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• Genetic differences between primary colorectal cancer and its paired synchronous and metachronous metastases

  In this study we present for the first time the genetic differences associated with different chronicity of colorectal cancer liver metastases identified by whole-exome sequencing of 210 CRC samples. We focus on differences in primary tumors as we hypothesize that these are the cause of the differences in the time course of the disease. The results suggest that distinct tumor progression pathways account for different chronicity outcomes with ultimate impact on patient’s prognosis

  Study EGAS50000000996

• LCM-ATACseq on human lung macrophages

  In this study we employed Laser Capture Microdissection (LCM) for the multimodal profiling of lung macrophages cell populations as a function of location within the healthy tissue. In detail, macrophage mini-bulks (~100 cells) were collected from 4 healthy human donors in 5 different locations of the airways (a total of 20 biopsies), including parenchyma (L1 – lower left lobe (LLL); L6 – 80% distance from LLL tip), trachea (L2), bronchi (L3 – 1st/2nd generation; L5 – 3rd/4th generation), and processed for ATAC-seq.

  Study EGAS00001006167

• Single-cell RNA sequencing reveals cell-type specific eQTLs in peripheral blood mononuclear cells

  This proof-of-concept study shows that single-cell RNA sequencing in ~25,000 peripheral blood mononuclear cells (PBMCs) of 45 donors allows for the identification of cell type-specific cis expression quantitative trait loci effects (cis-eQTLs). Moreover, the significant top-eQTL effects show consistent allelic direction (94%) with previously published whole blood deepSAGE data. These cell type-specific eQTLs may give us additional insight into the downstream consequences of genetic risk factors for immune-mediated diseases.

  Study EGAS00001002560

• Platelet response in aspirin adherent pregnant women

  We conducted an unbiased genome-wide assessment of genomic factors that may influence response to low-dose aspirin in pregnant women at high risk of pre-eclampsia in two pregnancy cohorts: Liverpool (n=91) and Dublin (n=91). We applied UK Axiom microarray technology for GWAS investigations. We specified tight phenotyping with COX-selective urinary 11-dehydrothromboxane B2 (pg/mg creatinine) and accounted for adherence/platelet exposure to aspirin by detection of aspirin’s principal urinary metabolite, SUA, with nuclear magnetic resonance (NMR).

  Study EGAS00001005188

• LCM-RNAseq on human lung macrophages

  In the reported study, we employed Laser Capture Microdissection (LCM) for the transcriptome profiling of lung macrophages cells populations as a function of location within the healthy tissue. In detail, macrophage mini-bulks (100 cells each) were collected by LCM from 4 healthy human donors in 5 different locations of the airways (a total of 20 biopsies), including parenchyma (L1 – lower left lobe (LLL); L6 – 80% distance from LLL tip), trachea (L2), bronchi (L3 – 1st/2nd generation; L5 – 3rd/4th generation) and processed for RNA-seq.

  Study EGAS00001006168

• Drug screen in iPSC-Neurons identifies nucleoside analogs as inhibitors of (G4C2)n expression in C9orf72 ALS/FTD

  To investigate the mode of action and potential side-effects we analyzed differential gene expression in Postmitotic C9orf72 iPSC-Neurons by RNAseq. The cells were treated in a 2 dose regime at 10 µm in 0.1 % DMSO for 9 days. Compound treated iPSC-Neurons were washed with PBS, frozen on dry ice and stored at -80°C until RNA isolation. The RNA was isolated using miRNA Mini Kit (Qiagen) using 700 μl of Qiazol. A total of 250 ng of RNA per sample was processed for mRNA library preparation as per the manufacturer’s instructions for Illumina® Stranded mRNA Prep Ligation to be used with the IDT® for Illumina® RNA UD Indexes Set B and sequenced using NextSeq 500/550 High Output Kit v2.5 (Illumina) on NextSeq 550 (Illumina). The data was processed and analyzed using CLC genomics workbench (Version 21.0.3, Qiagen)

  Dataset EGAD00001008674

• WGBS data of solid liver tumor DNA, and WGBS data of cell-free DNA derived from human blood, for CancerDetector study

  The blood samples of four liver cancer patients and four healthy people, and the solid liver tumor samples of two liver cancer patients are collected for this dataset. Blood samples were centrifuged first at 1,600 × g for 10 minutes, and then the plasma was transferred into new micro tubes and centrifuged at 16,000 × g for another 10 minutes. The plasma was collected and stored at -80⁰C. CfDNA was extracted from 5 ml plasma using the Qiagen QIAamp Circulating Nucleic Acids Kit and quantified by Qubit 3.0 Fluoromter (Thermo Fisher Scientific). Bisulfite conversion of cfDNA was performed by using EZ-DNA-Methylation-GOLD kit (Zymo Research). After that, Accel-NGS Methy-Seq DNA library kit (Swift Bioscience) was used to prepare the sequencing libraries. The DNA libraries were then sequenced with 150bp paired-end reads.

