16624 results for "sec+and+unspecified+malignant+neoplasm"

in 50.89 milliseconds.

• BIONi010-A / SAMEA3105765 WGS data

  The iPSC line BIONi010-A / SAMEA3105765 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001054

• Next Generation Mendelian Genetics: Familial Hemophagocytic Lymphohistiocytosis

  The NHGRI Next Generation Mendelian Genetics project uses exome resequencing to identify variants in unsolved Mendelian diseases. Familial hemophagocytic lymphohistiocytosis (fHLH) is a serious immune disorder that results from defective cytotoxic lymphocyte function. Autosomal recessive mutations in PFP1, UNC13D, STX11, STBP2, or RAB27, and hemizygous mutations in SH2D1A or BIRC4, account for known causes of the disease, but 30-70% of patients in North America lack a known genetic etiology. This project was designed to identify additional genetic abnormalities from HLH patients. The exome sequences of four unrelated individuals with a diagnosis of HLH, but without mutations in genes known to cause disease, were obtained by massively parallel DNA sequencing.

  Study phs000537

• Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Severe Asthma Research Program (SARP)

  Cohort Description The Severe Asthma Research Program (SARP) has been investigating the clinical, physiologic and molecular phenotypes of asthma since 2000. It is currently following ~400 deeply phenotyped asthma patients. Data Being Submitted Wave 1 questionnaire data includes 397 variables for up to 375 SARP participants in C4R.Wave 2 questionnaire data includes 448 variables for up to 289 SARP participants in C4R.Dried Blood Spot/Serosurvey data includes 7 variables for up to 290 SARP participants in C4R.Derived data includes 43 variables for up to 463 SARP participants in C4R.Phenotype data includes 113 variables for up to 463 SARP participants in C4R.

  Study phs002913

• Radiation-Related Genomic Profile of Papillary Thyroid Cancer after the Chernobyl Accident

  The April 26, 1986 accident at the Chernobyl nuclear power plant in northern Ukraine resulted in the release of radioactive contaminants, which were deposited in the surrounding areas in Ukraine, Belarus, and Russia. The main radiation-related health effect resulting from these exposures is the increased occurrence of thyroid cancer among individuals who were children at the time of the accident or born shortly thereafter. The purpose of this study was to conduct a comprehensive genomic landscape analysis of papillary thyroid tumors arising in individuals who were exposed as children to radioactive iodine (I-131) from the Chernobyl nuclear power plant accident.

  Study phs001134

• Development of molecular targeted therapy for small cell lung cancer by comprehensive genome analysis

  Aims: Identifying new therapeutic targets of small cell lung cancer (SCLC), genome-wide mutation analysis has been performed. Methods: Genomic DNA was extracted from formalin-fixed or methanol-fixed tissue samples. 71 Mb of DNA fragments containing whole coding exons were concentrated using SureSelect Human All Exon V4+UTRs Kit (Agilent Technologies) followed by 100-bp paired end sequencing by HiSeq 2000 (Illumina). Participants/Materials: 51 of 1042 cases of pathologically diagnosed small seen lung cancer that were registered to National Cancer Hospital East Lung Cancer Database in 1992-2012, and which surgically resected or biopsy samples were suitable for DNA extraction for further analyses.

  Study JGAS000037

• Esophageal adenocarcinoma plasma cfDNA samples - PERFECT cohort and nCRT cohort

  The dataset contains 295 plasma cfDNA samples from various stages of resectable esophageal adenocarcinoma from the PERFECT cohort and the nCRT cohort. Shallow WGS was performed on an Illumina Novaseq S4 PE150bp. Samples are provided as raw reads without any prior processing.

  Dataset EGAD00001008316

• Cancer treatment re-shapes the somatic mutational landscape of normal esophagus - 0.25mm punches targeted

  Ageing epithelial tissues, including the esophagus, are progressively colonized by somatic mutant clones, some carrying mutations linked to cancer. However, whether normal epithelial mutational landscapes that evolve over decades can be altered by short term interventions such as cancer treatment is not known. Here we sequenced normal esophageal epithelium removed from patients after 5-8 weeks of therapy for esophageal cancer. Some patients had no prior treatment (NT), while others had 8 weeks of 5 Fluorouracil (5-FU) containing chemotherapy (FLOT) or 4 weeks of chemotherapy and radiation directed at the tumor (CROSS). Despite the brief duration of therapy, we observed treatment specific differences in the selection of mutant clones. The median size of mutant TP53 and PPM1D clones in the CROSS group was double that in the other groups. Mutants of the tumor suppressor SPOP were selected in CROSS but not FLOT or NT patients. In FLOT patients we found positive selection of activating MTOR mutations, consistent with the hypothesis that these mutants confer 5-FU resistance. Sequencing densely mutated normal epithelia after cancer reveals treatment specific selection of mutations with potential therapeutic impact.

  Dataset EGAD00001011182

• Ethiopia Genome Project (high coverage)

  The Ethiopian area stands among the most ancient ones ever occupied by human populations and their ancestors. Particularly, according to archaeological evidences, it is possible to trace back the presence of Hominids up to at least 3 million years ago. Furthermore, the present day human populations show a great cultural, linguistic and historic diversity which makes them essential candidate to investigate a considerable part of the African variability. Following the typing of 300 Ethiopian samples on Illumina Omni 1M (see Human Variability in Ethiopia project, previously approved by the Genotyping committee) we now have a clearer idea on which populations living in the area include the most of the diversity. This project therefore aims to sequence the whole genome of 300 individuals at low (4-8x) depth belonging to the six most representative populations of the Ethiopian area to produce a unique catalogue of variants peculiar of the North East Africa. Furthermore 6 samples (one from each population) will also be sequenced at high (30x) depth to ensure full coverage of the diversity spectrum. The retrieved variants will be of great help in evaluating the demographic dynamics of those populations as well as shedding light on the migrations out of Africa.

