-type specific transcription factors that drive changes in both gene expression mean and variability. We observed strong positive linear dependence between motif response and their target gene expression changes, but negative in variability changes. This result suggests that an increase of transcription factor binding tightens the variability of gene expression around the mean. We then annotated genetic variants in chromatin accessibility peaks and response motifs followed by computational fine-mapping of eQTL signals from a pediatric asthma cohort. We found that eQTLs were 5-fold enriched in peaks with response motifs and refined the credible set for 410 asthma risk genes, with 191 having the causal variant in response motifs. These results enhance the understanding of molecular mechanisms for asthma risk variants mediated by gene expression.

  Study phs002182

• Ductal keratin 15+ luminal progenitors in normal breast exhibit a basal-like breast cancer transcriptomic signature

  Normal breast luminal epithelial progenitors have been implicated as cell of origin in basal-like breast cancer, but their anatomical localization remains understudied. Here, we combine micro-collection of uncultured organoids and single cell mRNA sequencing (scRNA-seq) of FACS-sorted luminal epithelial cells with multicolor imaging to profile ducts and terminal ductal lobular units (TDLUs) and compare them with breast cancer subtypes. Unsupervised clustering reveals eleven distinct clusters and a differentiation trajectory starting with keratin 15+ (K15+) progenitors enriched in ducts. Spatial mapping of luminal progenitors is confirmed at the protein level by staining with critical duct markers. Comparison of the gene expression profiles of normal luminal cells with those of breast cancer subtypes reveals a strong correlation between normal breast K15+ ductal progenitors and basal-like breast cancer. We propose that K15+ basal-like breast cancers originate in ductal progenitors, which emphasizes the importance of not only lineages but also cellular position within the ductal-lobular tree.

  Study EGAS00001005963

• BROCA cancer panel sequencing for 15 samples

  BROCA panel sequencing using the BROCA-HR v8 and BROCA-GO v1 versions of the gene panel

  Dataset EGAD50000000035

• Targeted exome sequencing of pleomorphic invasive lobular carcinoma (PILC).

  Pleomorphic invasive lobular carcinoma (PILC) is an aggressive variant of invasive lobular breast cancer that is associated with poor clinical outcomes. Limited molecular data are available to explain the mechanistic basis for PILC behavior. To address this issue, we performed targeted sequencing using the Beijing Genomics Institute (BGI) TumorCare™ gene panel that includes 1053 genes that were selected based upon their association with cancer. This sequencing analysis identified genes that distinguish PILC from classic ILC (CILC) and invasive ductal carcinoma (IDC) by the incidence of their genomic changes.

  Study EGAS00001002871

• CNV detection in targeted NGS panel data

  The aim of this study was to compare copy-number-variation (CNV) detection methods for targeted NGS panel data in a clinical diagnostic setting. We present targeted NGS panel data from 170 samples that were processed using the TruSight(TM) Cancer (TSC) panel (Illumina, San Diego, CA, USA), which targets 94 genes and 284 SNPs associated with a predisposition towards cancer. The samples are enriched for CNVs in the genes of interest. All CNVs have previously been assessed with MLPA and can therefore be considered as confirmed.

  Study EGAS00001002481

• Genomic variants in 121 genes associated with ovarian cancer in cancer tissue and derived organoids

  High-grade serous ovarian cancer (HGSOC) likely originates from the fallopian tube (FT) epithelium, but advanced stages are mostly found outside the FT. We used ex-vivo cultures of HGSOC and knock-out of tumor suppressors in FT organoids to study changes in epithelial cells and niche requirements for normal and transformed FT cells. We found that transformed cells require BMP signaling and are growth arrested in Wnt rich medium. A SureSelectXT Automation Custom Capture Library (Agilent) target enrichment panel was designed. The enrichment panel comprised all coding exons of 121 genes associated with ovarian cancer. Capture was performed according to the manufacturer’s instructions using an NGS Workstation Option B (Agilent) for automated library preparation starting with 3 μg DNA per sample. Sequencing was performed on a Illumina Hiseq 2500 system gnerating 2x100bp paired end reads and a target coverage of >200 per sample. Sequence reads were mapped to the haploid human reference genome (hg19) using BWA. Variants where called with FreeBayes v1.1.

  Dataset EGAD00001005279

• The Genetic Architecture of Smoking and Smoking Cessation

  This study includes samples from two projects: Collaborative Genetic Study of Nicotine Dependence (COGEND; PI: Laura Bierut) and University of Wisconsin Transdisciplinary Tobacco Use Research Center (UW-TTURC; PI: Timothy Baker). Data are available for an additional 1420 COGEND subjects through the Study of Addiction: Genetics and Environment (SAGE), dbGaP study accession phs000092. The majority of these subjects are independent from the current study, but there is a small amount of overlap between the two samples (n=29 subjects) for quality control purposes. It should be noted that the case definition in the SAGE study is DSM-IV alcohol dependence. The case definition in the current study is nicotine dependence by a current score of 4 or greater on the Fagerström Test for Nicotine Dependence (FTND). The overall goal of this project is to identify and characterize genetic variants that contribute to the development of nicotine dependence, related smoking behaviors, and smoking cessation. The COGEND sample includes unrelated cases and controls for a genetic association study of nicotine dependence. Cases are defined by a commonly used definition of nicotine dependence, a current score of 4 or more (maximum score of 10) on the Fagerström Test for Nicotine Dependence (FTND). Control status is defined as an individual who smoked at least 100 cigarettes during their lifetime, yet never became dependent (lifetime FTND=0). By selecting controls who smoked, those genetic effects that are specific to nicotine dependence can be examined. The UW-TTURC sample includes nicotine dependent smokers from three smoking cessation studies. Subjects had to smoke at least 10 cigarettes per day (confirmed smoking by an alveolar carbon monoxide (CO) level greater than 9) and report being motivated to quit smoking. Participants were excluded based on evidence of psychosis history, clinically significant depression symptoms, other severe mental illness, or contraindications to smoking cessation medications. COGEND: COGEND was initiated in 2001 as a three-part program project grant funded through the National Cancer Institute (NCI; PI: Laura Bierut). The three projects included a study of the familial transmission of nicotine dependence, a genetic study of nicotine dependence, and a study of the relationship of nicotine dependence with nicotine metabolism. The primary goal is to detect, localize, and characterize genes that predispose or protect an individual with respect to heavy tobacco consumption, nicotine dependence, and related phenotypes and to integrate these findings with the family transmission and nicotine metabolism findings. The primary design is a community based case-control family study. Nicotine dependent cases and non-dependent, smoking controls were identified and recruited from Detroit and St. Louis. In addition, one sibling for each case and control subject was recruited in a subset of the sample. More than 54,000 subjects aged 25-44 years were screened by telephone; more than 3,100 subjects were personally interviewed; and more than 2,900 subjects donated blood samples for genetic studies. UW-TTURC: The UW-TTURC was initiated in 2001 as a study of nicotine dependence and smoking cessation treatment. The second round of UW-TTURC was initiated in 2005 as a study of efficacy of smoking cessation and long term outcomes. Nicotine dependent smokers seeking cessation treatment were identified and recruited from Madison and Milwaukee, WI. Over 9,000 adult smokers were screened by telephone; 2,575 individuals were enrolled and randomized to treatment conditions that involved use of different smoking cessation medications. Participants from the UW-TTURC smoking cessation clinical trials had the option of participating in a genetic substudy, and approximately 2,000 donated blood samples for genetic studies. The goal of the genetic studies of smokers seeking cessation treatment is to detect, localize, and characterize genes that predispose or protect an individual with respect to heavy tobacco consumption, nicotine dependence, and related phenotypes including cessation, withdrawal, and relapse. Both studies (COGEND and UW-TTURC) include measures of basic socio-demographic variables, including age, sex, race/ethnicity, family income, and educational attainment. Information on nicotine dependence, as assessed by the Fagerström Test for Nicotine Dependence (FTND) is available for all subjects. In addition, participants also completed the Nicotine Dependence Syndrome Scale (NDSS; Shiffman et al., 2004) and the Wisconsin Inventory of Smoking Dependence Motives (WISDM-68; Piper et al, 2004). Coding for both individual variables and indices has been standardized across studies. All subjects were assessed in person by trained research assistants. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to the genetic architecture of smoking through large-scale genome-wide association studies of two well-characterized cohorts. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.

  Study phs000404

• Ultra-Fast Patient-Derived Xenografts Identify Functional and Spatial Tumour Heterogeneities that Drive Therapeutic Resistance

  Treatment of patients with advanced cancers increasingly relies on agents targeting specific molecular or cellular aberrations. These expensive therapies often fail because of pre-existing drug resistance. Intra-tumoural molecular and micro-environmental heterogeneity resistance can create resistance in one or more subclones of a tumour, leading to spatio-functional heterogeneity. We created a rapid approach for quantifying tumour functional phenotypes based on tumour-implantation into the chorioallantoic membrane of chick embryos. We apply this technique to 43 separate biopsies from 6 patients with renal cell carcinoma (RCC) with 36 replicates per biopsy, achieving a 93.6% engraftment rate (1449/1548). Challenging these models with sunitinib, an anti-angiogenic therapy frequently used in RCC allowed us to quantify spatio-functional heterogeneity in individual patients. Prediction of de novo drug resistance in advanced cancer patients would facilitate precision medicine by tailoring systemic therapies and improve clinical trial design outcome measures. We describe a patient-derived xenograft platform where fresh patient tumour samples are implanted into the chorioallantoic membrane (CAM) of chick embryos at high engraftment efficiencies, permitting large scale “tumour avatar” studies to guide the selection of drugs and to predict clinical drug resistance outcomes in renal cell carcinoma (RCC) patients. Applying this “tumour avatar” model in a co-clinical trial on RCC patients, we observe intra-tumoural functional heterogeneity with sunitinib treatment, revealing the presence of drug-resistant clones prior to the initiation of therapy. Multi-regional exome Matched DNA sequencing of the primary tumour and metastases revealed DNA mutational signatures associated with sunitinib resistance at baseline and after treatment. These These studies demonstrate a rapid and affordable method of findings confirm the existence of genetic and surveying functional tumour heterogeneities heterogeneity.

