14977 results for "cancer studies using rna-seq"

in 36.15 milliseconds.

• DNA from colon cancer samples and matched normal samples was hybridized on Human 660W-Quad SNP arrays and sequenced in Illumina HiScanSQ.

  DNA from colon cancer samples and matched normal samples was hybridized on Human 660W-Quad SNP arrays and sequenced in Illumina HiScanSQ. The objective of the study was to introduce methodology for the detection of genomic copy number alterations (CNAs) using high-throughput sequencing data. The samples in this study allow the comparison of the results from the seqCNA R package with those from other methods that detect copy number alterations (CNAs) in tumoural samples, either using SNP-array data or high-throughput sequencing data.

  Study EGAS00001000558

• Enhancing OSCC Prediction: The Prognostic Power of WPOI and Tumor Budding, and the Limited Impact of Molecular Resection Margins

  This dataset contains sequences with results of mutations observed in patients with oral squamous cell carcinoma. Mutations were detected by NGS in tumor tissue, tumor margins, and peripheral blood as a healthy control. Study was using a panel of 88 cancer-related genes, which were selected based on a literature search.

  Study EGAS50000000074

• Variant analysis on FFPE specimen from NSCLC patients (FoundationOne CDx)

  This study assessed the presence of somatic variants via the FoundationOne CDx panel of commonly mutated cancer genes and measure tumor mutational burden using next-generation sequencing panels. It was performed on genomic DNA from FFPE tissue of tumor resections. Mutations were used to draw OncoPrints and to assess TMB in relation with response metrics.

  Study EGAS50000001139

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: pancreas (2019-04-03)

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute (Illumina HiSeqX, 40X and 20X depth respectively). Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development. . This dataset contains all the data available for this study on 2019-04-03.

  Dataset EGAD00001004893

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: Colorectal_LCM (2020-02-20)

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute. Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development. . This dataset contains all the data available for this study on 2020-02-20.

  Dataset EGAD00001005994

• Non-small cell lung cancer targeted sequencing

  Targeted sequencing of non-small cell lung cancer samples. BAM files of paired end reads aligned to hg19 using BWA MEM v0.7.1573. This targeted panel covers 370 genes of clinical relevance in non-small cell lung cancer.

  Dataset EGAD00001007918

• T2D-GENES Project 2: San Antonio Mexican American Family Studies

  The Type 2 Diabetes (T2D) Genetic Exploration by Next-generation sequencing in Ethnic Samples (T2D-GENES) Consortium is a collaborative international effort to identify genes influencing susceptibility to T2D in multiple ethnic groups using next generation sequencing. T2D-GENES Project 2 is a complex pedigree-based study designed to identify low frequency or rare variants influencing susceptibility to T2D, using whole genome sequence (WGS) information from 1,043 individuals in 20 Mexican American T2D-enriched pedigrees from San Antonio, Texas. The major objectives of this study are to identify low frequency or rare variants in and around known common variant signals for T2D, as well as to find novel low frequency or rare variants influencing susceptibility to T2D. The sampled individuals are obtained from two studies: the San Antonio Family Heart Study (SAFHS) and the San Antonio Family Diabetes/Gallbladder Study (SAFDGS), collectively referred to as the San Antonio Mexican American Family Studies (SAMAFS). The strategy is to sequence approximately 600 individuals at an average of 50x coverage across the entire genome, then impute genome wide genotypes for about 440 additional family members. The 600 sequenced individuals are specifically chosen for their value in imputing sequence information into other family members. By studying large pedigrees, we expect to find multiple individuals carrying each genetic variant, even if this variant is very rare in the population at large. Thus, a pedigree-based approach provides an excellent opportunity for identifying rare novel variants influencing risk of T2D and quantitative variation in T2D-related phenotypes. The whole genome sequencing has been done commercially by Complete Genomics, Inc. (CGI). The final data set includes whole genome sequence data for 607 individuals. After quality control, 585 sequenced individuals provide data for family based imputation, using Merlin linkage analysis software, into approximately 440 additional family members for whom chip based genotypes are available to indicate which parental haplotype is transmitted. Extensive phenotype data is provided for 1048 individuals. These include 5 sequenced individuals who do not belong to any of the 20 large pedigrees. Phenotype information was collected between 1991 and 2011 in the two contributing longitudinal studies. SAFHS participants may have information from up to 5 visits, and SAFDGS participants may have up to 4 visits. The clinical variables reported are coordinated with T2D-GENES Project 1 (multi-ethnic exome sequencing) and include T2D status and age at diagnosis, glycemic traits (fasting and 2 hour glucose and insulin), blood pressure, blood lipids (total cholesterol, HDL cholesterol, calculated LDL cholesterol and triglycerides), clinical chemistry (cystatin c, glutamic acid decarboxylase antibody titer (GadAb), creatinine, adiponectin and leptin). Glycated hemoglobin (HbA1c) was not measured for these individuals and insulin C-peptide is not included in this data set. Additional phenotype data include the medication status at each visit, classified in four categories as any current use of diabetes, hypertension or lipid-lowering medications, and, for females, current use of female hormones. Anthropometric measurements include age, sex, height, weight, hip circumference, waist circumference and derived ratios. Each phenotype variable has an initial summary column containing the most recent non-missing measurement for each individual, followed by the five potential time points for each individual, the number of non-missing measurements, and the age and year for the most recent non-missing measurement. For historical reasons, the order in which variables are presented on the dbGaP web site differs from their order in the data download file. When reading the comment fields for each variable, please note that commas are omitted to support data exchange in .csv format.