  Dataset EGAD00001000696

• Timing the landmark events in the evolution of clear cell renal cell cancer

  Clear cell renal cancer is characterized by near-universal loss of the short arm of chromosome 3 (3p). This event arises through unknown mechanisms, but critically results in the loss of several tumor suppressor genes. We analyzed whole genomes from 95 biopsies across 33 patients with clear cell renal cancer (ccRCC) recruited into the Renal TRACERx study. We find novel hotspots of point mutations in the 5'-UTR of TERT, targeting a MYC-MAX repressor, that result in telomere lengthening. The most common structural abnormality generates simultaneous 3p loss and 5q gain (36% patients), typically through chromothripsis. Using molecular clocks, we estimate this occurs in childhood or adolescence, generally preceding emergence of the most recent common ancestor by years to decades. Similar genomic changes recent common ancestor by years to decades. Similar genomic changes are seen in inherited kidney cancers. Modeling differences in age-incidence between inherited and sporadic cancers suggests that the number of cells with 3p loss capable of initiating sporadic tumors is no more than a few hundred. Targeting essential genes in deleted regions of chromosome 3p could represent a potential preventative strategy for renal cancer.

  Dataset EGAD00001003445

• Ethiopia Genome Project (low coverage)

  The Ethiopian area stands among the most ancient ones ever occupied by human populations and their ancestors. Particularly, according to archaeological evidences, it is possible to trace back the presence of Hominids up to at least 3 million years ago. Furthermore, the present day human populations show a great cultural, linguistic and historic diversity which makes them essential candidate to investigate a considerable part of the African variability. Following the typing of 300 Ethiopian samples on Illumina Omni 1M (see Human Variability in Ethiopia project, previously approved by the Genotyping committee) we now have a clearer idea on which populations living in the area include the most of the diversity.This project therefore aims to sequence the whole genome of 300 individuals at low (4-8x) depth belonging to the six most representative populations of the Ethiopian area to produce a unique catalogue of variants peculiar of the North East Africa. Furthermore 6 samples (one from each population) will also be sequenced at high (30x) depth to ensure full coverage of the diversity spectrum.The retrieved variants will be of great help in evaluating the demographic dynamics of those populations as well as shedding light on the migrations out of Africa.

  Dataset EGAD00001000598

• North American Brain Expression Consortium (NABEC) Exome Sequencing

  A fundamental challenge in the post-genome era is to understand and annotate the consequences of genetic variation, particularly within the context of human tissues. We describe a set of integrated experiments designed to investigate the effects of common genetic variability on mRNA expression distinct human brain regions. We show that brain tissues may be readily distinguished based on expression profile. We find an abundance of genetic cis regulation mRNA expression. We observe that the largest magnitude effects occur across distinct brain regions. We believe these data, which we have made publicly available, will be useful in understanding the biological effects of genetic variation.

  Study EGAS00001002110

• Transcriptome analysis of a novel human iPSC-derived 3D cortical tissue model – 2D versus 3D co-culture comparison

  Single-cell RNA-seq analysis of human iPSC-derived microglia/astrocytes/neurons in a novel, human in vitro 3D cortical tissue model, as well as 2D co-cultures for comparison. Samples include distinct conditions (each as biological triplicates): - wild-type cells from 2D or 3D co-cultures after 3 months of culturing (2D_WT, 3D_WT) - knock-in cells from 2D or 3D co-cultures carrying three familial AD mutations in the APP gene (Swedish, Iberian, Arctic; introduced by CRISPR/Cas9-mediated knock-in) after 3 months of culturing (2D_KI, 3D_KI) - 2D and 3D KI cultures treated with Bumetanide (KI_bum) or BACE IV (KI_bace) inhibitor

  Study EGAS50000001392

• Use_of_Deep_Sequencing_to_Dectect_Clonal_Mutations_In_Sun_Exposed_Skin_Epidermis

  This study aims to define the landscape of somatic mutations in sun exposed human skin by deep sequencing, analyse their frequency and use the data to infer the effect of mutations on proliferating cell behaviour. The frequency of each mutation will reflect the size of the clone of cells in the tissue sample. By analyzing small samples, clones with as few as 100 cells will be detectable. Allele frequency distributions for each mutation will be used to infer cell fate using published methods (Klein et al. 2010). This study will shed unprecedented light on the early clonal events that lead to the emergence of cancer.

  Study EGAS00001000515

• Use_of_Deep_Sequencing_to_Dectect_Clonal_Mutations_In_Sun_Exposed_Skin_Epidermis_PART2

  This study aims to define the landscape of somatic mutations in sun exposed human skin by deep sequencing, analyse their frequency and use the data to infer the effect of mutations on proliferating cell behaviour. The frequency of each mutation will reflect the size of the clone of cells in the tissue sample. By analyzing small samples, clones with as few as 100 cells will be detectable. Allele frequency distributions for each mutation will be used to infer cell fate using published methods (Klein et al. 2010). This study will shed unprecedented light on the early clonal events that lead to the emergence of cancer.

  Study EGAS00001000603

• Targeted_sequencing_of_blood_DNA_from_Human_twins_

  The goals of this study is to investigate the prevalence and heritability of age-related clonal haemopoeisis (ARCH) in healthy elderly individuals.We will use a bespoke bait set to pull down DNA regions of interest in whole blood samples combined with HiSeq at a deep level . By correlating findings from each individual to their respective twin we hope to elucidate whether heritable traits influence the development of ARCH. a. 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/

  Study EGAS00001002210

• Native_American_Ancient_DNA_sequencing

  The morphology of the first humans in the Americas (Paleoamericans) differs from that of Native Americans, and has raised the question of whether or not there are also differences in origin or genetics. A few populations who survived until relatively recently have been suggested to retain Paleoamerican morphology. One of these populations is from La Jolla. Here, we have generated genome sequence data from four La Jolla individuals in order to investigate these questions 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/

  Study EGAS00001001802

• Combination Therapies for Personalised Cancer Medicine in drug resistant EGFR mutant lung cancer

  This study involves mutagenizing a range of different cell lines with ENU to identify those mutations which engender resistance to targeted treatment. In the last decade we have begun to move towards the use of targeted therapeutics in the clinic, often resulting in dramatic response rates in cancer patients. However, clinical experience has demonstrated time and time again that such responses are invariably followed by the development of drug resistance. Identification of the underlying mechanisms may enable us to reverse such resistance. Traditional methods of modelling this resistance in vitro can lead to a plethora of potential resistance mechanisms that can be difficult to decipher.