  Study EGAS00001002627

• Highly complex single-cell mixture of 5 individuals of low cell number

  Mixture of 5 unrelated individuals sequenced by 10x as a scATAC-seq with low cell count. The dataset was then processed by Cell Ranger and deconvoluted to yield each individuals genetic profile using the De-goulash pipeline. The separation file is submitted as the processed file. The bam are submitted as unprocessed files.

  Dataset EGAD50000000479

• WGA_Fulani_Database

  In total, 329 DNA samples were genotyped on the Illumina Infinium H3Africa Consortium array (designed for 2,271,503 SNPs; using BeadChip type: H3Africa_2019_20037295_B1). Genotyping was performed at the SNP&SEQ Technology Platform (NGI/SciLifeLab Genomics, Sweden). WGA Fulani dataset includes individuals from the following populations: 33 BurkinaFaso_FulaniBanfora, 32 BurkinaFaso_FulaniTindangou, 33 Mali_FulaniDiafarabe, 35 Cameroon_FulaniTcheboua, 34 Chad_FulaniBongor, 24 Chad_FulaniLinia, 25 Niger_FulaniAbalak, 32 Niger_FulaniAder, 31 Niger_FulaniDiffa, 20 Niger_FulaniBalatungur, and 30 Niger_FulaniZinder.

  Dataset EGAD50000000654

• scRNA-seq from brain metastasis micorenvironment and cerebrospinal fluid

  A total of 9 brain metastasis were sequenced. For 6/9 a matched cerebrospinal fluid sample, prior to surgery and in two cases after surgery (+1 month from surgery) and after treatment (+3 month) were collected. Single-cell gene expression was produced using the Chromium Single Cell 5’ Library and sequenced on an Illumina NovaSeq 6000.

  Dataset EGAD00001006452

• McGill Sperm Methylome Capture Sequencing Data

  The study includes methylC-capture sequencing (MCC-Seq) on 94 sperm DNA samples derived from both fertile and infertile individuals who were recruited from the Men’s Health Clinic at the Royal Victoria Hospital, Montreal, Quebec. All the data were generated with 100bp paired-end reads using the Illumina NovaSeq 6000 systems.

  Dataset EGAD00001005795

• Dataset for the study - Detection of cell-free DNA fragmentation and copy number alterations in cerebrospinal fluid from glioma patients

  FASTQ files from sequencing to < 0.4x depth of coverage of thirteen glioma patients. Indexed sequencing libraries were prepared using a commercially available kit (ThruPLEX-Plasma Seq, Rubicon Genomics). Libraries were pooled in equimolar amounts and sequenced on a HiSeq 4000 (Illumina) generating 150-bp paired-end reads.

  Dataset EGAD00001004425

• scTCR-seq from brain metastasis micorenvironment and cerebrospinal fluid

  A total of 9 brain metastasis were sequenced. For 6/9 a matched cerebrospinal fluid sample, prior to surgery and in two cases after surgery (+1 month from surgery) and after treatment (+3 month) were collected. Single-cell T cell receptor clonotypes were produced using the Chromium Single Cell 5’ Library and sequenced on an Illumina NovaSeq 6000.

  Dataset EGAD00001006451

• Whole-genome sequence data for The interface of malignant and immunologic clonal dynamics in high-grade serous ovarian cancer

  Each tumor sample was cut into three pieces, yielding two end-pieces for cryovials and a middle portion placed in 10% buffered formalin. End pieces were homogenized manually and with a paddle blender (Stomacher). All paraffin-embedded blocks, including formalin-fixed tumor samples and molecular-fixed fallopian tubes, were sectioned and stained with hematoxylin and eosin prior to expert histopathological review to confirm the presence of high grade serous carcinoma. Homogenized end pieces were then flash frozen and later used for WGS. For all tumor and matched normal (peripheral blood) samples, DNA was extracted with the Qiagen AllPrep DNA/RNA kit (tumor samples from patients 25,26,28-32) or the Qiagen Blood and Tissue Extraction Kit (tumor samples from patients 1-4,7,9-17, and all blood samples). For all tumor and normal samples, DNA extraction was followed by library construction and sequencing using Illumina HiSeq2500 whole genome shotgun v4 chemistry with paired-end 125bp reads.

  Dataset EGAD00001003984

• Center for Common Disease Genomics [CCDG] - Cardiovascular: PEGASUS-TIMI 54

  This study is a part of NHGRI's Center for Common Disease Genomics, which is a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes. Current estimates anticipate that the CCDG program will sequence approximately 140K whole genomes and 225K whole exomes during the life of the project. The Cardiovascular Disease working group of the CCDG considered five diseases: early-onset coronary artery disease (EOCAD), stroke, atrial fibrillation, congestive heart failure and type 2 diabetes. Atrial fibrillation will affect between 6-12 million individuals in the US by 2050. AF also is associated with increased risks of stroke, dementia, heart failure, death, and high health care costs. Many risk factors for AF have been identified, including advancing age, cardiovascular disease (CVD), and CVD risk factors. However, there is little knowledge how to prevent AF. Furthermore, therapies for AF are only partially effective, and are themselves associated with substantial morbidity. Previously, heritable forms of AF have been considered rare; yet in the last decade, it has been established that AF, and in particular early-onset forms of AF, are heritable. Genome-wide association studies (GWAS) provide a powerful tool to identify common variants underlying disease risk. The AFGen Consortium currently consists of investigators from more than 25 studies with >20,000 individuals with AF and >100,000 without AF. In the latest analyses, 14 loci have been identified for AF1 . Broadly, the loci implicate genes related to cardiopulmonary development, cardiac-expressed ion channels, and cell signaling molecules. Source: ccdg.rutgers.eduFor this study, The Broad Institute of MIT and Harvard generated genetic data for 7,481 individuals from the PEGASUS-TIMI 54 clinical trial run by Brigham and Women's Hospital TIMI study group using whole exome sequencing and whole genome genotyping (Infinium Global Screening Array); all samples serving as controls.  

  Study phs002243

• Center for Common Disease Genomics [CCDG] - Cardiovascular: ENGAGE Atrial Fibrillation-TIMI 48

  This study is a part of NHGRI's Center for Common Disease Genomics, which is a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes. Current estimates anticipate that the CCDG program will sequence approximately 140K whole genomes and 225K whole exomes during the life of the project. The Cardiovascular Disease working group of the CCDG considered five diseases: early-onset coronary artery disease (EOCAD), stroke, atrial fibrillation, congestive heart failure and type 2 diabetes. Atrial fibrillation will affect between 6-12 million individuals in the US by 2050. AF also is associated with increased risks of stroke, dementia, heart failure, death, and high health care costs. Many risk factors for AF have been identified, including advancing age, cardiovascular disease (CVD), and CVD risk factors. However, there is little knowledge how to prevent AF. Furthermore, therapies for AF are only partially effective, and are themselves associated with substantial morbidity. Previously, heritable forms of AF have been considered rare; yet in the last decade, it has been established that AF, and in particular early-onset forms of AF, are heritable. Genome-wide association studies (GWAS) provide a powerful tool to identify common variants underlying disease risk. The AFGen Consortium currently consists of investigators from more than 25 studies with >20,000 individuals with AF and >100,000 without AF. In the latest analyses, 14 loci have been identified for AF1. Broadly, the loci implicate genes related to cardiopulmonary development, cardiac-expressed ion channels, and cell signaling molecules.Source: https://ccdg.rutgers.edu/sites/default/files/CCDG_CVD_EOAF_FINAL_w_link.pdfFor this study, The Broad Institute of MIT and Harvard generated genetic data for 13,667 individuals from the ENGAGE AF-TIMI 48 clinical trial run by Brigham and Women's Hospital TIMI study group using whole exome sequencing and whole genome genotyping (Infinium Global Screening Array); all cases with atrial fibrillation.