  Study phs000462

• Whole exome and Transcriptome sequencing of treatment-naïve esophageal adenocarcinoma biopsies and matched peripheral blood mononuclear cells

  Exome sequencing was performed on n=28 treatment-naïve esophageal adenocarcinoma (EACs). Three to four biopsies sampling different areas of each tumor were pooled before nucleic acid extractions to mitigate the elevated heterogeneity described for EAC. WES was performed on EAC biopsies at 120X average coverage, with autologous PBMCs used as germline controls at 80X average coverage. Libraries were prepared from 30 ng of input DNA using the SureSelect QXT Human All Exon V7 kit (Agilent Technologies) and sequenced on the NextSeq 550 (Illumina), 2x150 bp. BCL files were demultiplexed to FastQ files using bcl2fastq2 software (Illumina). Three paired end sequencing batches were analyzed independently (Batch1: samples 8, 10, 11, 12, 15, 17, 18; Batch2: samples 20, 24, 25, 26, 27, 29, 30, 31, 33, 34 ; Batch3: samples 35, 37, 39, 40, 41, 43, 45, 48, 54, 55, 57). RNA sequencing was performed on n=26 treatment-naïve esophageal adenocarcinoma (EACs). Three to four biopsies sampling different areas of each tumor were pooled before nucleic acid extractions to mitigate the elevated heterogeneity described for EAC. RNAseq libraries were prepared on 50 ng of total RNA (with RNA integrity index RIN >=7) with the TruSeq Stranded mRNA library preparation kit (Illumina) in accordance with low-throughput protocol. After PCR enrichment (15 cycles) and purification of adapter-ligated fragments, the concentration and length of DNA fragments were measured using D1000 Screen Tape System (Agilent), obtaining a median insert size of 311 nucleotides. Then, RNAseq libraries were sequenced using the Illumina NovaSeq platform, 1x100 bp, obtaining on average 100 million single reads per sample.

  Dataset EGAD00001010876

• Pseudogene RNAseq

  RNA sequencing to validate findings of somatic pseudogenes acquired during cancer development

  Dataset EGAD00001000732

• Genomic Sequencing of Cervical Cancers

  Cervical cancer is responsible for 10-15% of cancer related deaths in women worldwide. The etiological role of infection with high-risk human papilloma viruses (HPV) in carcinomas of the cervix is well established. In general, the development of cervical carcinomas follows a progression from persistent HPV infection through precancerous lesions to invasive cancer. Previous studies have implicated somatic mutations in PIK3CA, PTEN, TP53, STK11 and KRAS as well as chromosome-arm level copy number alterations in the pathogenesis of cervical carcinomas. Here, we report whole exome sequencing analysis of 118 cervical carcinoma-normal paired samples from patients in Norway and Mexico, as well as transcriptome sequencing of 80 cases and whole genome sequencing of 13 tumor-normal pairs. Novel somatic mutations include recurrent E322K substitutions in the MAPK1 gene encoding the ERK2 kinase and inactivating mutations in the HLA-B gene. In addition, recurrent somatic mutations in FBXW7, EP300, and NFE2L2 are novel in the context of primary cervical carcinomas. Analysis of HPV integration sites revealed recurrent integration into the RAD51B locus as well as co-occurrence of HPV genome integration and copy number gains within several genomic loci. These findings shed new light on the pathogenesis of cervical carcinomas and suggest potential novel therapeutic targets.