  Dataset EGAD00001004317

• Exome sequencing for paired tumor/normal samples from patients with corticotropin-independnet Cushing's syndrome

  Exome sequencing was performed for paired tumor/normal samples from patients with corticotropin-independnet Cushing's syndrome. Tumor DNA was extracted from adrenocortical adenomas and normal DNA was extracted from adjacent adrenal tissues or periphral blood.

  Dataset EGAD00001000715

• FMT metagenomics triads and plasma metabolomics

  These are the metagenomic datasets of 29 FMT traids with corresponding plasma metabolomics. Data for each triad consists of metagenomics for baseline, post FMT and corresponding donor. Clinical data concerning the glucose rate of disappearance and blood pressure are available as phenotypes.

  Dataset EGAD50000000599

• WGS of primary neuroblastoma data

  Study of ecDNA structure heterogeneity for 13 primary neuroblastoma patients from shallow long-read whole-genome sequencing (MinION platform, WGS mean-coverage 5-10X).

  Study EGAS50000000348

• scRNA-seq from lung cancer organoids and immune cells

  15 scRNA-seq samples were multiplexed, and 5' 10X Chromium scRNA-seq was performed. This dataset provides the FASTQ files for the multiplexed data, as well as the BAM files for the demultiplexed samples.

  Dataset EGAD50000000845

• Dataset for early breast cancer samples

  This dataset contains WGS data for 27 tumor, control and patient derived culture samples of patients with breast cancer. Sequencing was performed on Illumina NovaSeq 6000 and HiSeq X using TruSeq Nano DNA Kit. The sequencing was always paired

  Dataset EGAD50000000860

• Fluctuating DNA methylation tracks cancer evolution at clinical scale

  Long-read Nanopore data of fCpGs from Gabbutt & Duran-Ferrer (2025) for developing the EVOFLUx method to study cancer evolution via DNA methylation fluctuations.

  Study EGAS50000001192

• TraIT Cell Line use case

  Experimental data collected from a set of cell lines. To be used as a test for pipelines and infrastructure.

  Study EGAS00001001476

• Whole_genome_sequencing_of_in_vitro_colonies

  In this study we will perform whole genome sequencing on in vitro colonies. Colonies of various sizes (100-300 cells) will be collected for somatic mutation analysis.

  Study EGAS00001003112

• Prognostic markers of DNA methylation and NGS sequencing in progressive glioblastoma from the EORTC-26101 trial

  These dataset contains NGS data from 380 samples from the EORTC-26101 clinical trial for patients with progressive glioblastoma.

  Study EGAS00001007421

• High-throughput sequencing data for study of molecular drivers of resistance to castration in localised prostate cancer

  Aligned whole-genome sequencing and RNA-seq of localised prostate cancer for study 'Loss of SNAI2 in prostate cancer correlates with clinical response to androgen deprivation therapy'.

  Dataset EGAD00001006640

• Chromatin Profiling in Twins (2019-08-21)

  50 lymphoblastoid cell lines of adult female Twins which are part of the MuTHER study, subjected to Chromatin Immunoprecipitation using an antibody for H3K4me1. H3K4me1 peaks mark distal regulatory elements. . This dataset contains all the data available for this study on 2019-08-21.

  Dataset EGAD00001005274

• Single Cell Genome Sequence for DLP+ library A95618B

  Single Cell Genome Sequence for Triple negative breast cancer patient-derived xenograft SA609 passage 3 on DLP+ library A95618B

  Dataset EGAD00001009316

• A95700A

  Whole genome sequencing for single cells for library A95700A 1172 cells; filetype=bam

  Dataset EGAD00001007611

• A96226B

  Whole genome sequencing for single cells for library A96226B 1274 cells; filetype=bam

  Dataset EGAD00001007621

• A98304A

  Whole genome sequencing for single cells for library A98304A 1560 cells; filetype=bam

  Dataset EGAD00001007636

• COVID-19 scRNA-seq, TCR-seq and BCR-seq

  COVID-19 scRNA-seq, TCR-seq and BCR-seq for 291 samples collected from 109 patients. Among 291 samples, 249 of them have two libraries (sequencing runs) for each assay, while 42 have only one library.