  Study phs002774

• POPRES: Population Reference Sample

  POPRES version 1 and 2 Technological and scientific advances, stemming in large part from the Human Genome and HapMap projects, have made large-scale, genome-wide investigations feasible and cost-effective. These advances have the potential to dramatically impact drug discovery and development by identifying genetic factors that contribute to variation in disease risk as well as drug pharmacokinetics, treatment efficacy, and adverse drug reactions. In spite of the technological advancements, successful application in biomedical research would be limited without access to suitable sample collections. To facilitate exploratory genetic research, we have assembled a DNA resource from a large number of subjects participating in multiple studies throughout the world. This resource was initially genotyped using the Affymetrix 500K SNP panel. This project includes nearly 6,000 subjects of African American, East Asian, South Asian, Mexican, and European origin. POPRES version 3 The discovery and development of novel drugs is challenging and with high attrition rates. Selection of the right target and optimal indications for novel therapeutics represent key decision points in this process, and are often hampered by our limited understanding of the biology of the target in humans. Building a robust body of knowledge of variation within drug target genes has in several cases increased the probability of success for novel therapeutics. Our knowledge of variation within drug target genes and their influence on traits of medical interest is still very limited. In an effort to fill this gap, we resequenced the exons of 202 known or suspected drug target genes in over 16,000 well-phenotyped individuals. A total of 863,883 bases were targeted, including 351 kb of coding and 323 kb of untranslated exon regions. The sequenced subjects included 3,381 from two studies that were part of the Population Reference Sample (POPRES) project: CoLaus (N = 2,059) and LOLIPOP (N = 1,322). Genotyping data generated through the targeted next generation sequencing is available through the dbGaP.

  Study phs000145

• H3Africa - Genomic and Environmental Risk Factors for Cardiometabolic Disease in Africans

  The long-term vision of the AWI-Gen Collaborative Centre (CC) is to build sustainable capacity in Africa for research that leads to an understanding of the interplay between genetic, epigenetic and environmental risk factors for obesity and related cardiometabolic diseases (CMD) in sub-Saharan Africa. The CC will be consolidated under the auspices of the University of the Witwatersrand (Wits) and the International Network for the Demographic Evaluation of Populations and Their Health in Developing Countries (INDEPTH). It will capitalize on the unique strengths of existing longitudinal cohorts, including the urban Soweto and rural Agincourt studies in South Africa (Wits based), and the well established INDEPTH demographic health and surveillance centers in Kenya, Ghana, Burkina Faso and South Africa. The centers offer established infrastructure, trained fieldworkers, long-standing community engagement, and detailed longitudinal phenotypic data, focusing on obesity and cardiometabolic health. Key strengths are harmonized phenotyping across sites, building on strong existing cohorts, and representation of the geographic and social variability of African populations. We aim to: 1. Build sustainable infrastructure (biobanks and laboratories) and capabilities (well characterized population cohorts, genotyping and bioinformatics) for genomic research on the African continent; 2. Understand the genomic architecture of sub-Saharan populations from west, east and south Africa to guide genomic studies (genome sequencing and high throughput SNP and CNV arrays using unrelated individuals and family trios to improve the accuracy of haplotype analyses) and; 3. Investigate the independent and synergistic genomic contributions to body fat distribution (BMI, hip/waist circumference, subcutaneous and visceral fat) in these populations considering the relevant environmental and social contexts (rural/urban communities, quickly transitioning obesity prevalence, differential HIV, TB, and malaria infection histories). We will investigate the effect of obesity and fat distribution on the risk for CMD in the longitudinal cohorts.

  Study EGAS00001002482

• ctDNA quantification in Ewing sarcoma patients

  Background. Treatment stratification and response assessment in pediatric sarcomas has relied on imaging studies and surgical/histopathological evidence of vital tumor cells. Such studies and evidence collection processes often involve radiation and/or general anesthesia in children. Cell-free circulating tumor DNA (ctDNA) detection in blood plasma is one available method of so-called liquid biopsies that has been shown to correlate qualitatively and quantitatively to some extent with the existence of vital tumor cells in the body. Our clinical observational study focused on the utility and feasibility of ctDNA detection in pediatric Ewing sarcoma (EWS) as a marker of minimal residual disease (MRD). Patients and Methods. We performed whole genome sequencing to identify the exact breakpoints in tumors known to carry the EWS-FLI1 fusion gene. Patient-specific fusion breakpoints were tracked in peripheral blood plasma using digital droplet PCR (ddPCR) before, during, and after therapy in six consecutive children and young adults with EWS. Presence and levels of fusion breakpoints were correlated with clinical disease courses. The genetic changes in the tumors were defined, and inter- and intra-individual changes in the tumor DNA copy loads were observed over time. Results. We show that the detection of ctDNA in the peripheral blood of EWS patients i) is feasible in the clinical routine and ii) allows for the longitudinal real-time monitoring of MRD activity in children and young adults. Although changing ctDNA levels correlated well with clinical outcome within patients, between patients, a high variability was observed (inter-individually) for the six patients described here. Conclusions. ctDNA detection by ddPCR is a highly sensitive, specific, feasible, and highly accurate method that can be applied in EWS for follow-up assessments as an additional surrogate parameter for clinical MRD monitoring and, potentially, also for treatment stratification in the near future.

  Study EGAS00001006433

• Detection of mutational patterns in cell free DNA (cfDNA) of colorectal cancer by custom amplicon sequencing

  Monitoring the mutational patterns of solid tumors during cancer therapy is a major challenge in oncology. Analysis of mutations in cell free (cf) DNA offers a non-invasive approach to detect mutations that may be prognostic for disease survival or predictive for primary or secondary drug resistance. A main challenge for the application of cfDNA as a diagnostic tool is the diverse mutational landscape of cancer. Here, we developed a flexible end-to-end experimental and bioinformatics workflow to analyze mutations in cfDNA using custom amplicon sequencing. Our approach relies on open software tools to select primers suitable for multiplex PCR using minimal cfDNA as input. In addition, we developed a robust linear model to identify specific genetic alterations from sequencing data of cfDNA. We used our method to design a custom amplicon panel suitable for detection of hotspot mutations relevant for colorectal cancer and analyzed mutations in serial cfDNA samples from 34 patients with advanced colorectal cancer. Our data demonstrates that recurrent and patient-specific mutational patterns can be reliably detected for the majority of patients. Furthermore, we show that the allele frequency of mutations in cfDNA correlates well with disease progression. Finally, we demonstrate that monitoring of cfDNA can outperform the predictive power of currently used tumor markers and reveal mechanisms of resistance to anti-EGFR antibody treatment.

  Study EGAS00001003382

• WGS of clonal organoids, bulk-tumor tissues, and matched blood samples derived from metastatic colorectal cancer patients

  This dataset consists of WGS fastq files from 58 clonal organoids and 18 fresh-frozen (FT) bulk-tissue samples from surgically resected primary and metastatic tumors before and after anticancer therapies in 6 patients with matched blood control samples from each patient. After DNA extraction from each sample using DNeasy Blood and Tissue Kit (Qiagen), library preparation was done using TruSeq DNA PCR-free kit. Then, paired-end fastq files were generated using Illumina NovaSeq 6000.

  Dataset EGAD50000001493

• Alcohol Dependence: Sequencing from Multiplex Families

  Two multiplex for alcohol dependence family studies were initiated based on the gender of a pair of probands. Ascertainment of a pair of AD probands was used to increase the density of alcohol dependence within the family. Identification of male (Cognitive and Personality Factors in Relatives of Alcoholics Family Study) and female (Biological Risk Factors in Female Alcoholics Family Study) alcohol dependent probands was accomplished by identifying an alcohol dependent proband while in treatment in a substance abuse treatment facility in Pittsburgh and surrounding communities who provided contact information for a sibling whom he/she thought might be interested in participating. The studies had identical ascertainment requirements. DNA was banked for all willing participants.

  Study phs001775

• Grady Trauma Project (GTP)

  Not everyone exposed to traumatic experience develops Posttraumatic Stress Disorder (PTSD). Genetic background is one of the predisposing risk factors causing differential outcomes of trauma exposure. A primary goal of the Grady Trauma Project (GTP) is to pinpoint and understand genetic polymorphisms that contribute to development of PTSD. Both PTSD diagnosis binary labels and PTSD severity scores are studied as target phenotypes. Also, both candidate gene studies and genome-wide association studies are performed. Besides genetic variants, other measurements that are studied as risk factors for PTSD include lifetime history of trauma and peri-traumatic response. Study participants are primarily African American, trauma-exposed populations of low socioeconomic status recruited from Grady Memorial Hospital in Atlanta.

  Study phs002046

• Evaluating potential drug candidates for the treament of Henamgiopericytoma on patient derived cell line models

  Solitary fibrous tumor/Hemangiopericytoma (SFT/HPC) is a rare subtype of soft tissue sarcoma associated with NAB2-STAT6 gene fusions. This study established and characterized a novel SFT/HPC patient-derived cell line called SFT-S1. Potential drug candidates that could be repurposed for the treatment of SFT/HPC were screened. Screening was performed through RNA-Seq

  Dataset EGAD50000000039

• Variant calling from CC220-MM-001 cohorts A,B,D

  These are genomic and transcriptomic high risk molecular segments for 167 samples collected at baseline from deidentified patients enrolled in cohorts A,B or D in the CC-220-MM-001 clinical study. Data are provided in a patient call table in csv format. Calls are generated from WGS data with mutations called by mutect2 best practices pipeline, CNV calls from Battenberg; and RNA-seq aligned with star aligner and quantified by Salmon.

  Dataset EGAD50000000388

• A brain precursor atlas reveals the acquisition of developmental-like states in adult cerebral tumours

  We generated a single-cell RNA-seq atlas capturing over 100,000 cells spanning all stages of the mouse cerebral development. By examining data from over 100 cerebral tumour samples, our study reveals that, despite the phenotypic/genotypic differences between the tumour types, they are all comprised of developmental sublineages that map most closely to embryonic or juvenile stages of development.