  Study phs000600

• Inter and intra - tumor heterogeneity in Colorectal Cancer

  The dataset consists of two main sample groups. 1) The inter-tumour sample group contains a total of 97 samples from 27 patients. Each patient has a single normal and primary sample as well as one or more metastases. All samples were sequenced using IonTorrent PGM and a custom colorectal cancer (CRC) panel. 2) The intra-tumour sample group contains a total of 68 samples from a single tumour as well as a normal tissue sample. All 68 samples were sequenced using IonTorrent PGM and a custom CRC panel. Shallow whole genome sequencing was additionally applied to 10 of the samples using Illumina HiSeq 4000.

  Dataset EGAD00001003131

• Sequencing_of_patient_samples_who_received_immune_checkpoint_inhibition___WES___NKI

  DNA and RNA isolated from FFPE blocks of patients who received immune checkpoint inhibition (ICI) are sequenced with the aim to identify therapeutically tractable vulnerabilities in tumors to prevent ICI resistance.

  Study EGAS00001003154

• Total RNA sequencing data from the Triple Negative Trial (TNT)

  BAM files from total RNA sequencing of samples from breast cancer patients in the TNT trial. Data includes 186 primary tumour samples and 13 matched recurrence samples.

  Dataset EGAD00001011141

• Deciphering Maternal-Fetal Crosstalk in the Human Placenta During Parturition Using Single-Cell RNA-Sequencing

  Labor is a complex physiological process requiring a well-orchestrated dialogue between the mother and fetus. However, the cellular contributions and communications that facilitate maternal-fetal crosstalk in labor have not been fully elucidated. In this latest version (#5), scRNA-seq was applied to decipher maternal-fetal signaling in the human placenta and chorioamniotic membranes during term labor. Samples were obtained from women who underwent spontaneous labor (n = 24) or who were delivered in the absence of spontaneous labor (n = 18) at term. Samples from previous versions (#1-3) of this study include the placental villous tree, basal plate, and chorioamniotic membranes of women across a range of pregnancy physiologic and pathologic conditions, including the processes of labor (term labor and preterm labor), and COVID-19 (version #3). Version #4 includes samples from the human myometrium during spontaneous term labor.

  Study phs001886

• Integrated Analysis of Multimodal Single-Cell Data

  The simultaneous measurement of multiple modalities, known as multimodal analysis, represents an exciting frontier for single cell genomics and necessitates new computational methods that can define cellular states based on multiple data types. Here, we introduce 'weighted nearest neighbor' analysis, an unsupervised framework to learn the relative utility of each data type in each cell, enabling an integrative analysis of multiple modalities. We apply our procedure to a CITE-seq dataset of hundreds of thousands of human white blood cells alongside a panel of 228 antibodies to construct a multimodal reference atlas of the circulating immune system. We demonstrate that integrative analysis substantially improves our ability to resolve cell states and validate the presence of previously unreported lymphoid subpopulations. Moreover, we demonstrate how to leverage this reference to rapidly map new datasets, and to interpret immune responses to vaccination and COVID-19. Our approach represents a broadly applicable strategy to analyze single-cell multimodal datasets, including paired measurements of RNA and chromatin state, and to look beyond the transcriptome towards a unified and multimodal definition of cellular identity. All CITE-seq and ECCITE-seq raw matrices are available in GEO database under the accession number GEO: GSE164378.

  Study phs002315

• Deep single-cell RNA sequencing data for 11138 T cells from tumour, adjacent normal tissue and peripheral blood of treatment-naive CRC patients. The DATA ACCESS AGREEMENT is provided at https://github.com/zhangyybio/single-T-cell-data-access. Applicants can request access to the data by directly downloading it or by sending an email to cancerpku@pku.edu.cn. The process that is used to approve an application includes verifying the institution, participants and research purposes of the application. In general this process will take about two weeks. In principal, any scientific research program complying with the laws and bioethic regulation policies of China will be approved.