  Study EGAS00001002509

• Combination Therapies for Personalised Cancer Medicine in 11-18

  This study involves mutagenizing 11-18 with ENU to identify those mutations which engender resistance to targeted treatment. In the last decade we have begun to move towards the use of targeted therapeutics in the clinic, often resulting in dramatic response rates in cancer patients. However, clinical experience has demonstrated time and time again that such responses are invariably followed by the development of drug resistance. Identification of the underlying mechanisms may enable us to reverse such resistance. Traditional methods of modelling this resistance in vitro can lead to a plethora of potential resistance mechanisms that can be difficult to decipher.

  Study EGAS00001002579

• Somatic_mutation_and_clonal_evolution_in_premalignant_lung_disease___WGS

  Cancer is a genetic disease caused by an accumulations of mutations, however many of these mutations have been identified in pathologically normal tissue. We aim to use laser-capture microscopy (LCM) to sample individual clones from the lung tissue of individuals with a variety of lung diseases (COPD, UIP, IPF, Emphysema, pulmonary hypertension). This will allow us to identify whether cancer-associated mutations appear in this normal tissue, assess the mutational burden present, and identify the mutational processes causing these mutations. Smoking is a large risk factor for developing many of these lung diseases so we are particularly keen to determining whether there is evidence of a smoking signature in these patients.

  Study EGAS00001002747

• Overrepresentation of genetic variation in the AnkyrinG interactome is related to a range of neurological disorders

  Upon the discovery of numerous genes involved in the pathogenesis of neurodevelopmental disorders, several studies showed that a significant proportion of these genes converge on common pathways and protein networks. Here, we used a reversed approach, by screening the well-characterized AnkyrinG protein-protein interaction network, implicated in a variety of neurodevelopmental disorders, for genetic variation in a large cohort of 1009 cases with neurodevelopmental disorder. We identified a significant enrichment of de novo potentially disease-causing variants in this network, confirming that this protein network plays an important role in the emergence of several neurodevelopmental disorders.

  Study EGAS00001004326

• Mutational landscape of renal cell carcinoma with venous tumor thrombus

  Renal cell carcinoma with venous tumor thrombus opens the unique opportunity to investigate the clonal evolution of a tumor in two fundamentally different compartments i.e., within the confinement of an organ and inside a large blood vessel. We performed multiregion whole exome sequencing of a total of 37 samples from five consecutive patients (normal tissue, n=5; primary tumors, n=16; tumor thrombi, n=16) to >35-fold target coverage. Four patients had a clear cell RCC, one patient had a poorly differentiated type II papillary RCC (RCC-VTT-04). The latter patient had a friable thrombus, the others were of solid consistency.

  Study EGAS00001001950

• Mutation analysis in human iPS cells

  PCR products were obtained from each target loci using genomic DNA from human iPS cells. Subsequently, PCR products are pooled and subjected to Illumina library preparation. The library will be sequenced by MiSeq. 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/

  Dataset EGAD00001000357

• Comprehensive NGS Profiling to Enable Detection of ALK Gene Rearrangements and MET Amplifications in Non-Small Cell Lung Cancer

  We evaluate the analytical performance of the PGDx™ elio™ tissue complete assay, a 505 gene next-generation sequencing (NGS) tissue-based assay, that has now been FDA-cleared for use by physicians to help guide treatment decisions for cancer patients, using a NSCLC cohort of 38 patients.

  Dataset EGAD50000000016

• Single-cell transcriptomic analyses of peritoneal fluid from patients with colorectal cancer metastasized to the peritoneum

  The data published here contains single-cell RNA-sequencing (scRNAseq) data as obtained using the 3' scRNAseq using Chromium Single Cell 3’ Reagent from 10X Genomics on peritoneal fluid (PF) from patients with colorectal cancer (CRC) and peritoneal metastases (PM). Sequencing was performed in a paired-ended fashion on the NovaSeq6000.

  Dataset EGAD50000000248

• Developmental Maturation of Hematopoietic Stem and Progenitor Cells Mediated by Lin28b/Let-7/Cbx2

  This study encompasses two human cell lines used to profile polycomb repressive complex markers during hematopoietic maturation.  This study includes epigenomic mark sequencing data obtained via the CUT&RUN protocol.

  Study phs002507

• COVID-19 ACTIV-4 ACUTE: A Multicenter, Adaptive, Randomized Controlled Platform Trial of the Safety and Efficacy of Antithrombotic Strategies in Hospitalized Adults with COVID-19 (ACTIV4A)

  This is a randomized, open label, adaptive platform trial to compare the effectiveness of antithrombotic strategies for prevention of adverse outcomes in COVID-19 positive inpatients.

  Study phs002694

• Papua New Guinean Lowlanders dataset

  The Papua New Guinean Lowlanders dataset includes 41 whole genome sequences for Papua New Guinean individuals sampled in Daru. DNA was extracted from saliva samples (Oragen kit). Sequencing libraries were prepared using the TruSeq DNA PCR-Free HT kit. 150 bp paired-end sequencing was performed on the Illumina HiSeq X5 sequencer. The PGAP dataset provides Fastq, mapped cram files (GRCh38) and phenotype measurements.

  Dataset EGAD50000000050

• Genetic subtyping by Whole Exome Sequencing across Diffuse Large B Cell Lymphoma and Plasmablastic Lymphoma.

  Whole exome sequencing was performed from 108 Diffuse Large B Cell Lymphoma cases. A library containing whole exome regions was used to isolate the DNA for sequencing (SureSelect XT Human All Exon V6 (Agilent technologies)). Sequencing on a NovaSeq 6000 instrument (Illumina, paired end, 2x100, mean 566Gb per FlowCell) was performed.

  Dataset EGAD50000000546

• RNA sequencing of baseline HCC PDX models

  To establish the baseline transcriptional profiles, we performed bulk RNA-seq for 36 of our HCC PDX models. 2-6 samples were collected for each model resulting in a total of 68 samples. Isolated RNA was used as input for library preparation using TruSeq RNA Sample Preparation Kit v2 (Illumina). The libraries were multiplexed and sequenced on Illumina HiSeq 2500 (Illumina) to produce FASTQ files.

  Dataset EGAD50000000736

• CASCADE tumour high-coverage whole genome sequencing data

  High coverage whole genome sequencing data (total: 22; median coverage: ~56X; range: 27X – 82X) from fresh frozen postmortem tissues harvested from patients who participated in the CASCADE rapid autopsy program and died of metastatic castration resistant prostate cancer.