  Dataset EGAD00001008746

• RNA-seq of cells cultured in vitro

  This dataset includes 90 samples profiled by high-throughput Illumina sequencing, in bam format, aligned to GRCh37. Normal human CD34+ cord blood (CB), bone marrow (BM), or post-natal thymus (PNT) cells were transduced with various combinations of T-ALL oncogenes and cultured in vitro.

  Dataset EGAD00001009750

• Genomic Data for Integrative Profiling of T790M Negative EGFR Mutated NSCLC

  Contains WES and RNA-seq for the 59 patients with first- and second-generation EGFR TKI-resistant metastatic EGFR-mutated NSCLC.

  Dataset EGAD00001010272

• RNA-Seq dataset for Malignant rhabdoid study

  Study describing the dynamics of chromatin organization within malignant rhabdoid tumors. This study describes how this chromatin organization changes upon SMARCB1 rescue within patient-derived organoid models from malignant rhabdoid tumors. Identification of a novel super-enhancer of MYC and identification of patient-specific enhancer utilization to activate MYC expression in these tumors.

  Dataset EGAD00001011819

• Whole exome sequencing analysis on patient-derived cervical cancer tissues and respective tumoroids

  Whole exome sequencing (WES) was performed on the matched tumor and organoid pairs from 7 cervical cancer patients. The DNA was sequenced on NovaSeq6000 platform with 8Gb sequencing coverage. WES data was mapped against human reference genome GRCh38 by using BWA (v0.7.5) mapping tool.

  Dataset EGAD00001006166

• Profiling the genomic landscape and evolutionary history of polyploid giant cancer cells in undifferentiated pleomorphic sarcomas

  Polyploid giant cancer cells (PGCCs), characterised by multi-nucleation and atypical nuclear morphology, are a common feature of undifferentiated pleomorphic sarcomas. While PGCCs may be a critical substrate for cancer evolution, their formation pathways and the genomic consequences of PGCCs remain relatively under explored. In this study, we characterise PGCCs in undifferentiated pleomorphic sarcomas, as well as their histological mimics, and use topographic single-cell DNA sequencing (scDNA-seq) to investigate their genomic landscape. We selected PGCCs based on their nuclear morphology, including mono-nucleated or multi-nucleated bizarre, misshapen nuclei and analysed them at single-cell resolution. Our findings highlight PGCCs as a highly heterogeneous and evolutionarily dynamic component of undifferentiated pleomorphic sarcomas.

  Study EGAS50000001445

• Whole-exome sequencing of breast cancer metastasis and corresponding blood samples

  This study included samples from metastatic breast cancer patients who underwent a biopsy in the context of SAFIR01 (NCT01414933), SAFIR02 (NCT02299999), SHIVA (NCT01771458) and MOSCATO (NCT01566019) prospective trials. These French multicentre trials used high throughput genome analysis on fresh frozen tumor biopsies as a therapeutic decision tool for metastatic cancer patients, with solid cancers (SHIVA, MOSCATO) or specifically with breast cancer (SAFIR01, SAFIR02). All patients gave their informed consent for translational research and genetic analyses of their somatic DNA. Overall, whole-exome sequencing for a total of 216 pairs of metastatic tumor and unmutated DNA derived from corresponding blood samples was performed using Illumina technology. The results of the analysis of the mutational profile of metastatic breast cancer was reported in Lefebvre et al. (PMID:28027327).

  Study EGAS00001001695

• Molecular sub-classification of hormone receptor-positive breast cancer

  Patients with estrogen and/or progesterone receptor-positive breast cancer benefit from hormonal treatment, yet high global death burdens due to high prevalence and long-term recurrence risk call for biomarkers to guide additional treatment approaches. From a prospective, observational study of postmenopausal early breast cancer patients treated with tamoxifen or aromatase inhibitors gene expression analyses of 612 tumors was performed using the NanoString® Breast Cancer 360 panel. We identified novel gene expression signatures, i.e. BRCAness and Tumor Inflammation Signature (associated with high tumor lymphocyte infiltration), that may aid to select high-risk patients in order to improve adjuvant treatment by targeting DNA repair deficiency or immune-checkpoints in addition to standard chemo-endocrine treatment. The overall goal is to foster novel concepts for a stratified early breast cancer management.

  Study EGAS00001004594

• RNAseq data of polyA+ RNA from Leukocytes from 624 individuals of the SardiNIA cohort.

  We sequenced the polyA+ of the RNA of the leukocytes from 624 sardinian individuals with RNAseq (Illumina 2000, an average of round 60M reads per sample, 51 + 51 nt). Combining the genotype information of the same individuals (already available from the ProgeNIA project) with the transcriptome data we identified 21,183 independent expression quantitative trait loci (eQTLs) and 6,768 independent splicing quantitative trait loci (sQTLs), including 619 novel QTLs that exhibit population-specific trait associations. Using family relationships, we identified 809 segregating expression outliers and provide a new approach to study large effect regulatory variants and their relevance to traits. Our results provide insight into the effects of regulatory variants and their relationship to population history and individual genetic risk.

  Study EGAS00001002105

• RNA sequencing on intestinal biopsies from inflammatory bowel disease patients treated with vehicle control, MEK inhibitor, or infliximab

  By investigating an intergenic haplotype on chr21q22, independently linked to inflammatory bowel disease (IBD), ankylosing spondylitis, primary sclerosing cholangitis and Takayasu’s arteritis, we discover that the causal gene, ETS2, is a master regulator of inflammatory responses in human macrophages and delineate how the risk haplotype increases ETS2 expression. Using a database of cellular signatures, we identified drugs that could modulate this pathway. To validate the anti-inflammatory activity of one class of small molecules ex vivo, we obtained biopsies from patients with active IBD and cultured these biopsies with a selective, non-ATP competitive MEK inhibitor (PD-0325901), infliximab (positive control), or DMSO (vehicle control) for 18 hours, then performed RNA sequencing.

  Study EGAS00001007534

• FLT3 is genetically essential for ITD-mutated leukemic stem cells but dispensable for human HSCs

  bulk RNA sequencing of AML patients It contains 18 samples from primary AML patients. Half of the samples are control samples and half of the samples are FLT3-ITD knock-out (edited for the FLT3-ITD mutation). It is using Illumina high-throughput technology

  Dataset EGAD50000000636

• Patient-tailored design for selective co-inhibition of leukemic cell subpopulations

  Single-cell RNA sequencing was performed on bone marrow mononuclear cells of 2 acute myeloid leukemia patients at refractory stage. The profiling was performed using 10x Genomics Chromium Single Cell 3ʹ Gene Expression platform. The raw data are available as fastq files.

  Dataset EGAD00001006360

• Dataset for neuroendocrine_adrenal_tumor-RNA

  Rare cancer sequencing data of 145 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008862

• Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Multi-Ethnic Samples (T2D-GENES) Follow-Up Study: Research Studies in Hong Kong