  T cells are central players in cancer immunotherapy1, yet some of their fundamental properties such as development and migration within tumours remain elusive. The enormous T cell receptor (TCR) repertoire, required for recognising foreign and self-antigens2,3, could serve as lineage tags to track these T cells in tumours4. Here, we obtained transcriptomes of 11,138 single T cells from 12 colorectal cancer (CRC) patients and developed STARTRAC (Single T-cell Analysis by Rna-seq and Tcr TRACking) indices to quantitatively analyse dynamic relationships among 20 identified T cell subsets with distinct functions and clonalities. While both CD8+ effector and “exhausted” T cells exhibited high clonal expansion, they were independently connected with tumour-resident CD8+ effector memory cells, implicating a TCR-based fate decision. Of the CD4+ T cells, the majority of tumour-infiltrating Tregs showed clonal exclusivity, whereas certain Treg clones were developmentally linked to multiple TH clones. Notably, we identified two IFNG+ TH1-like clusters in tumours, the GZMK+ TEM and CXCL13+ TH1-like clusters, which were associated with distinct IFN-γ-regulating transcription factors, EOMES/RUNX3 and BHLHE40, respectively. Only CXCL13+BHLHE40+ TH1-like cells were preferentially enriched in tumours of microsatellite-instable (MSI) patients, which might explain their favourable response rates to immune-checkpoint blockade. Furthermore, we found IGFLR1 to be highly expressed in both CXCL13+BHLHE40+ TH1-like and CD8+ exhausted T cells and possessed co-stimulatory functions. Our integrated STARTRAC analyses provides a powerful avenue to comprehensively dissect the T cell properties in CRC, which could shed new insights into the dynamic relationships of T cells in other cancers

  Study EGAS00001002791

• Cord blood progenitor CITE-seq dataset

  Sequencing results of single-cell transcriptome and antibody libraries from two biological experiments of cord blood progenitor cells. Four samples from different time points were processed using 10X Genomics Chromium Next GEM Single Cell 3’ Reagent Kits v3.1. Gene expression and antibody-derived libraries were sequenced separately.

  Dataset EGAD50000000405

• Transcriptomics sequencing 4 samples from the same KMT2A-rearranged Acute Lymphoblastic Leukemia patient

  Dataset contains four samples taken from a neonate with congenital KMT2A-rearranged Acute Lymphoblastic Leukemia patient (CHI-0391) with rare IKZF1 gene fusions. Sequencing was carried out using mRNA-seq sequencing on a Illumina NextSeq 500 machine

  Dataset EGAD00001009974

• A Single-cell Atlas of Progressive TKI Resistance in Chronic Myeloid Leukemia

  57 Bone marrow specimens for 5 healthy bone marrow and 24 CML samples profiled with 10X scRNA-seq 5' upon separation using MACS for CD34.

  Dataset EGAD00001007946

• Unraveling the transcriptomic profile of utero-tubal lavage fluid of ovarian cancer patients

  mRNA capture seq of uterotubal lavage samples

  Dataset EGAD00001007933

• HGSOC-celllines-SmartSeq3

  Smart-seq3 scRNA-seq of cells from primary (OV2295) and metastatic (OV2295R2) high-grade serous ovarian cancer cell-line

  Dataset EGAD00001009798

• Nivolumab and Ipilimumab and Radiation Therapy in Microsatellite Stable (MSS) and Microsatellite Instable (MSI) High Colorectal and Pancreatic Cancer

  This is a single-arm, non-randomized, phase 2 trial (NCT03104439) combining radiation, ipilimumab and nivolumab in patients with metastatic MSS Colorectal Cancer (CRC; n=40) and Pancreatic Ductal Adenocarcinoma Cancer (PDAC; n=25). Patients were previously treated population, and the primary endpoint was disease control rate. Pre- and post-treatment samples were subjected to RNA sequencing and whole exome sequencing. The primary data is shared via GEO and dbGaP at National Center for Biotechnology Information (NCBI), National Institutes of Health (NIH).

  Study phs002545

• Arcagen - Extra-pulmonary neuroendocrine tumour or cancer grade 3 (NET / NEC G3) domain

  Arcagen is an EORTC/SPECTA pan-European project that aims to recruit 1000 rare cancer patients from different tumour domains of EURACAN. This study collected samples from advanced or metastatic rare cancer from patients older than 12, and analysed them using Foundation Medicine next-generation sequencing (NGS) panels (FoundationOne CDx for FFPE samples or FoundationOne Liquid CDx for blood samples). Here were are submitting the dataset that contains NGS files from patients with extra-pulmonary neuroendocrine tumour or cancer grade 3 (NET / NEC G3) (n=85).

  Study EGAS50000000644

• 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.

  Study EGAS00001000648

• WES in Angolan and Cape Verdean triple-negative breast cancer samples

  WES (using the SureSelect Human All Exon V5 + UTRs target enrichment kit) in 23 Angolan and 7 Cape Verdean triple-negative breast cancer samples

  Dataset EGAD50000001482

• Spatial transcriptomics of 1 untreated prostate cancer.

  Two sections of cryopreserved prostate cancer tissue from one untreated prostate cancer patient were profiled for spatial transcriptomics using the Visium Spatial library preparation protocol from 10x Genomics. The GRCh38 aligned sequencing reads from the two prostate cancer tissue sections are provided as BAM files.