  Dataset EGAD00001009491

• 10X 3' V2 data of single immune cells in hepatocellular carcinoma

  The immune microenvironment of hepatocellular carcinoma (HCC) is poorly characterized. Combining two single-cell RNA sequencing technologies, we produced transcriptomes of CD45+ immune cells for HCC patients from five immune-relevant sites: tumor, adjacent liver, hepatic lymph node (LN), blood, and ascites. This is the droplet data of this study

  Dataset EGAD00001005961

• Mate Pair Sequencing data for Molecular Characterization of ETMRs

  This dataset contains Mate Pair Sequencing data from 15 samples from 13 patients. Mate pair DNA library preparation was carried out using the Illumina MP v.2 reagents and protocol. In brief, fragmentation of genomic DNA was performed using a Hydroshear device to an insert size of 4.5 kb followed by sequencing with Illumina HiSeq 2000 instruments resulting in 30 Fastq files (paired end).

  Dataset EGAD00001006207

• Sequence Data for Paper: Epigenetic reprogramming during differentiation of human CD4+ T lymphocytes into memory stages

  Sequence Data of total RNA, miRNA, WGB, mRNA, NOMe, Chip (H3K27ac,H3K27me, H3K36me3, H3K4me1, H3K4me3, H3K9me3, Input) Short Desrciption: Epigenetic profiling of human CD4+ memory T cells reveals their proliferative history and argues in favor of a progressive differentiation model driven by epigenetically controlled master regulators.

  Dataset EGAD00001001865

• Single-cell transcriptome sequencing

  Raw reads from single-cell RNA-sequencing of peripheral blood of five TET2 mutation carriers as well as three non-carrier family members. Single-cells were captured into 10x barcoded gel beads and RNA-sequencing library preparation was done using Chromium Single Cell 3' v2 chemistry (10x Genomics, Pleasanton, CA, USA). Sequencing was performed as recommended with 98bp length of read 2 using HiSeq4000 sequencer.

  Dataset EGAD00001004778

• Genomic data of acute myeloid leukemia cases for integration with metabolomic analyses

  Whole exome sequencing (WES) data of paired (germline and leukemic) samples of 100 adult patients affected by acute myeloid leukemia. Targeted sequencing data of myeloid-related genes of 21 leukemia (not paired) samples from adult patients affected by acute myeloid leukemia.

  Dataset EGAD00001007941

• single cell transcriptome data of gluten-specific T cells

  The data contains paired-end fastq files of 1440 single cells transcriptome sequencing data from 4 Celiac disease patients. CD4+ T cells were sorted by HLA-DQ-gluten tetramers carrying four immunodominant gluten epitopes. All single cell libraries were constructed following SmartSeq2 and sequenced on Illumina NextSeq 500.

  Dataset EGAD00001007975

• RNA sequencing of high-risk paediatric cancers for identifying T-cell infiltration signatures

  Transcriptome profiling of 121 high-risk paediatric cancer samples for identifying T-cell infiltration signatures using poly-A capture by Truseq and sequenced on NextSeq 500

  Dataset EGAD00001010920

• Whole-exome sequencing of P2RY8-CRLF2-positive ALL on Illumina HiSeq 2000, 100 bp paired-end

  Genomic DNA from leukemic and remission bone marrow mononuclear cells was isolated with the QIAamp DNA Blood Extraction Kit (Qiagen, Venlo, The Netherlands). Libraries were prepared using Nextera Rapid Capture Exome Kit (Illumina, San Diego, USA). Paired-end sequencing of 100 bp reads was performed on a HiSeq 2000 (Illumina) to obtain at least a 50 x coverage.

  Dataset EGAD00001002666

• Single cell Human Kidney ADPKD

  This ADPKD project has 3 different experiments, 7 different single cell RNA-seq data, 5 different single nuclei RNA-seq data and 6 different bulk ATAC-seq data objects.

  Dataset EGAD00001009328

• Dataset GBM 2022

  The cellular origin and differentiation status of glioblastoma by scRNA-seq

  Dataset EGAD00001008745

• BCSA_Exome+SmartSeq3

  Multiple regions were cut out of each tumor extracted form breast cancer patients and two experiments were run: - Whole exome sequencing on each of the regions plus an adjacent normal tissue sample - Smart-Seq3 Single cell RNA sequencing on EPCAM+ CD45- sorted cells from different tumor regions

  Dataset EGAD00001009781

• Single-cell RNA sequencing generated from 11 glioma patient samples

  This dataset includes paired-end fastq files from 6 IDH-mutant, 5 IDH-wild-type glioma patient samples of unmatched initial and recurrent timepoints profiled using single-cell RNA sequencing.

  Dataset EGAD00001007772

• Paired-end Whole Exome-seq analysis of multi-centric lower grade glioma

  This dataset includes Nimblegen SeqCap EZ Exome v3 data for each lesion of three patients with multicentric glioma. For two patients, each lesion was sequenced along with whole blood. For a third patient, 3 pieces from the right lesion and 4 pieces from the left were sequenced along with whole blood. In each case BAM files that have been aligned with BWA mem alignment are available.

  Dataset EGAD00001003795

• Failure of Differentiation of the Rhombic Lip Constitutes Medulloblastoma

  We used single-cell transcriptomics to study cells from the developing human cerebellum, and show that different molecular subgroups of medulloblastoma resemble distinct glutamatergic progenitors.

  Dataset EGAD00001008381

• Epigenomic analysis of human dopaminergic neuron differentiation reveals LBX1, NHLH1 and NR2F1/2 as necessary for lineage specification

  Sample information: The 56 samples produced in this project come from the human iPSC line GM17602 (Coriell) where a tyrosine hydroxylase-T2A-mCherry reporter was inserted. A combination of epigenetic analysis (ATAC/ChIP) along transcriptomics.

  Dataset EGAD00001009288

• Paired RNA seq of wild type VDH15 cells (3 replicates) - a cell line of oral squamous cell carcinoma (OSCC)

  Paired RNA seq of wild type VDH15 cells (3 replicates) - a cell line of oral squamous cell carcinoma (OSCC). RNA was extracted and sequencing libraries were prepared using TruSeq Stranded mRNA Library Prep Kit following manufacturer's protocol. The sequencing was done using Illumina Novaseq 6000.