  Dataset EGAD00001007995

• BLUEPRINT September 2016, ATAC-seq for tonsil, on Genome GRCh38

  ATAC-seq data for 7 sample(s) from tonsil, on Genome GRCh38. 7 run(s), 7 experiment(s), 7 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002708

• A96181C

  Whole genome sequencing for single cells for library A96181C 1216 cells; filetype=bam

  Dataset EGAD00001007117

• A96240A

  Whole genome sequencing for single cells for library A96240A 1493 cells; filetype=bam

  Dataset EGAD00001007121

• A95731B

  Whole genome sequencing for single cells for library A95731B 1307 cells; filetype=bam

  Dataset EGAD00001007110

• A95663B

  Whole genome sequencing for single cells for library A95663B 1364 cells; filetype=bam

  Dataset EGAD00001007108

• A110632A

  Whole genome sequencing for single cells for library A110632A 1151 cells; filetype=bam

  Dataset EGAD00001007094

• Single Cell Genome Sequence for DLP+ library A96192A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1093C passage 1, patient SA1147 on DLP+ library A96192A

  Dataset EGAD00001009467

• CBD-RAW-REPERTOIRE-T: T cell bulk repertoire sequence files

  fastq and filtered fasta files for T-cell receptor sequencing. For further information regarding this dataset, please contact Rachael Bashford-Rogers at contact@combat.ox.ac.uk.

  Dataset EGAD00001007961

• A95634B

  Whole genome sequencing for single cells for library A95634B 1335 cells; filetype=bam

  Dataset EGAD00001007105

• Sequencing data for oesophageal and related samples - Abbas et al (RNA)

  Data supporting: "Mutational signature dynamics shaping the evolution of oesophageal adenocarcinoma" Abbas et al (RNA for 197 samples)

  Dataset EGAD00001011269

• A96115A

  Whole genome sequencing for single cells for library A96115A 1635 cells; filetype=bam

  Dataset EGAD00001007111

• Single Cell Genome Sequence for DLP+ library A95632A

  Single Cell Genome Sequence for immortalized breast epithelium - BRCA1-/- Tp53-/- cell line 184-hTERT-22 L9 83.86 on DLP+ library A95632A

  Dataset EGAD00001009321

• Single Cell Genome Sequence for DLP+ library A95634A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1091A passage 1 on DLP+ library A95634A

  Dataset EGAD00001009323

• Data files for PCGP SJACT WES

  This dataset contains WES files for the SJACT cohort associated with the paper "Genetic landscape of pediatric Adrenocortical Tumor". In this paper, we analyse 37 adrenocortical tumours (ACTs) by whole-genome, whole-exome and/or transcriptome sequencing.

  Dataset EGAD00001002679

• WGS and WES data for manuscript titled: ctDNA as a biomarker of progression in oesophageal adenocarcinoma

  WGS and WES data for manuscript titled: ctDNA as a biomarker of progression in oesophageal adenocarcinoma

  Dataset EGAD00001008554

• Single Cell Genome Sequence for DLP+ library A96173A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA501 passage 15 on DLP+ library A96173A

  Dataset EGAD00001009459

• Single Cell Genome Sequence for DLP+ library A96177C

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA604 passage 6 on DLP+ library A96177C

  Dataset EGAD00001009462

• Single Cell Genome Sequence for DLP+ library A108765A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1181A passage 1 on DLP library A108765A

  Dataset EGAD00001009428

• Single Cell Genome Sequence for DLP+ library A95621B

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA501 passage 2 on DLP+ library A95621B

  Dataset EGAD00001009487

• Single Cell Genome Sequence for DLP+ library A95635A

  Single Cell Genome Sequence for immortalized breast epithelium - BRCA2-/-; Tp53-/- cell line 184-hTERT-22 L9 116.126 on DLP+ library A95635A

  Dataset EGAD00001009324

• Single Cell Genome Sequence for DLP+ library A95650A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1052J passage 1 on DLP+ library A95650A

  Dataset EGAD00001009325

• A96124B

  Whole genome sequencing for single cells for library A96124B 1241 cells; filetype=bam

  Dataset EGAD00001007616

• A96162A

  Whole genome sequencing for single cells for library A96162A 1505 cells; filetype=bam

  Dataset EGAD00001007618

• A98234B

  Whole genome sequencing for single cells for library A98234B 1600 cells; filetype=bam

  Dataset EGAD00001007627

• A98255B

  Whole genome sequencing for single cells for library A98255B 1394 cells; filetype=bam

  Dataset EGAD00001007632

• A108870A

  Whole genome sequencing for single cells for library A108870A 1795 cells; filetype=bam

  Dataset EGAD00001007598

• Single Cell Genome Sequence for DLP+ library A96142B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient SA1162SA on DLP+ library A96142B

  Dataset EGAD00001009455

• Single Cell Genome Sequence for DLP+ library A95621A

  Single Cell Genome Sequence for Immortalized breast epithelium - BRCA2-/-; Tp53-/- cell line 184-hTERT-22 L9 112.109 cell line SA1055 on DLP+ library A95621A

  Dataset EGAD00001009488

• Combination Therapies for Personalised Cancer Medicine in 11-18 (2019-06-10)

  This study involves mutagenizing 11-18 with ENU to identify those mutations which engender resistance to targeted treatment. . This dataset contains all the data available for this study on 2019-06-10.