  Dataset EGAD00001007921

• Tracking early lung cancer metastatic dissemination in TRACERx using ctDNA

  These data relate to Abbosh et al 2023 'Tracking early lung cancer metastatic dissemination in TRACERx using ctDNA'. Some patients were included in this work that were excluded from the other TRACERx 421 papers (Frankell et al and Al-bakir et al) often due to exclusion criteria in the TRACERx clinical trial. Reasons include partial contamination with C>A artefact mutational signature (CRUK0480 ,0490) which were included for ctDNA detection analyses using high confidence clonal mutations but not clonality analyses, incomplete resection at primary surgery (CRUK0291, 0234, 0230, 0387, 0622) and a concurrent oesophageal second primary cancer (CRUK0498). The primary tissue exome sequencing for these patients that were used in this study are included in this repository. Deep targeted sequencing of (median 200) tumour specific mutations in plasma for 1069 samples from 198 TRACERx patients are also included. Additional details related to these patients and samples can be found in the supplementary or data repositories from Frankell et al and Abbosh et al.

  Study EGAS00001006923

• Wilm's tumor sequencing data

  No. of samples: 80 (28 ULP-WGS, 26 WES, 26 RNA-SEQ) File types: FASTQ (28 ULP-WGS, 19 WES, 18 RNA) and BAM (7 WES, 8 RNA) Technology used: Sequencing - Illumina Novoseq 6000; Map/Align - Illumina DRAGEN v3.7.5; Genome assembly - GrCh38p13 Filename nomenclature: - SampleName_Passage_SampleType_TissueType_SequencingType - Passage of: PX = unknown; PZ = from patient; P0 = first passage from patient on plastic; P1 = first passage from plastic/PDX/organoid - SampleType: STN = normal; STT = tumor - SampleType STN: 00 = tissue unknown; 01 = adjacent normal; 02 = fibroblast; 03 = germline blood; 21 = cell line from patient tissue; 22 = cell line from PDX; 23 = cell line from patient fibroblast - SampleType STT: 00 = tissue unknown; 01 = primary tumor; 21 = cell line from patient; 22 = cell line from PDX - TissueType: WT = Wilm's tumor; 00 = kidney unknown; 01 = kidney left; 02 = kidney right - SequencingType: 00 = unknown; 02 = ultra-low pass whole-genome sequencing; 20 = whole-exome; 61 = bulk RNA-sequencing

  Dataset EGAD00001011111

• Dataset for hepatopancreaticobiliary_malignancy-WHOLE_GENOME

  Rare cancer sequencing data of 83 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008884

• Dataset for neuroendocrine_adrenal_tumor-WHOLE_GENOME

  Rare cancer sequencing data of 112 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008893

• RNAseq_of_ribosomal_footprints

  Cancer genes can affect ribosomal RNA processing and this can underlie their essentiality to cells, making them cell-essential in the same way as ribosomal genes themselves. We want to confirm this, in order to understand the results of our CRISPR drop-out screens.NOTE FROM BESPOKE TEAM: Run a single read 1 (forward read) of 30 bases, then an index 1 read as normal. This would fit a 50cycle kit

  Study EGAS00001001591

• Genome_Diversity_in_Africa_Project__Uganda

  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

  Study EGAS00001002523

• Transcriptomic data in 46,XX, 46,XY, 47,XXY, 47,XYY individuals

  This dataset contains paired-end (151x2) RNA sequencing data (fastq files) from 25 human blood samples, some with sex chromosome aneuploidies. Data were generated using Illumina technology (Novaseq 6000) and a median of approximately 174 million pairs of reads per sample were obtained using two sequencing batchs. Samples come from: six 46,XX individuals, six 46,XY individuals, nine 47,XXY individuals, and four 47,XYY individuals.

  Dataset EGAD00001011202

• Genomic analysis of HGSOC using long read sequencing

  High-grade serous ovarian cancer (HGSOC) is characterized by widespread genomic instability, but genomic and epigenomic alterations within repetitive regions remain poorly understood. This study aims to investigate genomic and epigenomic variations in HGSOC using Oxford Nanopore long-read sequencing technology. High-molecular-weight DNA was extracted from cryopreserved, pre-treatment tumor samples and matched blood specimens. The objectives include developing a robust long-read sequencing analysis pipeline, identifying novel genomic and epigenomic variations, and exploring potential applications in future clinical and basic research.