  The ~52,000 sample Type 2 Diabetes Exome Sequencing project is a collaboration of six consortia with various funding mechanisms that have joined together to investigate genetic variants for type 2 diabetes (T2D) using the largest T2D case/control sample set compiled to date. This includes samples from: Type 2 Diabetes Genetic Exploration by Next-generation sequencing in Multi-Ethnic Samples (T2D-GENES) Genetics of Type 2 Diabetes (GoT2D) Exome Sequencing Project (ESP) Slim Initiative in Genomic Medicine for the Americas (SIGMA) Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCAMP) Progress in Diabetes Genetics in Youth (ProDIGY) This data generated from the Hong Kong cohort was part of the T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples) consortium, which is a NIDDK-funded international research consortium that seeks to identify genetic variants for type 2 diabetes (T2D) through multiethnic sequencing studies. The T2D-GENES Project is a multi-ethnic sequencing study designed to assess whether less common variants play a role in T2D risk and to assess similarities and differences in the distribution of T2D risk variants across ancestry groups. The individuals were obtained from over 20 cohorts across the 6 consortia that are listed in Table 1. The strategy was to perform deep exome sequencing of individuals, 24,991 with T2D and 24,953 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. The T2D-GENES, ProDIGY and SIGMA studies, sequencing was performed at the Broad Institute using the Agilent v2 capture reagent or Illumina Rapid Capture on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, two of the cohorts below are not in dbGaP, due to the samples not being consented for deposition. This includes the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study and Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) study. The Exome Sequencing Project (ESP) was deposited in dbGaP as part of their initial study and the phs numbers for that project can be found here: https://esp.gs.washington.edu/drupal/dbGaP_Releases. Table 1. 52,000 sample T2D Case/Control Whole Exome Sequencing Studies Ancestry Consortia Study Countries of Origin # Cases # Controls African American T2D-GENES Project 1 Jackson Heart Study US 500 526 African American T2D-GENES Project 1 Wake Forest School of Medicine Study US 518 530 African American ESP Exome Sequencing Project (ESP) US 467 1374 African American T2D-GENES Follow-Up Study BioMe Biobank Program (BioMe) US 1297 1256 East Asian T2D-GENES Project 1 Korea Association Research Project Korea 526 561 East Asian T2D-GENES Project 1 and Follow-Up Study Singapore Diabetes Cohort Study; Singapore Prospective Study Program Singapore (Chinese) 1486 1568 East Asian T2D-GENES Follow-Up Study Korea SNUH South Korea 450 475 East Asian T2D-GENES Follow-Up Study Research Studies in Hong Kong (Hong Kong) Hong Kong 493 485 European T2D-GENES Project 1 Ashkenazi US, Israel 506 352 European T2D-GENES Project 1 Metabolic Syndrome in Men Study (METSIM) Finland 484 498 European GoT2D Finland-United States Investigation of NIDDM Genetics (FUSION) Study Finland 472 476 European GoT2D Kooperative Gesundheitsforschung in der Region Augsburg (KORA) Germany 97 90 European GoT2D UK Type 2 Diabetes Genetics Consortium (UKT2D) UK 322 320 European GoT2D Malmö-Botnia Study Finland, Sweden 478 443 European LuCamp Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) Denmark 997 997 European ESP Exome Sequencing Project (ESP) US 390 2843 European T2D-GENES Follow-Up Study Genetics of Diabetes and Audit Research Tayside Study (GoDARTS) Scotland, UK 960 966 European T2D-GENES Follow-Up Study Framingham Heart Study (FHS) US 396 596 Hispanic T2D-GENES Project 1 San Antonio Family Heart Study, San Antonio Family Diabetes/ Gallbladder Study, Veterans Administration Genetic Epidemiology Study, and the Investigation of Nephropathy and Diabetes Study Family Component US 272 218 Hispanic T2D-GENES Project 1 and SIGMA v2 Starr County, Texas US 1762 1738 Hispanic SIGMA v1 Mexico City Diabetes Study Mexico 281 549 Hispanic SIGMA v1 and SIGMA v2 Multiethnic Cohort (MEC) US 1476 1443 Hispanic SIGMA v1 and SIGMA v2 UNAM/INCMNSZ Diabetes Study (UIDS) Mexico 1998 1977 Hispanic SIGMA v1 and SIGMA v2 Diabetes in Mexico Study (DMS) Mexico 1522 1546 Multiethnic ProDIGY Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) US 3097 0 Multiethnic ProDIGY SEARCH for Diabetes in Youth (SEARCH) US 553 0 South Asian T2D-GENES Project 1 London Life Sciences Population Study (LOLIPOP) UK (Indian Asian) 531 538 South Asian T2D-GENES Project 1 and Follow-Up Study Singapore Indian Eye Study Singapore (Indian Asian) 1640 1478 South Asian T2D-GENES Follow-Up Study Pakistan Risk of Myocardial Infarction Study (PROMIS) Pakistan 914 932 The research studies in Hong Kong contributed 493 cases and 485 controls to T2D-GENES Follow-Up study.

  Study phs001504

• Gene expression profiles of single disseminated breast cancer cells

  A set of 56 EpCAM-positive cells derived from bone marrow aspirates of breast cancer patients or patients without a cancererous disease (30 cells from 21 M0-stage and 11 cells from five M1-stage breast cancer patients, 15 cells from seven non-cancer patients serving as controls). EpCAM-positive cells from breast cancer patients were considered disseminated tumor cells as they harbored copy number alterations and showed high expression of the epithelial marker EpCAM and the mammary luminal progenitor marker KIT in comparison to EpCAM-positive bone marrow cells from non-cancer patients. Paired-end RNA-Sequencing of the samples was performed on Illumina NovaSeq6000, raw data are provided in the Fastq format.

  Dataset EGAD00001006359

• Cancer Genome Project Exome Sequencing

  Agilent whole exome hybridisation capture was performed on genomic DNA derived from cancer and matched normal DNA from the same patients. Next Generation sequencing performed on the resulting exome libraries and mapped to build 37 of the human reference genome to facilitate the identification of novel cancer genes. Now we aim to re find and validate the findings of those exome libraries using bespoke pulldown methods and sequencing the products.

  Dataset EGAD00001000289

• Quantitative analysis of a novel DNA hypermethylation panel using bronchial specimen for lung cancer diagnosis

  The dataset includes IDAT raw files for 10 samples and the analyzed DMP file which describes the differential methylation positions based on Illumina Infinium MethylationEPIC BeadChip. All samples (5 lung cancer cases vs. 5 benign lung disease controls) were obtained from bronchial washings at the site of the lesion under bronchoscopy manipulation. The histological type of the five lung cancer cases is adenocarcinoma and squamous cell carcinoma.

  Dataset EGAD00010002465

• Clinical panel sequencing of cancer of unknown primary using TruSight Oncology 500 (TSO500)

  TruSight Oncology 500 (TSO500) cancer panel sequencing data on paired tumour and germline DNA from cancer of unknown primary samples. All of the samples in this dataset are matched to WGS data. This data was used to compare biomarker yield against what was achieved with WGS and contains n=51 tumour-only samples. All samples are in BAM format aligned with GRCh38 reference genome.

  Dataset EGAD50000000657

• Recalibrated alignment files of Saudi Thyroid Cancer

  The dataset consists of samples from papillary thyroid cancer patients. A total of 292 DNA samples from blood/normal and cancer tissue are subjected to whole exome sequencing using Illumina. The fastq files generated were aligned with reference genome ‘hg19’, duplicates were marked, realignment around indels and quality recalibration were performed to produce good quality variants. The recalibrated “.bam” files are included with this dataset.​

  Dataset EGAD00001003950

• Access to "A Spatially Resolved Single-Cell Atlas of the Human Fetal Olfactory System"

  The human nasal region arises from neural crest and placodal lineages, yet its early development remains poorly understood owing to limited fetal tissue access and structural complexity. Here we present an integrated single-nucleus and spatial transcriptomic atlas of the human fetal nasal region, generated from 10 fetuses (males and females) between 7 and 12 post-conceptional weeks. Single-nucleus RNA sequencing resolved 32 distinct cell types, while integration with multiplexed error-robust fluorescence in situ hybridization (MERFISH) enabled spatial and temporal mapping of gene expression dynamics across the olfactory epithelium (OE) and adjacent tissues. We identify novel markers of olfactory sensory neuron differentiation and pathways governing epithelial patterning and OE morphogenesis. Notably, spatially organized expression of 169 olfactory receptor genes reveals molecular evidence for the “one neuron-one receptor” principle during the first trimester. Together, this work establishes the first molecular and spatial framework of early human olfactory development and provides a foundational resource for studies of sensory neurogenesis and congenital disorders.

  Dac EGAC50000000688

• Genome Diversity in Africa Project: Benin (2021-02-16)

  Globally, human populations show structured genetic diversity as a result of geographical dispersion, selection and drift. Understanding this genetic variation can provide insights into the evolutionary processes that shape both human adaptation and variation in disease. Populations from SSA have the highest levels of genetic diversity. This characteristic, in addition to historical genetic admixture, can lead to complexities in the design of studies assessing the genetic determinants of disease and human variation. However, such studies of African populations are also likely to provide new opportunities to discover novel disease susceptibility loci and variants and refine gene-disease association signals. A systematic assessment of genetic diversity within SSA would facilitate genomic epidemiological studies in the region. The Genome Diversity in Africa Project (GDAP) aims to produce a comprehensive catalogue of human genetic variation in SSA, including single nucleotide polymorphisms (SNPs), structural variants, and haplotypes. This resource will make a substantial contribution to understanding patterns of genetic diversity within and among populations in SSA, as well as providing a global resource to help design, implement and interpret genomic studies in SSA populations and studies comprising globally diverse populations, complementing existing genomic resources. Specifically, we plan to carry out high depth whole genome sequencing of up to 2000 individuals across Africa (25 individuals from each ethnolinguistic group). Our scientific objectives are to: 1) develop a resource that provides a comprehensive catalogue of genetic variation in populations from SSA accessible to the global scientific community; 2) characterise population genetic diversity, structure, gene flow and admixture across SSA; 3) develop a cost-efficient, next-generation genotype array for diverse populations across SSA; and 4) facilitate whole genome-sequencing association studies of complex traits and diseases by developing a reference panel for imputation and resource for enhancing fine-mapping disease susceptibility loci. These scientific objectives will be supported by cross-cutting operational activities, including network and management of the consortium, research ethics, and research capacity building in statistical genetics and bioinformatics This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2021-02-16.

  Dataset EGAD00001006970

• Aboriginal Genetics and Health Studies based at the Telethon Kids Institute, Perth, Western Australia

  Dac EGAC00001000261

• Inhibition of CDK4/6 Promotes CD8 T Cell Memory

  Inhibitors of Cyclin-Dependent Kinase 4 and 6 (CDK4/6) have been recently deployed for the treatment of advanced breast cancer. Despite their success, the mechanism of action of these drugs is unclear. In mice, treatment with a CDK4/6 inhibitor improve T cell memory responses and protect mice against tumor rechallenge. We aimed to identify the correlates of this finding in human subjects. In this study, blood was collected from 5 breast cancer patients before and during treatment with the CDK4/6 inhibitors abemaciclib or palbociclib. Blood was also collected from 2 breast cancer patients who did not receive a CDK4/6 inhibitor. Recently activated CD8 T cells (CD45RO+ CD45RA+) were sorted and subjected to single-cell RNA sequencing.