  Dataset EGAD00001010172

• Hodgkin Lymphoma Whole Genome Sequencing

  Whole genome sequencing of 17 paired tumor-normal Hodgkin Lymphoma whole genomes. Bulk tumor (-T) and flow-sorted Reed Sternberg cell (-HRS) samples. Approximately 30x wgs normal depth, 40-50x wgs depth tumor samples.

  Dataset EGAD00001009818

• RNA sequencing of tumor samples from patients with BPLL

  RNA-Seq was performed on 12 samples of sorted CD19+ tumor cells. RNA-Seq libraries were prepared using the SureSelect Automated Strand Specific RNA Library Preparation Kit as per manufacturer’s instructions (Agilent technologies) and subjected to paired-end (2 x 100 bp) sequencing on HiSeq2000 (Illumina). The files are in FASTQ format.

  Dataset EGAD00001004412

• Whole exome analysis of adult type ovarian granulosa cell tumors

  Whole exome data from tumor/normal pairs for adult type ovarian granulosa cell tumor sequencing project. This data set contains 24 tumor whome exomes and 20 matched normal whole exomes generated using the Agilent V4 exome hybrid capture platform, with sequencing performed on an Illumina HiSeq 2000. This dataset contains BAM files generated by aligning paired-end reads to the hg19 reference genome.

  Dataset EGAD00001003961

• Ewing's Sarcoma RNA-Seq

  28 Pretreated Ewing sarcoma tumor blood samples were collected from the Hospital for Sick Children (SickKids) and Mount Sinai Hospital in Toronto, Canada in accordance with each institution’s Research Ethical Board (REB) guidelines. Detailed clinical information (age at presentation, gender, tumor site, stage, etc.) were obtained from the corresponding institutional tumor banks. Transcriptome (RNA-Seq) sequencing was performed using established protocols on Illumina instruments.

  Dataset EGAD00001004188

• RNA expression profiling of melanoma patient-derived xenograft

  Patient-derived xenografts (n=96) were derived from metastatic melanoma patients. RNA expression profiling will be preformed to study 1. HLA-typing and 2. the effect of the tumour microenvironment on tumour growth 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/

  Dataset EGAD00001002230

• Whole exome and whole genome sequencing of juvenile myelomonocytic leukemia (JMML)

  To obtain a complete registry of gene mutations in JMML, whole-exome sequencing was performed for paired tumor-normal DNA from 13 JMML cases, of which 2 cases were also analyzed by whole genome sequencing.

  Study EGAS00001000521

• Ovarian cancer sample size analysis

  The dataset contains exome sequencing fastq from 5 ovarian cancer patients, paired with tumor normal blood samples. Three tumor samples were sequenced from each patient: a biopsy sample ("-1" suffix in the file name), a local sample (multiple regions around the biopsy pooled together, with the "-2" suffix in the file name), and a global sample (multiple regions from the tumor pooled together, with a "-3" suffix in the file name).

  Dataset EGAD00001005947

• Somatic mutations reveal embryonic genetic bottlenecks generating placental mosaicism

  The human placenta harbours chromosomal aberrations that are absent from the fetus in one to two percent of pregnancies. This confined mosaicism suggests that embryonic genetic bottlenecks exist, which phylogenetically segregate placental tissue. Here, we studied the somatic genetic landscape of human placentas by whole genome sequencing of 86 placental biopsies and of 106 microdissections.

  Dataset EGAD00001006337

• Whole Exome Sequencing of High grade T1 non-muscle invasive bladder cancer

  The dataset consists of a multisample VCF (version 4.1) and the corresponding annotated MAF file, containing the somatic point mutations found from exome sequencing across the high-grade T1 bladder cancer cohort (HGT1, n=61 samples). The VCF file is in accordance with the HTS format specifications (https://samtools.github.io/hts-specs/). The dataset comprises also a CSV file with clinical data.

  Dataset EGAD00001006346

• Validated Single-cell RNA sequencing in early breast cancer

  Single-cell RNA and VDJ sequencing of early breast cancer

  Dataset EGAD00001006608

• Metadata Submission

  Metadata Submission Welcome to the EGA Metadata Submission landing page. Here, we provide you with essential resources to facilitate a seamless submission process. Before starting your submission, please make sure you check the following pages: Submission FAQ Submission Quickguide Submission account terms EGA metadata schema If you want to submit sequencing and/or phenotypic data check these pages: Submitter Portal Submitter Portal API If you want to submit array data check these pages: Array documentation Webin Webin API

  Documentation submission/metadata/submission

• Bulk RNASeq of DLL1 positive or negative cells in two different metastatic colorectal cancer organoids under cetuximab treatment

  Standard Poly-A enriched stranded RNASeq libraries were obtained from DLL1 positive and negative subpopulations on two different mestastatic colorectal cancer organoids under cetuximab treatment. Paired sequencing was performed on a NovaSeq 6000 with 100bp reads aiming at 70M clusters. 8 fastq files have been deposited for the 4 samples.

  Dataset EGAD50000002555

• Raw sequencing data from low-input chromosome conformation capture in CD4+ T cells

  This dataset contains raw sequencing data from low-input PCHi-C in human primary CD4+ T cells isolated from healthy donors. The data are released as paired-end Illumina FASTQ files. Promoter Capture Hi-C used DpnII digestion and Tn5-based low-input library preparation, followed by targeted capture with custom-designed biotinylated RNA probes targeting most of the annotated gene promoters.

  Dataset EGAD50000001873

• RNA-seq analysis of TGF-β-induced transcriptional changes in 19TT cancer-associated fibroblasts

  The dataset contains 6 samples, three biological replicates for vehicle-treated 19TT cells, and three biological replicates for TGF-β-treated 19TT cells. The dataset was generated by the next generation high throughput sequencing. Strand specific transcriptome library construction is completed by enriching mRNA from total RNA, sequenced by DNBSEQ high throughput platform.

  Dataset EGAD50000001350

• The dataset for Genome-wide analyses of cell-free DNA for therapeutic monitoring of patients with pancreatic cancer

  The dataset for “Genome-wide analyses of cell-free DNA for therapeutic monitoring of patients with pancreatic cancer” includes 496 cram files from whole genome next-generation sequencing on the Illumina NovaSeq 6000. The samples analyzed include tumor tissue, matched buffy coat and longitudinal plasma samples from individuals with pancreatic cancer.