  Study EGAS50000001036

• Methylome sequencing of cell-free DNA and RRBS of solid tissue

  Early cancer detection by cell-free DNA (cfDNA) faces multiple challenges: low fraction of tumor cfDNA, molecular heterogeneity of cancer, and sample sizes not sufficient to reflect diverse patient population. We develop a cancer detection approach to address these challenges. It consists of an assay, cfMethyl-Seq, for cost-effective sequencing of cfDNA methylome (with >12-fold enrichment over whole genome bisulfite sequencing in CpG islands), and a computational method to extract methylation information and diagnose patients. Applying our system to 408 colon, liver, lung, and stomach cancer patients and controls, at 97.9% specificity we achieve 80.7% and 74.5% sensitivity in detecting all-stage and early-stage cancer, and 89.1% and 85.0% accuracy for locating tissue-of-origin of all-stage and early-stage cancer, respectively. Our approach cost-effectively retains methylome profiles of cancer abnormalities, thereby permitting the classification models to learn new features as training cohorts grow, and expanding their scope to other cancer types.

  Study EGAS00001006020

• The Human Virome in Children and its Relationship to Febrile Illness

  Definition of the human microbiome is an important scientific priority. This study will expand the scope of the investigation to include viruses, which account for a substantial proportion of infectious disease morbidity and mortality, especially in children. The long-term goal of this project is to describe the human virome in children and to investigate its relevance to febrile illnesses in children. The project will also seek to understand the relationship of the immune system to the composition of the virome. Thus, the project's specific aims are 1) To elucidate the spectrum of viruses that can be detected using non-biased, high throughput sequencing on samples of blood, respiratory, and gastrointestinal secretions from healthy children and to use this information as a basis for understanding the role of viruses in acute febrile illnesses without an obvious source, and 2) to investigate the effect of various forms of immunosuppression on the spectrum of viruses detected in children, and to use this information as a basis for understanding the role of viruses in acute febrile illnesses occurring in these children. Our preliminary studies show that diverse viruses can be detected in children having undiagnosed fever. To carry out the specific aims, well children will be enrolled prior to having elective surgery, and febrile otherwise well children will be enrolled from the Emergency Department at St. Louis Children's Hospital. Immunocompromised children will be recruited from hematopoietic stem cell and solid organ transplant clinics, the HIV/AIDS clinic, and the rheumatology/immunology clinic from the same hospital. Children with fever will have samples obtained at the time of the febrile illness and at 1 and 6-month follow-up visits. Selected samples from each study group will be analyzed at the Genome Center at Washington University (GCWU) using next generation 454 high throughput sequencing to detect and sequence all viral sequences present. We anticipate detecting and sequencing a broad range of viruses, including previously unrecognized agents. A variety of techniques will be used to investigate the significance of viruses detected. Virus-specific PCR assays will be used to determine the frequency and extent of viruses detected by sequencing, using the full range of samples collected. Host response to the detected viruses will be investigated using serologic analysis, cytokine profiling, and microarrays to characterize host gene expression. These studies will take advantage of follow-up samples to compare the acute response with the response in the convalescent period. This study will draw upon the expertise and technological assets of one of the world's most powerful sequencing centers to provide the research community with a comprehensive sequence data base of the viruses that are present in children, which can be used to improve our understanding of the causes of febrile illnesses in young children, many of which are currently undiagnosed.

  Study phs000264

• Genomic Analysis of Metastatic Brain Cancer

  This study contains targeted exome and transcriptome sequencing of metastatic brain tumors from 68 patients. Sequencing data includes i) targeted Tempus xT exome sequencing from matched tumor/normal from 68 patients, and ii) whole-transcriptome RNA sequencing from a subset of 65 patients.

  Study phs002639

• Mechanisms of Restoring T Cell Immunity after Cure of Chronic Viral Infection

  We analyzed hepatitis C virus (HCV)-specific T cells and non-specific memory T cell populations from 6 patients with chronic HCV infection receiving 12 weeks of direct-acting antiviral (DAA) therapy with aritaprevir/ritonavir/ombitasvir + dasabuvir + ribavirin. All patients were treated successfully. Peripheral blood mononuclear cells were obtained from blood draws right before treatment initiation (Pre-DAA) and 12 months after the end of treatment (Post-DAA). In each patient, HCV-specific cells were sorted using two different HCV multimers: One representing an epitope present in the circulating HCV genome and one epitope where the virus had escaped the T cell response and thus the corresponding T cells did not receive a TCR signal in vivo. Sorted specific T-cell populations and memory T cell subpopulations were analyzed by extracting RNA and performing RNA sequencing using the Smart-Seq2 protocol. A group of 8 patients with acute self-limited HCV infection (resolvers) were included as control representing natural control of infection. These patients were studied 24 weeks after their last detectable HCV viremia. Finally, we confirmed the data from chronically treated patients in a confirmatory cohort, consisting of 9 patients after successful antiviral treatment.