  Dataset EGAD00001005081

• A96149A

  Whole genome sequencing for single cells for library A96149A 751 samples; filetype=bam

  Dataset EGAD00001008234

• A108842A

  Whole genome sequencing for single cells for library A108842A 1477 cells; filetype=bam

  Dataset EGAD00001007595

• A98254A

  Whole genome sequencing for single cells for library A98254A 1490 cells; filetype=bam

  Dataset EGAD00001007631

• Clinical data

  This dataset contains demographic, histology, PDL1 IHC, TMB and outcome data (PFS and ORR) for 836 patients, 823 of which had RNAseq, 715 had FMI, with 702 patients having both. The dataset also includes xCell deconvolution scores for patients with RNAseq data.

  Dataset EGAD00001006617

• Single Cell Genome Sequence for DLP+ library A95668A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient SA1162SA on DLP+ library A95668A

  Dataset EGAD00001009447

• Single Cell Genome Sequence for DLP+ library A95717A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1096A passage 1 on DLP+ library A95717A

  Dataset EGAD00001009450

• Single Cell Genome Sequence for DLP+ library A96174A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA501 passage 11 on DLP+ library A96174A

  Dataset EGAD00001009460

• Single Cell Genome Sequence for DLP+ library A96189A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1049C passage 1 on DLP+ library A96189A

  Dataset EGAD00001009465

• Single Cell Genome Sequence for DLP+ library A96213A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA501 passage 6, cell line SA1090 on DLP+ library A96213A

  Dataset EGAD00001009477

• A108851B

  Whole genome sequencing for single cells for library A108851B 1681 cells; filetype=bam

  Dataset EGAD00001007596

• Single Cell Genome Sequence for DLP+ library A95652A

  Single Cell Genome Sequence for immortalized breast epithelium BRCA2+/- Tp53-/- cell line 184-hTert L9 116.66 on DLP+ library A95652A

  Dataset EGAD00001009326

• A96228B

  Whole genome sequencing for single cells for library A96228B 1125 samples; filetype=bam

  Dataset EGAD00001008218

• A96157C

  Whole genome sequencing for single cells for library A96157C 938 samples; filetype=bam

  Dataset EGAD00001008237

• Single Cell Genome Sequence for DLP+ library A98279A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1050A passage 1, patient SA1234 on DLP+ library A98279A

  Dataset EGAD00001009486

• EUROBATS RNAseq BAM files for LCLs

  These analysis are the BAM files for the LCLs samples of the EUROBATS samples.

  Dataset EGAD00001001086

• EUROBATS RNAseq BAM files for the Fat samples

  RNAseq BAM files for the Fat samples of the EUROBATS project

  Dataset EGAD00001001089

• EUROBATS RNAseq BAM files for the Blood samples

  RNAseq BAM files for the blood samples of the EUROBATS project

  Dataset EGAD00001001088

• BLUEPRINT release January 2015, DNase-Hypersensitivity for Acute myeloid leukemia

  DNase-Hypersensitivity data for 1 Acute myeloid leukemia sample(s). 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_dnaseseq_analysis_20140811

  Dataset EGAD00001001190

• WGS files for Mullighan PAX5_B-ALL

  WGS files for Mullighan PAX5_B-ALL paper titled "PAX5-driven Subtypes of B-cell Acute Lymphoblastic Leukemia"

  Dataset EGAD00001004446

• EUROBATS RNAseq BAM files for the Skin samples

  RNAseq BAM files for the Skin samples of the EUROBATS project.

  Dataset EGAD00001001087

• WES files for Mullighan PAX5_B-ALL

  WES files for Mullighan PAX5_B-ALL paper titled "PAX5-driven Subtypes of B-cell Acute Lymphoblastic Leukemia"

  Dataset EGAD00001004447

• Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - 129_rnaseq

  Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - 129_rnaseq EAC expression data - Publication Secrier & Li et al., 2016, Nature Genetics

  Dataset EGAD00001002260

• ICGC-LIRI-JP Release 15

  RIKEN collection WGS reads for 321 HCC and blood matched samples from 158 donors submitted to ICGC for release 15

  Dataset EGAD00001000808

• Whole Exome Sequencing of healthy Spanish individuals - VCF file

  The need for a detailed catalogue of local variability for the study of rare diseases within the context of the Medical Genome Project motivated the whole exome sequencing of 267 unrelated individuals, representative of the healthy Spanish population.