  Dataset EGAD50000001353

• 10Xchromium 3' RNA-seq of 21 samples from human embryonic heart

  21 samples were taken from human embryonic heart of PCW 5.5-14 of a total of 13 fetuses. Samples were subject to 10Xgenomics chromium single cell 3' sequencing version 2 or 3. Data was analyzed using STARSolo version 2.7.10a, using human genome GRCh38.p12 and transcript annotations from ENSEMBL release 93 from reference package GRCh38-3.0.0 as available from 10Xgenomics.

  Dataset EGAD50000001499

• WES dataset for SJMPAL011911 with different treatments

  This dataset includes whole exome sequencing (WES) data from PDX samples post-drug treatment (N=1 vehicle, N=1 gilteritinib, N=1 venetoclax and N=1 VenGilt). Bam files are provided for each sample. The VenGilt-treated sample underwent whole genome amplification using the Qiagen REPLI-g kit (#150345) prior to sequencing due to the very low cell number.

  Dataset EGAD50000001425

• ATAC-seq for 2 samples

  This dataset contains ATACseq data from ta primary sample and a patient derived model (PDX) of the novel FOXF1/FENDRR ALL subtype. All the 2 samples are in bam file type.

  Dataset EGAD50000001791

• 10x Genomics scRNA-seq for 3 samples

  This dataset contains 10x Genomics single-cell RNA-seq data from two primary leukemia samples and their corresponding patient-derived xenograft (PDX) models. All the 3 samples are in bam file type.

  Dataset EGAD50000001788

• miRNASeq profiles from Indian HFrEF Cohort

  The dataset contains miRNA profiling from a cohort of 49 HFrEF patients. The myocardium samples were collected from these patients during heart transplant of LVAD implantation procedure. The RNA samples were collected in RNAlater. Small RNA libraries were prepared using QIAseq miRNA Library Kit, Qiagen and sequenced on Illumina HiSeq4000.

  Dataset EGAD50000001194

• Long read sequencing to detect structural variants in Indian patient with non-syndromic autism spectrum disorders

  This study involved performing long read whole genome sequencing using Oxford Nanopore Technology platform on to detect causative structural variants in patients with non-syndromic autism spectrum disorder. This study was performed on 23 such children in whom prior karyotyping, Fragile-X analysis (in males), chromosomal microarray and whole exome sequencing did not identify a causative variant.

  Dataset EGAD50000001231

• SIGi001-A-9 / SAMEA4447499 WGS data

  The iPSC line SIGi001-A-9 / SAMEA4447499 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-9 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001095

• SIGi001-A-8 / SAMEA4448777 WGS data

  The iPSC line SIGi001-A-8 / SAMEA4448777 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-8 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001093

• SIGi001-A-5 / SAMEA4448708 WGS data

  The iPSC line SIGi001-A-5 / SAMEA4448708 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-5 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001092

• SIGi001-A-4 / SAMEA4448632 WGS data

  The iPSC line SIGi001-A-4 / SAMEA4448632 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-4 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001088

• SIGi001-A-6 / SAMEA4447426 WGS data

  The iPSC line SIGi001-A-6 / SAMEA4447426 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-6 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001078

• SIGi001-A-2 / SAMEA4451116 WGS data

  The iPSC line SIGi001-A-2 / SAMEA4451116 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-2 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001077

• SIGi001-A-12 / SAMEA104237570 WGS data

  The iPSC line SIGi001-A-12 / SAMEA104237570 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-12 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001076

• SIGi001-A-11 / SAMEA4451118 WGS data

  The iPSC line SIGi001-A-11 / SAMEA4451118 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-11 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001075

• SIGi001-A-10 / SAMEA4451117 WGS data

  The iPSC line SIGi001-A-10 / SAMEA4451117 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-10 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001074

• SIGi001-A-1 / SAMEA4451096 WGS data

  The iPSC line SIGi001-A-1 / SAMEA4451096 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-1 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001073

• BIONi010-C-2 / SAMEA4342705 WGS data

  The iPSC line BIONi010-C-2 / SAMEA4342705 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-2 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001068

• BIONi010-C-5 / SAMEA4452061 WGS data

  The iPSC line BIONi010-C-5 / SAMEA4452061 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-5 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001062

• SIGi001-A-7 / SAMEA4448730 WGS data

  The iPSC line SIGi001-A-7 / SAMEA4448730 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-7 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001060

• BIONi010-C-8 / SAMEA4454011 WGS data

  The iPSC line BIONi010-C-8 / SAMEA4454011 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-8 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001028

• SIGi001-A-13 / SAMEA104386250 WGS data

  The iPSC line SIGi001-A-13 / SAMEA104386250 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-13 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001031

• BIONi010-C-3 / SAMEA4342740 WGS data

  The iPSC line BIONi010-C-3 / SAMEA4342740 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-3 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001034

• BIONi010-C-7 / SAMEA4454010 WGS data

  The iPSC line BIONi010-C-7 / SAMEA4454010 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-7 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001035

• BIONi010-C-6 / SAMEA4454009 WGS data

  The iPSC line BIONi010-C-6 / SAMEA4454009 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-6 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001037

• BIONi010-C-9 / SAMEA4454012 WGS data

  The iPSC line BIONi010-C-9 / SAMEA4454012 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-9 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001040

• SIGi001-A-3 / SAMEA4448571 WGS data

  The iPSC line SIGi001-A-3 / SAMEA4448571 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-3 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001041

• BIONi010-C-4 / SAMEA4452060 WGS data

  The iPSC line BIONi010-C-4 / SAMEA4452060 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-4 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001043

• EDi014-A / SAMEA4459369 WGS data

  The iPSC line EDi014-A / SAMEA4459369 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi014-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001051

• EDi014-B / SAMEA4459371 WGS data

  The iPSC line EDi014-B / SAMEA4459371 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi014-B is available for research use at www.EBiSC.org.