  Study phs002510

• PATL2 is a key actor of oocyte maturation whose invalidation causes infertility in women and mice

  The genetic causes of oocyte meiotic deficiency (OMD), a form of primary infertility characterised by the production of immature oocytes, remain largely unexplored. Using whole exome sequencing, we found that 26% of a cohort of 23 subjects with OMD harboured the same homozygous nonsense pathogenic mutation in PATL2, a gene encoding a putative RNA-binding protein. Using Patl2 knockout mice, we confirmed that PATL2 deficiency disturbs oocyte maturation, since oocytes and zygotes exhibit morphological and developmental defects respectively. PATL2's amphibian orthologue is involved in the regulation of oocyte mRNA as a partner of CPEB. However, Patl2's expression profile throughout oocyte development in mice, alongside colocalisation experiments with Cpeb1, Msy2 and Ddx6 (three oocyte RNA-regulators) suggest an original role for Patl2 in Mammals. Accordingly, transcriptomic analysis of oocytes from WT and Patl2-/- animals demonstrated that in the absence of Patl2, expression levels of a select number of highly relevant genes involved in oocyte maturation and early embryonic development are deregulated. In conclusion, PATL2 is a novel actor of mammalian oocyte maturation whose invalidation causes OMD in humans.

  Study EGAS00001002903

• 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.

  Study EGAS00001000301

• Cold Ischemia Study

  This study aimed to evaluate the impact of cold ischemia time on the expression of cancer-related genes, particularly those involved in hypoxia, apoptosis, and epithelial-to-mesenchymal transition (EMT). We performed RNA sequencing on 54 normal colon mucosa samples from nine patients undergoing colorectal cancer surgeries, freezing samples at predefined intervals ranging from 0 to 60 minutes. A total of 44 differentially expressed genes (DEGs) (p < 0.05) were identified when comparing samples frozen immediately (T0) with those frozen after 60 minutes (T5).

  Study EGAS00001008233

• Genome Wide Association Study of Chronic TMD: Discovery Phase

  The OPPERA project is investigating effects of genetic, physiological, psychological and clinical factors on the risk of developing painful temporomandibular disorder (TMD). This case-control study is a discovery-phase genome wide association study that aims to identify commonly-occurring genetic variants associated with chronic TMD. It represents the first step in a series of studies that seek to identify the genetic background of TMD. For related phenotype and targeted genotype data, please see additional studies from the OPPERA project at dbGaP phs000761).

  Study phs000796

• Genome-Wide Association Analysis of Biomarkers in the InCHIANTI and BLSA

  Version 1 The aim of this study was to identify gene(s) associated with serum iron concentrations. This dataset contains the results from a meta-analysis of 1919 subjects from the InCHIANTI and Baltimore Longitudinal Study of Aging (BLSA). Both studies are population based prospective studies that evaluate the contributors of normal aging. Version 2 We performed genome wide analysis of 93 circulating biomarkers in the InCHIANTI study of 1210 individuals, after imputation from the 1000 genomes project.

  Study phs000215

• H3K27ac ChIP-seq in a selected group of AML patients

  ChIP-seq data were generated for a number of selected patients to investigate changes in enhancer and promoter regions. ChIP was performed as described previously with slight modifications27. Briefly, cells were crosslinked with 1% formaldehyde for 10 minutes at room temperature and the reaction was quenched with glycine at a final concentration of 0.125 M. Chromatin was sheared using the Covaris S220 focused-ultrasonicator to an average size of 250–350 bp. A total of 2.5 µg of antibody against H3K27ac (Abcam, ab4729) was added to sonicated chromatin of 2 × 106 cells and incubated overnight at 4 °C. Protein A sepharose beads (GE healthcare) were added to the ChIP reactions and incubated for 2 h at 4 °C. Beads were washed and chromatin was eluted. After crosslink reversal, RNase A and proteinase K treatment, DNA was extracted with the Monarch PCR & DNA Cleanup kit (NEB). Sequencing libraries were prepared with the NEBNext Ultra II DNA Library Prep Kit for Illumina (NEB) according to the manufacturer’s instructions. The quality of dsDNA libraries was analyzed using the High Sensitivity D1000 ScreenTape Kit (Agilent) and concentrations were assessed with the Qubit dsDNA HS Kit (Thermo Fisher Scientific). Libraries were single-end sequenced on a HiSeq 4000 (Illumina). ChIP-seq reads were aligned to the human reference genome build hg19 with bowtie