  Dataset EGAD00001003101

• WGBS data for ependymomas and normal controls (fetal and adult)

  Whole genome bisulfite sequencing data for 6 ependymomas plus 3 fetal controls (f1, f2, f4) and 3 adult controls (a2, a3, a4). See Mack, Witt et al. Nature 506(7489):445-50, 2014 (PMID: 24553142).

  Dataset EGAD00001000966

• Cancer-Normal chronic myeloid leukaemia sequencing data for "A comparative analysis of algorithms for somatic SNV detection in cancer", Bioinformatics 29 (2013) 2223

  This dataset contains the fastq sequencing data collected from bone marrow DNA of a chronic myeloid leukaemia patient at time of diagnosis.

  Dataset EGAD00001000967

• APCDR Uganda GWAS - UG2G dataset: Whole genome low depth sequence data for 2000 Ugandans (BAMs).

  Low depth (4x) Illumina HiSeq raw sequence data for 2000 Ugandans from various ethno-linguistic group from rural South-West Uganda (related individuals included).

  Dataset EGAD00001001639

• Dataset for EGAS00001007937

  WGS, RNAseq, Methylation, variant calling analysis for a Novel paediatric case of a spinal high-grade astrocytoma with piloid features in a patient with Noonan Syndrome

  Dataset EGAD00001015412

• Single Cell Genome Sequence for DLP+ library A95629B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1051D passage 1 on DLP+ library A95629B

  Dataset EGAD00001009320

• Expression data

  This dataset contains the RPKM and raw read counts of expression for all the individuals. This dataset was generated as part of the following study: Panousis et al (2019). Combined genetic and transcriptome analysis of patients with SLE: Distinct, targetable signatures for susceptibility and severity.

  Dataset EGAD00001005039

• Clinical phenotypes/covariates

  This dataset contains the clinical phenotypes/covariates information for all the individuals. This dataset was generated as part of the following study: Panousis et al (2019). Combined genetic and transcriptome analysis of patients with SLE: Distinct, targetable signatures for susceptibility and severity.

  Dataset EGAD00001005040

• Analysis File for 87 Argentinean individuals

  VCF for 87 Argentinean samples. Only SNPs (no indels) that passed the Affymetrix QC. Data from Luisi et al. 2020. Plos One. Fine-Scale Genomic Analyses Of Admixed Individuals Reveal Unrecognized Genetic Ancestry Components In Argentina. Reference Allele column does NOT contain reference allele from genome assembly.

  Dataset EGAD00001006227

• RNASeq files for Mullighan TXVI dataset

  RNASeq files for paper titled "Prognostic and therapeutic significance of leukemia subtypes and minimal residual disease measurements in pediatric acute lymphoblastic leukemia treated with contemporary risk-directed trial: a cohort study"

  Dataset EGAD00001006609

• Sequencing data for oesophageal / related samples - Kazachenka et al (RNA)

  Data supporting: "The transcriptional landscape of endogenous retroelements delineates esophageal adenocarcinoma subtypes" RNAseq for 279 samples

  Dataset EGAD00001011076

• DNA WGS Short Read Sequence (Illumina NovaSeq) for manuscript titled: "Performance of Somatic Structural Variant Calling in Lung Cancer using Oxford Nanopore Sequencing Technology"

  DNA WGS Short Read Sequence (Illumina NovaSeq) for manuscript titled: "Performance of Somatic Structural Variant Calling in Lung Cancer using Oxford Nanopore Sequencing Technology"

  Dataset EGAD00001015399

• Automated machine-learning approach for next generation profiling of sequence alterations, mutation burden, microsatellite instability, and structural variants in human cancers