  Dataset EGAD50000001053

• Non-Coding Autoimmune Risk Variant Defines Role for ICOS in T Peripheral Helper Cell Development

  Our fine-mapping of 76 non-MHC loci associated with risk for rheumatoid arthritis (RA, 11,475 cases, 15,870 controls) has recently identified rs117701653, a non-coding single nucleotide polymorphism (SNP) in the CTLA4/CD28/ICOS locus, as the variant most likely to modulate RA risk within this region, with the minor allele C showing disease protection compared to the major allele A. We found that this SNP exhibits allele-specific protein binding and transcriptional modulation, further supporting its regulatory nature. Here, we aimed to determine whether the functional non-coding variant rs117701653 modulates the expression of genes within the CD28/CTLA4/ICOS locus. To address this question, we employed low-input RNA sequencing using the Illumina SmartSeq2 platform on resting total CD4+ T cells from the blood of 24 healthy subjects (8 AA, 8 AC, 8 CC) recruited based on genotype from the Mass General Brigham biobank. We performed a targeted cis-eQTL mapping analysis for protein coding genes with transcription start sites (TSS) within a 1MB window of SNP rs117701653. These genes included WDR12, NBEAL1, CYP20A1, ABI2, RAPH1, CD28, CTLA4, ICOS, and PARD3B. Surprisingly, allelic variation at rs117701653 correlated strongly with expression of ICOS. This suggests that individuals carrying the protective allele C at rs117701653 express lower levels of ICOS, implicating ICOS as a plausible target gene influenced by this protective allele. The raw sequence data from the 24 healthy individuals are available through dbGAP. Gene expression matrices have been deposited to GEO accession GSE235868.

  Study phs003448

• Genetic Modifiers of Duchenne Muscular Dystrophy

  The primary determinant of disease severity in patients with severe Duchenne muscular dystrophy (DMD) or milder Becker muscular dystrophy (BMD) is whether their dystrophin gene (DMD) mutation disrupts the mRNA reading frame or permits the expression of a partially functional protein. However, even in the complete absence of dystrophin, variability in disease severity is observed, with candidate gene studies implicating several genes as potential DMD modifiers. This study undertakes a comprehensive genome-wide search for modifier loci influencing disease severity in DMD patients. The availability of subjects for such studies remains limited, resulting in modest sample sizes that challenge the GWAS design. To address this, we have implemented measures to minimize heterogeneity within the dataset at the dystrophin (DMD) gene itself, adopting a conservative approach to DMD mutation classification to limit the possibility of residual dystrophin expression. Additionally, the study employed statistical methods that are well-suited to smaller sample sizes, including the use of a novel linear regression-like residual for time to ambulatory loss and the application of evidential statistics, specifically the Posterior Probability of Linkage Disequilibrium (PPLD), to assess trait-SNP associations in the GWAS framework. With a sample size of 419 patients, this study has identified multiple candidate genetic modifier loci. The molecular data available in dbGaP includes 2,562,265 directly genotyped variants in 419 people using the Illumina Infinium Omni2.5Exome-8 Beadchip assay, achieving a genotyping rate of 0.998. The phenotypic data comprises age at ambulatory loss, steroid status, DMD gene mutation, and the PPLD value from the time-to-event (TE) phenotype.

  Study phs003680

• Genetic Analysis of Normal Human Facial Variation

  The purpose of this project is to identify genes associated with normal human quantitative facial variation. The motivation for this project stems from the fact that very little is known about how variation in specific genes relates to the diversity of facial forms commonly observed in humans. Viable candidates for these morphogenes originate from a number of sources: tissue expression studies, animal models with targeted or spontaneous mutations, and genetic syndromes with craniofacial manifestations. Importantly, understanding the genetic basis for normal facial variation also has important implications for health-related research. For example, this work has the potential to shed light on the factors influencing liability to common craniofacial anomalies such as orofacial clefts. There is now ample evidence that certain facial features (e.g., increased midfacial retrusion) characterize individuals genetically at-risk for orofacial clefts (e.g., biological relatives of affected cases). While these predisposing facial features are statistically over-represented in at-risk groups, they are also common in the general population. Since many of the current candidate genes for clefting are thought to play a critical role in facial morphogenesis, variation in these genes may also underlie normal variation in these facial features. These candidate genes, however, probably represent only a small fraction of the total number of loci influencing normal human facial variation. Phenotypes for this project were obtained from over 3000 healthy Caucasian subjects recruited through three separate studies. The majority of the subjects were recruited as part of the 3D Facial Norms Project, which is described in extensive detail here: (https://www.facebase.org/facial_norms/notes). The provided dbGaP phenotypes include a series of anthropometric craniofacial measurements (linear distances) primarily derived from 3D photographic facial surface scans (see previous hyperlink). The specific genotyping requested is described elsewhere in this document. Our analysis team is pursuing a variety of different analytic approaches to derive genetically informative phenotypes, including various shape-based morphometric methods. For those interested in pursuing more advanced phenotypic approaches, the original 3D surface scans and additional phenotypic traits are available to researchers through the FaceBase Consortium. This dataset has the potential to facilitate the discovery of new genetic loci with an important role in both normal and abnormal facial development. It may also serve as a dataset to test hypotheses regarding specific SNP associations (e.g. as a replication dataset) or as part of a larger meta-analysis.

  Study phs000949

• Genetics of Human Inherited Retinal Diseases (GHIRD)