  Study phs002448

• eMERGE: Northwestern (NUgene) WGS

  The NUgene Project is a biorepository with longitudinal medical information from participating patients at Northwestern Medicine affiliated hospitals and outpatient clinics. Participants' DNA samples are coupled with data from a self-reported questionnaire (2 versions were used, 1 before and 1 after February 2006, both are included) and continuously updated data from our Electronic Medical Record (EMR) representing actual clinical care events. Northwestern has a state-of-the art, comprehensive inpatient and outpatient EMR system of over 3 million patients. NUgene has broad access to participant data for all outpatient visits as well as inpatient data via a consolidated enterprise data warehouse. NUgene participants consent to distribution and use of their coded DNA samples and data for a broad range of genetic research by third-party investigators. The electronic MedicalRecords and Genomics (eMERGE) Network is a consortium of 9 clinical sites with EMR linked DNA biobanks, including Northwestern University and its NUgene biobank, funded by the NHGRI (National Human Genome Research Institute) to investigate the use of electronic medical record systems for genomic research. The goal of eMERGE is to conduct genome-wide association studies in approximately 100,000 individuals using EMR-derived phenotypes and DNA from linked biorepositories. Using electronic phenotyping methods, the consortium has been and is using DNA samples from all participating sites to explore the genetic determinants of approximately 80 phenotypes, including both diseases and traits, for which the electronic phenotyping algorithms have or are being published on PheKB.org. Thus, for the eMERGE network, ~900 NUgene subjects were selected, as described in the study inclusion/exclusion criteria section below, to be genotyped using whole genome sequencing (WGS), for use in the eMERGE network as eMERGE subjects. The criteria used below were selected so that these subjects will likely meet the criteria to be cases and/or controls, of diverse races and/or ethnicities, for at least 1 of the ~80 phenotypes being studied within eMERGE, and could be recontacted for future research if needed.

  Study phs001191

• GoT2D: Genetics of Type 2 Diabetes, a study of the the genetic architecture of type 2 diabetes using low pass whole genome sequencing and high density SNP genotyping in 2,657 individuals.

  The Genetics of Type 2 Diabetes Consortium (GoT2D) is a collaboration between the University of Michigan, the Broad Institute and the Wellcome Trust Centre for Human Genetics. The overall aim is to extend upon recent efforts, such as genome-wide association studies (GWAS) and large scale meta-analyses. While they have proved successful at mapping genomic loci that influence human diseases, like type 2 diabetes, much of the heritability remains unexplained. In this study, we use next generation sequencing and genotyping technologies to query for lower frequency variants in the human genome. Thereby, allowing a deeper characterization of the spectrum of alleles associated with type 2 diabetes risk, and a better assessment of the genes that play a role in the etiology of type 2 diabetes development. We studied 1,326 T2D cases and 1,331 normoglycemic controls from Northern and Central Europe (Sweden, Finland, UK, and Germany). To efficiently characterize the entire genome sequence of each individual, we performed low-coverage (~5x) whole-genome sequencing, augmented by deep coverage (~100x) sequencing of the exome, and dense (2.5M) single nucleotide polymorphism (SNP) genotyping using the HumanOmni2.5 array. The data deposited in EGA will include all the Swedish, Finnish, UK, and German samples.

  Study EGAS00001001459

• BAM files of targeted next-generation DNA sequencing data of 13 chordoid gliomas of the third ventricle

  BAM files of targeted next-generation DNA sequencing data of 13 chordoid gliomas of the third ventricle (2 paired tumor-normal samples and 11 tumor-only samples). Genomic DNA was extracted from formalin-fixed, paraffin-embedded blocks of tumor tissue from 13 patients with chordoid glioma of the third ventricle using the QIAamp DNA FFPE Tissue Kit (Qiagen). Genomic DNA was also extracted from leukocytes in a peripheral blood sample from one of the patients and a non-neoplastic gastric biopsy specimen from one of the patients. Capture-based next-generation DNA sequencing was performed at the University of California, San Francisco Clinical Cancer Genomics Laboratory, using an assay that targets all coding exons of approximately 500 cancer-related genes, select introns of 47 genes, and TERT promoter with a total sequencing footprint of 2.8 Mb (UCSF500 Cancer Panel). Sequencing libraries were prepared from genomic DNA, and target enrichment was performed by hybrid capture using a custom oligonucleotide library (Nimblegen SeqCap EZ Choice). Captured libraries were sequenced as paired-end 100 bp reads on an Illumina HiSeq 2500 instrument. Duplicate sequencing reads were removed computationally to allow for accurate allele frequency determination and copy number calling.

  Dataset EGAD00001003818

• scRNAseq data of CAP

  Fastq files from scRNAseq data of cancer associated pericytes-like from 3 patients. CAP were isolated from a total of 3 primary BC (surgical residues prior to any treatment) by using BDFACS ARIA III sorter (BD Biosciences). BC were collected directly from the operating room after surgical specimen macroscopic examination and selection of areas of interest by a pathologist. Samples were cut into small pieces (around 1 mm3) and digested in CO2-independent medium (Gibco #18045-054) supplemented with 150 μg/mL liberase (Roche #05401020001) and Dnase I (Roche #11284932001) for 40 min at 37°C with shaking (180 rpm). After digestion, cells were processed and stained as described above (#Flow Cytometry analysis of BC samples). CAP fibroblasts were then gated on the Live/Dead negative fraction and defined as EPCAM- CD45- CD31- CD235a- FAPMed CD29High. CAP scRNA-seq: Upon isolation, CAP cells were directly collected into RNase-free tubes (Thermo Fisher Scientific, #AM12450) precoated with DMEM (GE Life Sciences, #SH30243.01) supplemented with 10% FBS (Biosera, #1003/500). Single-cell capture, lysis, and cDNA library construction were performed using Chromium system from 10X Genomics, with the following kits: Chromium Single Cell 3′ Library & Gel Bead Kit v2 kit (10X Genomics, #120237) and Chromium Single Cell A Chip Kits (10X Genomics, #1000009). Generation of gel beads in Emulsion (GEM), barcoding, post GEM-reverse transcription cleanup and cDNA amplification were performed according to the manufacturer’s instructions. Cells were loaded accordingly on the Chromium Single cell A chips, and 12 cycles were performed for cDNA amplification. cDNA quality and quantity were checked on Agilent 2100 Bioanalyzer using Agilent High Sensitivity DNA Kit (Agilent, #5067-4626) and library construction followed according to 10X Genomics protocol. Libraries were next run on the Illumina HiSeq (for patients P1) and NovaSeq (for patients P2–3) with a depth of sequencing of 50,000 reads per cell.