  Sequence and structural alterations together with tumor mutation burden (TMB) and microsatellite instability (MSI) have been identified as biomarkers for the determination of response to targeted and immune checkpoint inhibitor therapies. However, widespread clinical adoption of these biomarkers has historically been limited due to barriers such as evidence of clinical utility and reimbursement. We have developed 2.2 Mb targeted NGS system and an automated machine-learning analysis approach (PGDx elio™ tissue complete, ETC) that has been FDA cleared for examination of 500+ cancer-related genes and 68 mononucleotide repeats for identification of sequence and structural alterations, TMB, and MSI in solid cancers in a clinical setting. We designed and trained this approach using sequence data from 4,174 cancers and >124,000 in silico alterations and evaluated the methodology in >2,550 tumor or non-cancerous normal samples. Independent analyses of ETC sequence changes in 440 formalin fixed paraffin embedded (FFPE) tumor or cell line samples using MSK-IMPACT™, FoundationOne®, and ddPCR revealed a positive percent agreement (PPA) >97% with high sensitivity as low as 3% mutant allele fraction. We observed high concordance between panel-wide and whole-exome TMB for 307 pan-cancer FFPE tumors (Pearson r=0.95, p < 0.0001) using samples with ≥20% tumor cellularity. Comparison of the mutation context and repeat-based MSI approach in ETC with a multiplex MSI PCR assay in 223 samples revealed a PPA of 99% and negative predictive agreement (NPA) >99%. We confirmed the accuracy and precision of TMB and MSI measurements across three independent laboratories (CV of <5% and average PPA >99%, respectively). Finally, evaluation of amplifications and translocations against DNA and RNA-based approaches exhibited >98% NPA and PPA of 86% and 82% respectively. These results demonstrate high analytical performance for determination of sequence and structural changes, TMB, and MSI using a targeted NGS panel and provide a scalable and facile approach for evaluating these biomarkers in a clinical laboratory.

  Study EGAS00001005556

• University of Washington Developmental Single Cell Atlas

  We set out to generate a human cell atlas of both gene expression and chromatin accessibility using tissues obtained during development. In this study, we applied an assay for single cell profiling of gene expression based on three-level combinatorial indexing (sci-RNA-seq3) to 121 fetal tissue samples representing 15 organs, altogether profiling transcription in over 4 million single cells. In parallel, we devised an improved assay for single cell profiling of chromatin accessibility also based on three-level combinatorial indexing (sci-ATAC-seq3). We applied this method to 53 fetal tissue samples representing 15 organs, altogether profiling on the order of one million single cells. From these data, we identify and characterize diverse human cell types and annotate them with respect to marker genes, expression and regulatory modules. These data comprise a rich resource for the exploration of human biology.

  Study phs002003

• Genomic Analysis of Low Grade B-Cell Lymphoma

  We included tumors from 64 newly diagnosed or untreated Low Grade B-Cell Lymphoma (LGBCL) patients, consisting of SMZL (n = 48), NMZL (n = 6), EMZL (n = 2), LPL (n = 5), and B-NOS (n = 3) in this study. Samples were selected from cases consented to the Molecular Epidemiology Resource (MER) of the University of Iowa and Mayo Clinic Lymphoma Specialized Program of Research Excellence (SPORE). RNA or DNA were extracted from 64 frozen LGBCLs tumors (with available matched germline DNA for N=61. For RNA sequencing, library preparation was done using the Illumina TruSeq RNA Exome Kit and sequenced with 100 nucleotide paired-end reads using the HiSeq 4000. For WES, library preparation was done using the Agilent SureSelect XT kit and sequenced with 100 nucleotide paired-end reads using the Illumina HiSeq 4000.

  Study phs002552

• Whole Genome Sequencing of Harvard University Embryonic Stem Cell Lines 63 and 64

  In this study we used next generation deep sequencing technologies to analyze the genomes of Harvard University Stem Cell lines 63 and 64. We performed 101-bp paired-end whole genome sequencing of the two cell lines using Illumina HiSeq platforms. The sequence reads obtained were analyzed for copy number and used for replication timing analysis. Our data suggests that read depth profiles can be used to map replication timing in Embryonic Stem Cells (ESCs). Further we observe that replication profiles are highly correlated across ESCs but distinct from those of other cell types such as Lymphoblastoid Cell Lines (LCLs). These results demonstrated that read depth data from whole genome sequencing can be used to study variation in replication timing within the human population and across different cell types. Whole genome sequences from HUES63 and HUES64 used for this study are being submitted.

  Study phs000825

• DNA and RNA sequencing of single human haploid germ cells

  Our goal was to look at allele-specific gene expression in single spermatids from two human donors. We first genotyped and phased each donor using a combination of linked-read sequencing (one sample per donor, 10X Chromium), and single haploid whole genome sequencing (53 spermatids for the first donor, and 19 for the second). We then sequenced mRNA from single spermatids (302 from the first donor, and 164 from the second), using the Smart-Seq2 protocol. We used these gene expression data, in combination with the haplotype data, to look for gene products that exhibit allele-specific bias reflecting the haploid genotype of the cell. We find a large class of human genes that show such allele-specific bias in spermatids, indicating that these gene products are not fully shared across the cytoplasmic bridges that connect spermatids. We term these genes “genoinformative markers” (GIMs).