  The goal of this project is to identify novel mutations and genes involved in human retinal disorders, a stated priority of the National Eye Institute. To accomplish this, additional genes whose mutations cause inherited retinal diseases (IRD) will be identified by combining targeted gene panel sequencing, whole exome sequencing, and whole genome sequencing. We have collected about 1050 patient families around the world. In this proposal, we will identify the underlying mutations in these patients using a combination of targeted gene panel sequencing, whole exome sequencing, whole genome sequencing, bioinformatics, statistics, and functional studies. Genes targeted for gene panel sequencing are: ABCA4; ASIC2; JAG1; ABCC6; ARL3; ATP1B2; BBS1; BBS2; BBS4; OPN1SW; CAPN5; C21orf2; CA4; CACNA1F; CDH3; CHM; ERCC8; CLCN2; CLCN3; CLCN7; TPP1; CLN3; CLN5; CNGB1; CNGA1; CNGA3; COL2A1; COL9A1; COL11A1; CRX; VCAN; CTSD; TIMM8A; DMD; CLN8; ERCC6; EFEMP1; OPN1MW; GNAT1; GNAT2; GNGT1; GRM6; GUCA1A; GUCA1B; GUCY2F; GUCY2D; HARS; CFH; HK1; IDH3B; IMPDH1; IMPG1; KCNJ13; KIF11; LRP5; MAK; MITF; TRPM1; MTTP; MVK; MYO7A; NDP; NEK2; NEUROD1; NPHP1; NRL; OAT; OPA1; OTX2; PAX2; PAX6; PDCL; PCYT1A; PDE6A; PDE6C; PDE6G; PDE6H; PDE6B; PEX1; PEX6; PEX7; PEX10; PEX12; PEX13; PEX14; PFDN5; PGK1; PHYH; PIN1; PLA2G5; PPT1; PRKCZ; PEX19; PEX2; PEX5; RB1; RBP3; RBP4; OPN1LW; RDH5; PRPH2; RGR; RHO; GRK1; RLBP1; ROM1; RP9; RP1; RP2; RPGR; RPE65; RS1; SAG; ATXN7; CCL2; SLC6A6; ELOVL4; TEAD1; NR2F1; TIMP3; NR2E1; TTPA; TUB; TULP1; UCHL3; USH2A; CLRN1; VLDLR; BEST1; WFS1; ALMS1; MKKS; FZD4; OFD1; PEX3; CTSF; GBF1; ADAM9; RGS9; PEX11B; PROM1; UNC119; PRPF4; PRPF3; AIFM1; SLC24A1; LRAT; ASIC3; RAB28; PEX16; ITM2B; SLC4A7; IQCB1; CROCC; IFT140; DHX38; MFN2; NR2E3; USH1C; TOPORS; MERTK; FBLN5; CIB2; PRPF8; SDCCAG8; IFT27; TREX1; RRAS2; CEP164; ATF6; TRIM32; RIMS1; SNRNP200; CLUAP1; EMC1; ZNF423; TTLL5; AGTPBP1; RPGRIP1L; CRB1; TSPAN12; ARL2BP; AIPL1; PRPF6; FSCN2; ABHD12; PRPF31; TCTN3; IFT172; CNNM4; NPHP3; INVS; BBS9; FLVCR1; RDH8; IMPG2; WDPCP; RDH11; TMEM216; TMEM138; LZTFL1; CNGB3; AHI1; MKS1; CLN6; BBS7; POMGNT1; PEX26; SPATA7; KIZ; KLHL7; INPP5E; MDM1; CABP4; RPGRIP1; MCOLN1; CC2D2A; KIAA1549; SLC7A14; WDR19; NYX; CDH23; SEMA4A; MPP5; NMNAT1; TMEM237; PCDH15; C5orf42; GNPTAB; TMEM231; TCTN1; SRD5A3; BBS10; ZNF408; TTC21B; CSPP1; LPCAT1; DHDDS; PDZD7; PANK2; CEP290; OPA3; DNAJC5; PITPNM3; MFRP; HMCN1; ADGRV1; ARL6; FAM161A; TMEM126A; GNPTG; GJA10; RAX2; TUBGCP6; TMEM67; ACBD5; C12orf65; CDHR1; BBIP1; REEP6; CACNA2D4; RP1L1; CEP41; C1QTNF5; NXNL1; TTC8; USH1G; BBS5; ZNF513; RDH12; SLC38A8; C8orf37; VPS13B; NXNL2; BBS12; ADGRA3; LCA5; KCNV2; ADAMTS18; ARL13B; ATOH7; MFSD8; NPHP4; CCDC66; CYP4V2; CRB2; RD3; LRIT3; EYS; KIF7; CERKL; RGS9BP; C2orf71; GDF6; DTHD1; GPR179; CISD2; CCR2; PRCD; WHRN; ADGRA3. The current dbGaP study release makes available all sequencing-derived vcf data of study participants.

  Study phs001517

• TNBC ctDNA Targeted Panel

  Circulating tumour DNA (ctDNA) detection in liquid biopsy is an emerging alternative to tissue biopsy, but its utility in treatment response monitoring and prognosis in triple negative breast cancer (TNBC) remains to be well understood. In this study, we determined the presence of early stage TNBC ctDNA detectable actionable mutations with a clinically validated hotspot treatment indication panel. Sequencing of plasma DNA from 130 TNBC patients collected within 7 months of primary treatment completion revealed that 7.7% had detectable residual disease with a hotspot panel. Among neoadjuvant treated patients, we observed a trend where patients with incomplete pathologic response and positive ctDNA within 7 months of treatment completion were at risk of reduced progression free survival. We propose that a high risk subset of early TNBC patients treated in NAT protocols may be identifiable by combining tissue response and sensitive ctDNA detection.

  Study EGAS00001006937

• A new beta-globin mutation responsible of a beta-thalassemia (HbVar database ID 2928) was observed in 8 unrelated French families. The mutation carriers originated from Nord-Pas-de-Calais, a Northern French region where the chief town is Lille.5 unrelated mutation carriers were genotyped for a set of 12 microsatellites from chromosome 11, around the beta-globin gene. Among the 5 mutation carriers, 4 were genotyped for 97 European Ancestry Informative SNPs (EAIMs). 32 controls from Nord-Pas-de-Calais were genotyped for the microsatellites and SNPs.

  Dac EGAC00001000245

• SC_DDD-G-3

  Unfiltered genotype data for DDD Study trios (patient and parents) (N=2,166 samples), some of which were used for replication of neurodevelopmental disorder polygenic risk (Niemi et al., Nature 2018). Samples were genotyped on the Illumina HumanOmniExpress BeadChip

  Dataset EGAD00010001602

• FFPE cohort with RNA-seq data of tumor samples

  This dataset contains RNA-seq raw data in fastq format from 14 tumor samples. The samples are from primary tumors or metastasis and represent various cancer entities. The samples are formalin-fixed paraffin-embedded (FFPE) treated. For target enrichment SureSelect XT Human All Exon V6 was used. The libraries were sequenced in paired-end mode (2 x 50 nt) on a NovaSeq6000 S2 flow cell.

  Dataset EGAD00001006781

• Epigenome-wide association study of cocaine use disorder in postmortem human brain tissue

  Analysis of cocaine use disorder (CUD) associated epigenome-wide DNA methylation (DNAm) alterations in human postmortem brain tissue of Brodmann Area 9. Tissue samples from N=21 CUD cases and N=21 individuals without CUD originating from the Douglas Bell Canada Brain Bank (DBCBB) were included. Epigenome-wide DNAm was investigated using the Illumina Infinium MethylationEPIC array.

  Dataset EGAD00010002396

• 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