  Dataset EGAD50000000321

• Framingham Cohort

  Startup of Framingham Heart Study. Cardiovascular disease (CVD) is the leading cause of death and serious illness in the United States. In 1948, the Framingham Heart Study (FHS) -- under the direction of the National Heart Institute (now known as the National Heart, Lung, and Blood Institute, NHLBI) -- embarked on a novel and ambitious project in health research. At the time, little was known about the general causes of heart disease and stroke, but the death rates for CVD had been increasing steadily since the beginning of the century and had become an American epidemic. The objective of the FHS was to identify the common factors or characteristics that contribute to CVD by following its development over a long period of time in a large group of participants who had not yet developed overt symptoms of CVD or suffered a heart attack or stroke. Design of Framingham Heart Study. In 1948, the researchers recruited 5,209 men and women between the ages of 30 and 62 from the town of Framingham, Massachusetts, and began the first round of extensive physical examinations and lifestyle interviews that they would later analyze for common patterns related to CVD development. Since 1948, the subjects have returned to the study every two years for an examination consisting of a detailed medical history, physical examination, and laboratory tests, and in 1971, the study enrolled a second-generation cohort -- 5,124 of the original participants' adult children and their spouses -- to participate in similar examinations. The second examination of the Offspring cohort occurred eight years after the first examination, and subsequent examinations have occurred approximately every four years thereafter. In April 2002 the Study entered a new phase: the enrollment of a third generation of participants, the grandchildren of the original cohort. The first examination of the Third Generation Study was completed in July 2005 and involved 4,095 participants. Thus, the FHS has evolved into a prospective, community-based, three generation family study. The FHS is a joint project of the National Heart, Lung and Blood Institute and Boston University. Research Areas in the Framingham Heart Study. Over the years, careful monitoring of the FHS population has led to the identification of the major CVD risk factors -- high blood pressure, high blood cholesterol, smoking, obesity, diabetes, and physical inactivity -- as well as a great deal of valuable information on the effects of related factors such as blood triglyceride and HDL cholesterol levels, age, gender, and psychosocial issues. Risk factors have been identified for the major components of CVD, including coronary heart disease, stroke, intermittent claudication, and heart failure. It is also clear from research in the FHS and other studies that substantial subclinical vascular disease occurs in the blood vessels, heart and brain that precedes clinical CVD. With recent advances in technology, the FHS has enhanced its research capabilities and capitalized on its inherent resources by the conduct of high resolution imaging to detect and quantify subclinical vascular disease in the major blood vessels, heart and brain. These studies have included ultrasound studies of the heart (echocardiography) and carotid arteries, computed tomography studies of the heart and aorta, and magnetic resonance imaging studies of the brain, heart, and aorta. Although the Framingham cohort is primarily white, the importance of the major CVD risk factors identified in this group have been shown in other studies to apply almost universally among racial and ethnic groups, even though the patterns of distribution may vary from group to group. In the past half century, the Study has produced approximately 1,200 articles in leading medical journals. The concept of CVD risk factors has become an integral part of the modern medical curriculum and has led to the development of effective treatment and preventive strategies in clinical practice. In addition to research studies focused on risk factors, subclinical CVD and clinically apparent CVD, Framingham investigators have also collaborated with leading researchers from around the country and throughout the world on projects involving some of the major chronic illnesses in men and women, including dementia, osteoporosis and arthritis, nutritional deficiencies, eye diseases, hearing disorders, and chronic obstructive lung diseases. Genetic Research in the Framingham Heart Study. While pursuing the Study's established research goals, the NHLBI and the Framingham investigators has expanded its research mission into the study of genetic factors underlying CVD and other disorders. Over the past two decades, DNA has been collected from blood samples and from immortalized cell lines obtained from Original Cohort participants, members of the Offspring Cohort and the Third Generation Cohort. Several large-scale genotyping projects have been conducted in the past decade. Genome-wide linkage analysis has been conducted using genotypes of approximately 400 microsatellite markers that have been completed in over 9,300 subjects in all three generations. Analyses using microsatellite markers completed in the original cohort and offspring cohorts have resulted in over 100 publications, including many publications from the Genetics Analysis Workshop 13. Several other recent collaborative projects have completed thousands of SNP genotypes for candidate gene regions in subsets of FHS subjects with available DNA. These projects include the Cardiogenomics Program of the NHLBI's Programs for Genomics Applications, the genotyping of ~3000 SNPs in inflammation genes, and the completion of a genome-wide scan of 100,000 SNPs using the Affymetrix 100K Genechip. Framingham Cohort Phenotype Data. The phenotype database contains a vast array of phenotype information available in all three generations. These will include the quantitative measures of the major risk factors such as systolic blood pressure, total and HDL cholesterol, fasting glucose, and cigarette use, as well as anthropomorphic measures such as body mass index, biomarkers such as fibrinogen and CRP, and electrocardiography measures such as the QT interval. Many of these measures have been collected repeatedly in the original and offspring cohorts. Also included in the SHARe database will be an array of recently collected biomarkers, subclinical disease imaging measures, clinical CVD outcomes as well as an array of ancillary studies. The phenotype data is located here in the top-level study phs000007 Framingham Cohort. To view the phenotype variables collected from the Framingham Cohort, please click on the "Variables" tab above. The Framingham Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the "Substudies" section of this top-level study page phs000007 Framingham Cohort. phs000342 Framingham SHARe phs000282 Framingham CARe phs000363 Framingham SABRe phs000307 Framingham Medical Resequencing phs000401 Framingham ESP Heart-GO phs000651 Framingham CHARGE-S phs000724 Framingham DNA Methylation phs001610 Framingham T2D-GENES phs002558 Framingham ADSP phs002559 Framingham BRIDGET phs002560 Framingham Cholesterol phs002611 Framingham Post-Mortem Brain Tissue phs002938 Framingham Molecular QTL The unflagging commitment of the research participants in the NHLBI FHS has made more than a half century of research success possible. For decades, the FHS has made its data and DNA widely available to qualified investigators throughout the world through the Limited Access Datasets and the FHS DNA Committee, and the SHARe database will continue that tradition by allowing access to qualified investigators who agree to the requirements of data access. With the SHARe database, we continue with an ambitious research agenda and look forward to new discoveries in the decades to come.

  Study phs000007

• A New Reference Panel to Boost African American Genotype Imputation

  Modern genetic studies have been conducted predominantly in cohorts of individuals of European ancestry. By 2010, there were approximately ten times as many published genome wide association studies (GWAS) in people of European ancestry than studies in people of all other ancestries combined. This research disparity has led to an uneven understanding of the genetic basis underlying disease in Europeans and non-Europeans. 23andMe's web-based, large scale research model is ideal for scaling genetics research within non-European populations and thereby bringing more parity to genetics research. Our database is composed of genotypes and phenotypes of over 1,000,000 consenting customers, including over 200,000 individuals with non-European ancestry. The data derived from non-European individuals represent a particularly valuable resource for genetic discovery of novel variants that may not be found in the European population. However, research studies in non-European populations are weakened by the lack of availability of large-scale reference datasets and, in particular, genotype imputation panels. Genotype imputation is a statistical methodology that uses observations of genotypes in a large reference panel to infer unobserved genotypes in a target dataset. This methodology is widely used within GWAS, and allows novel genetic associations to be identified and refined. Due to this utility, very large reference panels have been constructed, containing thousands or tens of thousands of whole genome sequences. Unfortunately, the largest imputation panels are composed of predominantly European genomes, reflecting the modern bias towards European studies in GWAS. This proposal aims to address this imbalance by constructing an imputation panel specifically for the African American population. In doing so, we will expand 23andMe's ability to perform genetic discovery in non-European populations, and improve the understanding of global genetic variation underlying diseases and traits. Key commercial outcomes of the research include the identification of novel genetic targets for internal and external therapeutic development. The long-term aim is to improve understanding of disease in minority populations, which we hope may eventually lead to improved treatments of disease in these historically medically understudied groups.

  Study phs001798

• National Institute of Mental Health (NIMH) Duke Cognition Cohort

  The overall goal is to identify genetic variants influencing normal variation between humans, with a focus on cognitive and neurosensory traits. Because of the focus of funding agencies on disease, very few studies of the genetics of non-disease traits have been performed. The genetic variation underlying the vast majority of differences between humans therefore remains not only undiscovered, but also unexplored. We have assessed >1,200 healthy volunteers for >70 diverse, non-disease phenotypes, with a focus on cognitive and neurosensory traits that are understudied and seem to have a strong biological basis. Our study includes measurements of face recognition, night vision, cognitive performance, auditory pitch discrimination, contagious yawn susceptibility, time perception, sense of direction, taste preferences, personality, sexual behaviors, sleep habits, acne, headache locations, synesthesia, and teeth sensitivity. This method is very different from the focus of most studies on collecting cohorts of patients with disease and controls with minimal phenotypic information. Because we phenotype the same healthy volunteers for multiple highly variable yet heritable traits, we can perform genetic analyses on a large number of phenotypes by just investing once in sequencing the DNA of these participants. An additional >2,000 participants in our cohort have been measured just for cognitive performance instead of for the more extensive phenotyping. Most of the genetic studies in this cohort have been about cognitive perfromance. The number of participants with genetic data generated who have undergone the more extensive phenotyping is limited. Our studies of the more novel traits like contagious yawning have therefore focused more on correlations between different phenotypes until we have a sufficient sample size to truly attempt to make genetic discoveries. . The dataset also includes two small challenge studies. In one study, the cognitive performance of 150 healthy volunteers was measured before and after an acute dose of the antiepileptic drug topiramate. In the other study, the cognitive performance of 13 healthy volunteers was measured before and after 24 hours of sleep deprivation.

  Study phs001406

• The Dynamic Landscape of Open Chromatin During Human Cortical Neurogenesis

  Non-coding regions comprise most of the human genome and harbor a significant fraction of risk alleles for neuropsychiatric diseases, yet their functions remain poorly defined. We created a high-resolution map of non-coding elements involved in human cortical neurogenesis by contrasting chromatin accessibility and gene expression in the germinal zone and cortical plate of the developing cerebral cortex. To obtain a high resolution depiction of chromatin structure and gene expression in developing human fetal cortex, we dissected the post-conception week (PCW) 15-17 human neocortex into two major anatomical divisions to distinguish between proliferating neural progenitors and post mitotic neurons: (1) GZ: the neural progenitor-enriched region encompassing the ventricular zone (VZ), subventricular zone (SVZ), and intermediate zone (IZ) and (2) CP: the neuron-enriched region containing the subplate (SP), cortical plate (CP), and marginal zone (MZ). Tissues were obtained from three independent donors and three to four technical replicates from each tissue were processed for ATAC-seq to define the landscape of accessible chromatin and RNA-seq for genome-wide gene expression profiling.

  Study phs001438

• Upper cortical layer-driven network impairment in schizophrenia

  Schizophrenia is one of the most wide-spread and complex mental disorders. To characterize the impact of schizophrenia, we performed single nucleus RNA sequencing (snRNA-seq) of >220,000 neurons from the dorsolateral prefrontal cortex of patients with schizophrenia and matched controls. Additionally, >115,000 neurons were analyzed topographically by immunohistochemistry. Compositional analysis of snRNA-seq data revealed a reduction in abundance of GABAergic neurons and a concomitant increase in principal neurons, most pronounced for upper cortical layer subtypes, which was substantiated by histological analysis. Many neuronal subtypes showed extensive transcriptomic changes, the most dramatic - in upper layer GABAergic neurons, including downregulation in energy metabolism and upregulation in neurotransmission. Transcription factor network analysis demonstrated a developmental origin of transcriptomic changes. Finally, Visium spatial transcriptomics further corroborated upper layer neuron vulnerability in schizophrenia. Overall, our results point towards general network impairment within upper cortical layers as a core substrate associated with schizophrenia symptomatology. Study is available on bioRxiv (https://doi.org/10.1101/2020.11.17.386458) and in upcoming publication.

  Study EGAS00001006495

• High-throughput single-cell DNA sequencing of acute myeloid leukemia tumors with droplet microfluidics

  We developed a novel microfluidic platform to automatically barcode genomic DNA from individual cancer cells. Using this approach, we sequenced acute myeloid leukemia (AML) tumors targeting up to 62 loci relevant for the disease from thousands of cells. We predict that our platform will enable analysis of heterogeneity in AML and improve stratification and therapy selection.