  Study phs002279

• Association Between Telomere Length and Falciparum Malaria Endemicity in Sub-Saharan Africans

  The goal of this study was to identify the genetic and environmental drivers of telomere length variation in an ethnically diverse African cohort. It comprises 1,818 participants from Cameroon, Tanzania, Ethiopia, and Botswana. For each participant, leukocyte telomere length was measured using the Southern blotting of the terminal restriction fragment methodology. 1,758 of the individuals with phenotype data also had genetic data, and these individuals were subjected to a genome-wide association study which accounted for age, sex, and genetic relatedness. Individuals were genotyped on one of two genotyping arrays (Illumina Infinium Omni5 array or Illumina H3Africa consortium array). Genetic datasets were merged, and missing genotypes were imputed for a final genetic dataset of 11,001,107 genetic variants. Correlations between telomere length and a variety of environmental factors, including malaria endemicity, were also examined in this study.

  Study phs003567

• Childhood Cancer Data Initiative (CCDI): Molecular Characterization Initiative

  The National Cancer Institute's (NCI) Childhood Cancer Data Initiative (CCDI) focuses on the critical need to collect, analyze, and share data to address the burden of cancer in children, adolescents, and young adults (AYAs). The Molecular Characterization Initiative (MCI) will further the CCDI's goals by providing access to better diagnostic tests for pediatric and AYA patients. The molecular characterizations of solid tumors, soft tissue sarcomas, and rare diseases are performed in a CLIA-certified setting as results may be used to screen for and/or confirm clinical trial eligibility, direct treatment, or otherwise contribute to the conduct of the trial. The following molecular characterization assays were performed:Tumor/Normal Whole Exome sequencing Methylation arraysArcher fusion panel Deidentified clinical reportsNote: New data will be added periodically, please check the CCDI Hub Explore site for updates.

  Study phs002790

• Spatial heterogeneity in medulloblastoma

  Spatial heterogeneity of transcriptional and genetic markers between physically isolated biopsies of a single tumor poses major barriers to the identification of biomarkers and the development of targeted therapies that will be effective against the entire tumor. We analyzed the spatial heterogeneity of multiregional biopsies from 35 patients, using a combination of transcriptomic and genomic profiles. Medulloblastomas (MBs), but not high-grade gliomas (HGGs), demonstrated spatially homogeneous transcriptomes, which allowed for accurate subgrouping of tumors from a single biopsy. Conversely, somatic mutations that affect genes suitable for targeted therapeutics demonstrated high levels of spatial heterogeneity in MB, malignant glioma, and renal cell carcinoma (RCC). Actionable targets found in a single MB biopsy were seldom clonal across the entire tumor,which brings the efficacy of monotherapies against a single target into question. Clinical trials of targeted therapies for MB should first ensure the spatially ubiquitous nature of the target mutation.

  Study EGAS00001001014

• Genetic landscape of inherited retinal dystrophies affected cases in Spain

  Inherited retinal diseases (IRDs), defined by dysfunction or progressive loss of photoreceptors, are disorders characterized by elevated heterogeneity, both at the clinical and genetic levels. Our main goal was to address the genetic landscape of IRD in a Spanish cohort of patients. A retrospective hospital-based cross-sectional study was carried out on IRD affected individuals, referred for genetic testing from all the Spanish autonomous communities. Clinical, demographic and familiar data were collected from each patient, including family pedigree, age of appearance of visual symptoms, presence of any systemic findings and geographical origin. Genetic studies were performed to all families with available DNA using different molecular techniques. Our study provides the general landscape for IRD in Spain and our results have important implications for genetic diagnosis, counselling and new therapeutic strategies to both the Spanish population and other related populations.

  Study EGAS00001005104

• WTS and WES of Renal Cell Carcinoma Tumors From a Phase III Anti-Angiogenic Adjuvant Therapy Trial

  Archival de-identified formalin-fixed paraffin-embedded RCC tumor tissue blocks from nephrectomy or tumor biopsy were processed as per below and the same sections were used for both DNA and RNA extractions. For WES (ACE version 3; Illumina NovaSeq), samples were profiled using Personalis ACE Cancer Exome (Personalis, Inc, Menlo Park, CA) Whole-transcriptome profiles were generated by RNA-seq (Accuracy and Content Enhanced (ACE) version 3; Illumina NovaSeq) using Personalis ACE Cancer Transcriptome (Personalis, Inc, Menlo Park, CA ) Of the 615 patients in the intent-to-treat population in S-TRAC trial, 193 individual specimens were available for molecular profiling, of which 171 (27.8%) (sunitinib, n = 91; placebo, n = 80) returned results for the WES analysis, and 133 (21.6%) (sunitinib, n = 72; placebo, n = 61) returned results for the GES analysis. Of the 138 WTS samples with data, replicates for two patients were summarized by median expression, and three samples were excluded from the final analysis due to low counts.