  Dataset EGAD00001007582

• Multi-Omic Investigation of Beckwith-Wiedemann Syndrome Wilms Tumor

  Wilms’ Tumor (WT), also known as nephroblastoma, is one of the most common malignant kidney tumors diagnosed in children. One of the most common WT predisposition syndromes is Beckwith-Wiedemann Syndrome (BWS, OMIM: 130650), which affects approximately 1/10,000 live births. In this study, we perform Whole Exome Sequencing (WES), DNA methylation array, and messenger RNA-Sequencing (mRNA-Seq), to examine the genomic, methylomic, and transcriptomic signature of BWS WT. We analyzed six tumor-normal paired samples, three BWS tumor only samples, and four non-BWS control samples to identify BWS WT drivers.

  Study phs002769

• ABHD11 inhibition drives sterol metabolism to modulate T cell effector function and alleviate autoimmunity

  Chronic inflammation in autoimmunity is driven by hyperactive T cells with dysregulated metabolism. ABHD11 is a mitochondrial hydrolase that supports alpha-ketoglutarate dehydrogenase function and has been associated with remission in rheumatoid arthritis. To explore its role in T cell function, we used CRISPR/Cas9 to knock down ABHD11 in Jurkat T cells and performed RNA-Seq analysis. Differential gene expression revealed widespread transcriptional changes, with sterol-related pathways among the most significantly enriched. These findings highlight ABHD11 as a potential regulator of metabolic programming in T cells with implications for autoimmunity.

  Study EGAS50000001297

• Integrative understanding of human immune system by functional genomics and development of intervention strategies for the prevention of autoimmune diseases

  To elucidate the regulation of B cell recptor repertoire in B cell subsets and its contribution to autoimmune diseases, B cell subsets from 36 Systemic Lupus Erythematosus(SLE), 90 Systemic Sclerosis(SSc), 85 Myositis(IIM), 21 Mixed Connective Tissue Disease(MCTD), 18 Sjogren's syndrome(SjS), 27 Rheumatoid Arthritis(RA), 23 Behcet's disease(BD), 18 Adult Onset Still���s Disease(AOSD), 24 ANCA-associated Vasculitis(AAV), 16 Takayasu���s Arteritis(TAK) and 137 healthy controls(HC) were collected (Naive_B, USM_B, SM_B, DN_B, Plasmablast. RNA-seq and BCR-mapping was performed with each B cell subset samples.

  Study JGAS000485

• An Integrated Approach to Patient Stratification and Therapy Selection in Acute Myeloid Leukemia

  As more clinically-relevant genomic features of myeloid malignancies are revealed, it has become clear that targeted clinical genetic testing is inadequate for risk stratification. Here, we developed and validated a clinical transcriptome-based assay for stratification of acute myeloid leukemia (AML). Comparison of RNA-Seq to whole genome and exome sequencing revealed that as a standalone assay, RNA-Seq offered the greatest diagnostic return, enabling identification of expressed gene fusions, single nucleotide and short insertion/deletion variants, and whole-transcriptome expression information. Expression data were used to develop a novel risk score which, when combined with molecular risk guidelines, allowed for the re-stratification of 22.1 to 25.3% of AML patients from three independent cohorts into correct risk groups. Within the adverse-risk subgroup, we identified a subset of patients characterized by dysregulated integrin signaling and RUNX1 or TP53 mutation. We show that these patients may benefit from therapy with inhibitors of focal adhesion kinase (PTK2), demonstrating additional utility of transcriptome-based testing for therapy selection in myeloid malignancy.

  Dataset EGAD00001006701

• RNA-seq data

  RNA-seq FASTQ files from 296 bulk pre-treatment tumors from IMblaze370

  Dataset EGAD00001008553

• WGS and WES data of metastatic breast cancer tissues and organoids

  Paired-end WGS (x25) and WES data (x2) from metastatic breast cancer organoids, tissues and germline controls. WGS was performed on Illumina NovSeq 6000 and HiSeq X, using Illumina TruSeq Nano DNA kit. WES was performed on Illumina NovSeq 6000 and HiSeq 2000, using Agilent SureSelect XT HS + Human All Exon V7 and SureSelect Human All Exon V6+UTR (hg19).

  Dataset EGAD50000000817