  Study phs001627

• WES Analysis of precancerous lesions in Lynch Syndrome

  The project focuses on identifying the genetic alterations involved in the early stages of tumor development in individuals with Lynch Syndrome. Using Whole Exome Sequencing (WES), the study aims to characterize somatic mutations and molecular pathways that drive the transformation from normal tissue to precancerous lesions. This research contributes to a better understanding of tumorigenesis in hereditary colorectal cancer syndromes.

  Study EGAS50000001546

• Whole genome analysis of pediatric patients with medulloblastoma

  Cancer genomes often contain structural variations (SVs) in non-coding regions, while its impact on tumorigenesis is still unclear. Our goal is to discover genome folding changes resulted from SVs using InfoGenomeR and InfoHiC frameworks, which may reveal novel therapeutic targets. We applied our frameworks to five pediatric patients with medulloblastoma, revealing 3D genome changes of medulloblastoma driver genes.

  Study EGAS00001006653

• Single cell RNA-sequencing (scRNA-seq) of the human hematopoietic stem cell compartment (CD34+CD38-CD45RA-)

  To identify a trajectory of human hematopoietic stem cell (HSC) activation single cell gene expression profiling of RNA from human HSC was performed by flow cytometry-based single cell deposition of CD34+CD38—CD45RA—cells from G-CSF-mobilized peripheral blood from 3 individual donors and 1 bone marrow donor in concert with single cell index-sorting (signals indexed: CD34, CD38, CD45RA, CD90, CD49f) and followed by SMARTseq2 based protocol. We show that INKA1 and CDK6/PAK4 expressing single cells segregate across alternative states of quiescence.

  Study EGAS00001004769

• A Phase II Study: CRS207/GVAX Plus Anti-PD1 and Anti-CTLA4 Recruits Mesothelin- and KRAS-Specific T cells into PDAC

  This study examined immunologic correlatives from a phase II study evaluating CRS207/GVAX vaccines in combination with anti-PD1 and anti-CTLA4 in metastatic pancreatic cancer (NCT03190265). Arm A received CRS207/GVAX with anti-PD1 and anti-CTLA4 therapy; Arm B received CRS207 with anti-PD1 and anti-CTLA4 therapy. Patients undergoing treatment in this trial had peripheral blood mononuclear cells (PBMCs) and tumor tissue biopsied serially at pre-treatment and on-treatment timepoints. Single-cell RNA/TCR sequencing was employed on PBMCs. Bulk RNA/TCR sequencing was employed on tumor tissues. We identified treatment-enriched inflammatory pathways as well as T cell repertoires.

  Study phs003798

• Center for Common Disease Genomics [CCDG] - Cardiovascular: Pharmacokinetic Polymorphisms in Japanese General Population

  This study is a part of NHGRI's Center for Common Disease Genomics, which is a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes. Current estimates anticipate that the CCDG program will sequence approximately 140K whole genomes and 225K whole exomes during the life of the project. The Cardiovascular Disease working group of the CCDG considered five diseases: early-onset coronary artery disease (EOCAD), stroke, atrial fibrillation, congestive heart failure and type 2 diabetes. Atrial fibrillation will affect between 6-12 million individuals in the US by 2050. AF also is associated with increased risks of stroke, dementia, heart failure, death, and high health care costs. Many risk factors for AF have been identified, including advancing age, cardiovascular disease (CVD), and CVD risk factors. However, there is little knowledge how to prevent AF. Furthermore, therapies for AF are only partially effective, and are themselves associated with substantial morbidity. Previously, heritable forms of AF have been considered rare; yet in the last decade, it has been established that AF, and in particular early-onset forms of AF, are heritable. Genome-wide association studies (GWAS) provide a powerful tool to identify common variants underlying disease risk. The AFGen Consortium currently consists of investigators from more than 25 studies with >20,000 individuals with AF and >100,000 without AF. In the latest analyses, 14 loci have been identified for AF1 . Broadly, the loci implicate genes related to cardiopulmonary development, cardiac-expressed ion channels, and cell signaling molecules.Source: https://ccdg.rutgers.edu/sites/default/files/CCDG_CVD_EOAF_FINAL_w_link.pdfAnalysis of 165 pharmacokinetic-related gene polymorphisms (the number of polymorphisms may increase) using DNA derived from the blood of approximately 1,000 Japanese general populations. Tokai University School of Medicine Molecular Life Sciences 2 Isogo Lab has been trying to find new genes which contribute to the development of multiple diseases and to develop new methods for human genome diversity analysis that will lead to the development of technology for disease screening by finding genes related to diseases and incorporating gene analysis technology. Using this method, we are trying to clarify the relationship between the characteristics of rheumatoid arthritis and psoriasis vulgaris and genes to seek effective treatments and prevention methods. Raw sequencing data, metadata, vcf and phenotype data at individual level are available at https://anvilproject.org/data. For questions about availability contact help@lists.anvilproject.org.

  Study phs002985

• ESR1 mutations in tamoxifen-associated endometrial cancer versus spontaneous arisen endometrial tumors

  An increased incidence of endometrial cancer has been described for patients that have received tamoxifen to treat breast cancer. Using samples from endometrial tumors, isolated from surgivcal specimens of patients who previously received tamoxifen treatment for breast cancer, we aimed to identify whether there are specific somatic mutations enriched in this population, relative to endometrial tumors from the general population. For this, WES was performed on matched endometrial tumors and healthy tissue (n=21).

  Dataset EGAD00001009088

• FinHer Breast Cancer Study

  The purpose of this study is to sequence 500 known cancer genes in 960 newly diagnosed high risk breast cancer patients treated with current standard of care therapies and trastuzumab, for somatic alteration and copy number changes. We will be using next gen sequencing technology to determine the prognostic relevance of these somatic genetic alterations and of teh low frequency events to determine if they are associated with trastuzumab benefit or HER2 positive breast cancer, i.e. treatment interaction. The samples will be analysed adn correlated with clinical variables including outcome.

  Dataset EGAD00001000871

• Small RNA Contents of Extracellular Vesicles from Patients with Cognitive Decline

  In this proposal, we examined samples from living neurologically normal individuals (n=72), cognitively normal Parkinson's disease (PD; n=21), PD with mild cognitive impairment (PD-MCI; n=18), PD with dementia (PDD; n=23), and dementia with Lewy-bodies (DLB; n=18), Alzheimer’s disease (AD; n=33) and mild cognitive impairment (MCI, n=38). The main goal for this study was to assess the diagnostic utility of small RNA contents from extracellular vesicles (EVs) for the prediction of cognitive decline. Plasma samples were collected and the RNA from extracellular vesicles (EVs) was isolated using the Qiagen exoRNeasy kit, and the small RNA contents were sequenced using the PerkinElmer NextFlex kit (v2). While PD is typically thought of as a motor disorder, there are significant non-motor symptoms that can be devastating. One of the most common non-motor symptoms of PD is dementia (PDD). While PD subjects that develop dementia all have Lewy bodies, there is often co-pathology with tau and β-amyloid found at autopsy or by PET amyloid imaging; thus, subjects diagnosed with AD were also included in the study. The development of the category, mild cognitive impairment (MCI) in AD, and in PD, provides an opportunity to identify and examine a transitional state between normal aging and dementia; this is a patient population ideally suited for therapeutic intervention. Progress in the detection, validation, and standardization of molecular biomarkers from biofluids, such as extracellular RNAs (exRNAs), would be efficient and cost-effective aids in the assessment of disease progression, cognitive decline, and response to therapeutics. We have provided the raw fastq files for the sequencing data from each sample. We are also providing demographic information, as complete as we have for each person; including age, diagnosis, sex, and cognitive assessments.

  Study phs003300

• RNA Sequencing of Colorectal Liver Metastases

  A subset of patients with metastatic colorectal cancer achieves prolonged survival after hepatic resection of limited liver metastases. Here, we examined the molecular features of colorectal liver metastases as they relate to clinical outcomes.

  Study EGAS00001002945

• Infiltrative and drug-resistant slow-cycling cells support metabolic heterogeneity in glioblastoma

  Glioblastoma patient derived Fast/Slow cycling cancer stem cell RNA sequencing. Consists of 3 patient cell lines and 6 files

  Dataset EGAD00001004380

• Field_effect_of_healthy_and_diseased_livers_WGS

  Recent work in the Campbell group has revealed somatic mutations present in normal, non-cancerous human skin. A subset of the mutations conferred selective advantages to the host cells, leading to clonal expansions and raising the risk for future cancer development. Capturing such somatic mutations in normal tissue is important to advance our understanding about carcinogenesis and could provide prospective medical insights. In this project, our goal is to detect somatic mutations in normal (pre-cancerous) liver tissue. Using Laser Microdissection technology, we will dissect individual liver lobules from patient samples and submit these to sequencing. For each patient sample, we aim to sequence multiple lobules to characterise the mutagenic burden. Samples will be taken from patients with different liver disease aetiologies, including alcoholism and obesity, with a view on distinguishing the prevalent mutation types occurring in each disease context. We will perform both whole genome and targeted sequencing, initially using the WTSI cancer panel. Later we aim to use a novel bait set that captures both cancer genes as well as genes relevant to the non-cancerous samples (ie. genes implicated in hereditary disorders, immune sequences).

  Study EGAS00001002413