  Dataset EGAD00001009294

• Early Methamphetamine Abstinence: fMRI and Brain Function

  This study included two groups of subjects, methamphetamine-dependent and healthy control participants, with the purpose of characterizing brain structure and cognition during the first month of abstinence from methamphetamine. Participants were able to participate in one or both phases of the study. Methamphetamine abusers were held as inpatients and abstained from methamphetamine use during the entirety of the study. Phase I covered the 1st week of abstinence and Phase II covered the next 3-4 weeks of abstinence. Control subjects participated as outpatients at timeframes which corresponded to the assessments taken of methamphetamine users. The following outlines the procedures in more detail. After initial telephone screening, in-person screening and recruitment procedures took place at the UCLA Neuropsychiatric Institute. Each methamphetamine abuser subject entered the study after completing an interview and questionnaires on drug use history, and providing a positive urine test for methamphetamine. The evaluation included a psychiatric diagnostic interview according to the Structured Clinical Inventory for DSM-IV (SCID-IV), a medical history and physical examination, blood tests [including a complete chemistry panel, hepatic panel, and tests for hepatitis-C and HIV]. Urine samples were also taken for drug screening of illicit drugs, and to test for pregnancy (female subjects). The methamphetamine abusers were then admitted to the General Clinical Research Center (CRC) and participated on a residential basis, where they were administered daily questionnaires about drug craving, withdrawal and mood. The current study makes available phenotype and genotype data, and interested investigators may contact the principal investigator regarding potential sharing of fMRI data.

  Study phs001198

• Genetic Modifiers of Syndromic Orofacial Clefts

  Reduced penetrance and variable expressivity are common, but poorly understood, features of most monogenic diseases. Genetic modifiers are possible factors to contribute to this phenotypic variability and blur the traditional distinction between monogenic and complex disease. This study focuses on the most common orofacial cleft syndrome (Van der Woude syndrome, VWS) and nonsyndromic orofacial clefts (OFCs), which intersect both in phenotype and in genetic etiology, as a model to understand reduced penetrance and variable expressivity. VWS occurs in 1 in 35,000 individuals and accounts for 2% of all OFCs. The features of VWS include an OFC and/or lower lip pits, but 15% of VWS patients present with an isolated OFC, making them indistinguishable from nonsyndromic OFC patients. Mutations in the genes IRF6 or GRHL3 cause VWS, but approximately 20% of VWS patients currently lack a molecular diagnosis. Furthermore, there are few genotype-phenotype correlations for known mutations and patient phenotypes. By contrast, GWAS of nonsyndromic OFCs have identified a number of risk factors, some of which we have shown increase risk for specific types of OFCs or act as modifiers of OFC subtypes. Whole genome sequencing will be used to identify the remaining genetic mutations for VWS, determine the relationship between those genes/regions with nonsyndromic OFCs, and identify rare and common modifiers of VWS and OFC phenotypes. These analyses will provide further insight into the genetic architecture of VWS and OFCs and will serve as a model for exploring links between other Mendelian disorders that share phenotypes with complex traits.

  Study phs002221

• Melbourne Collaborative Cohort Study DNA Methylation Studies

  This dataset contains raw Illumina 450K blood DNA methylation data from a subset of participants in the Melbourne Cohort Study (MCCS), a prospective study of 41,513 healthy adult volunteers (24,469 women) aged between 27 and 76 years when recruited between 1990 and 1994. Nested case-control studies: DNA methylation data were generated as part of cancer case-control studies nested in the MCCS. Participants were cancer-free at blood draw; blood samples were taken at baseline (1990-1994) for 97% of participants; and for 3% of participants at the second wave of follow-up (2003-2007). Eight separate studies were conducted of breast, prostate, colorectal, lung, kidney, urothelial and gastric cancer and B-cell lymphoma, for a total of > 3,500 cancer cases. Controls were individually matched to cases on age, sex, and country of birth using incidence density sampling. Additional matching on smoking history was made for the study of lung cancer. Longitudinal study: For a subset of 1,100 participants with baseline DNA methylation measures (from dried blood spots) who were selected as controls in the nested case-control studies, repeated methylation measures were made using wave 2 follow-up samples (also from dried blood spots) to study longitudinal DNA methylation changes. Project aims: 1. Nested case-control studies: To assess prospective associations between peripheral blood DNA methylation and risk of eight cancer types (breast, prostate, colorectal, lung, kidney, urothelial cell and gastric cancer, and mature B-cell neoplasms). 2. Longitudinal study: To assess associations between lifestyle changes and changes in peripheral blood DNA methylation.

  Study phs003213