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• Hospital for Sick Children 2020 Pediatric Low-Grade Glioma RNA and Targeted DNA Sequencing

  Whole transcriptome and targeted dna sequencing (Ampliseq) of pediatric low-grade glioma samples at the Hospital for Sick Children

  Dataset EGAD00001005987

• A118862B

  Whole genome sequencing for single cells for library A118862B 1152 cells; filetype=bam

  Dataset EGAD00001007606

• A98271A

  Whole genome sequencing for single cells for library A98271A 1190 cells; filetype=bam

  Dataset EGAD00001007633

• Dataset for transcriptome sequencing of forebrain organoids from Lissencephaly patients

  This dataset contains transcriptome sequencing for 16 samples of forebrain organoids from Lissencephaly patients. The sequencing was performed on Illumina NextSeq 6000 . The sequencing was always paired.

  Dataset EGAD00001015688

• RNA-seq data from paired tumour and germline samples from mesothelioma patients for study EGAS00001005196

  RNA-seq data from paired tumour and germline samples from mesothelioma patients for study EGAS00001005196

  Dataset EGAD00001007874

• Utility of ctDNA to support patient selection for early phase clinical trials: The TARGET Study

  The TARGET Study consists of 200 BAM files, for the 100 patients discussed in the publication. Each patient has a normal control BAM file and a ctDNA BAM file.

  Dataset EGAD00001004796

• 10x Genomics Single Cell Gene Expression for SA1053BX1XB01603

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1053 passage 1

  Dataset EGAD00001009131

• 10x Genomics Single Cell Gene Expression for SA1047BX1XB01022

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1047 passage 1

  Dataset EGAD00001009146

• 10x Genomics Single Cell Gene Expression for SA1056

  10x Genomics Single Cell Gene Expression for Telomerase immortalized breast epithelium cell line 184-hTERT-22 L9 116.126

  Dataset EGAD00001009112

• 10x Genomics Single Cell Gene Expression for SA604X6XB01979

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA604 passage 6

  Dataset EGAD00001009117

• 10x Genomics Single Cell Gene Expression for SA604X7XB02089

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA604 passage 7

  Dataset EGAD00001009119

• 10x Genomics Single Cell Gene Expression for SA609X6XB01899

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA609 passage 6

  Dataset EGAD00001009120

• 10x Genomics Single Cell Gene Expression for SA1050DX1XB01437

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1050 passage 1

  Dataset EGAD00001009126

• 10x Genomics Single Cell Gene Expression for SA1181AX1XB02700

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1181 passage 1

  Dataset EGAD00001009135

• 10x Genomics Single Cell Gene Expression for SA1162BX1XB03004

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1162 passage 1

  Dataset EGAD00001009138

• 10x Genomics Single Cell Gene Expression for SA605X3XB01966

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA605 passage 3

  Dataset EGAD00001009142

• 10x Genomics Single Cell Gene Expression for SA1035X7XB03502

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA1035 passage 7

  Dataset EGAD00001009151

• 10x Genomics Single Cell Gene Expression for SA610X3XB03802

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA610 passage 3

  Dataset EGAD00001009160

• 10x Genomics Single Cell Gene Expression for SA1050EX1XB01442

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1050 passage 1

  Dataset EGAD00001009141

• 10x Genomics Single Cell Gene Expression for SA1035X6XB03216

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA1035 passage 6

  Dataset EGAD00001009154

• Single Cell Genome Sequence for DLP+ library A95722A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA604 passage 6 on DLP+ library A95722A

  Dataset EGAD00001009451

• Single Cell Genome Sequence for DLP+ library A98247A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA530 passage 3 on DLP+ library A98247A

  Dataset EGAD00001009646

• Single Cell Genome Sequence for DLP+ library A96168B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient SA1105, patient SA1106 on DLP+ library A96168B

  Dataset EGAD00001009644

• 10x Genomics Single Cell Gene Expression for SA1049CX1XB01422

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1049 passage 1

  Dataset EGAD00001009140

• A98274B

  Whole genome sequencing for single cells for library A98274B 1295 cells; filetype=bam

  Dataset EGAD00001007128

• CRISPR screen M14, NCI-H3122 (2019-08-28)

  Genome wide CRISPR screen was performed to find resistance to targeted drugs for melanoma and lung . This dataset contains all the data available for this study on 2019-08-28.

  Dataset EGAD00001005296

• 10x Genomics Single Cell Gene Expression for SA1188

  10x Genomics Single Cell Gene Expression for Telomerase immortalized breast epithelium cell line 184-hTert L9 116.66

  Dataset EGAD00001009114

• 10x Genomics Single Cell Gene Expression for SA1052JX1XB01535

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1052 passage 1

  Dataset EGAD00001009134

• Hi-C for Junvenile Pilocytic Astrocytomas

  5 Hi-C datasets (4 JPA and 1 LGG). Hi-C data for the remaining 5 JPAs used in our paper as well as all controls have been uploaded to EGA under EGAS00001005476.

  Dataset EGAD00001009044

• Single Cell Genome Sequence for DLP+ library A96212B

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA604 passage 7 on DLP+ library A96212B

  Dataset EGAD00001009476

• A Hematogenous Route for Medulloblastoma Leptomeningeal Metastases

  A Hematogenous Route for Medulloblastoma Leptomeningeal Metastases

  Dataset EGAD00001003907

• GBM-ZEB1: RNA sequencing of parental tumors used for cell line generation

  This dataset contains RNA sequencing raw data from four parental tumors that were used for classification of gene expression subtypes (Verhaak, Cancer Cell 2010) using ssGSEA.

  Dataset EGAD00001001627

• McGill EMC Release 4 for assay "ATAC-seq"

  McGill EMC Release 4 for assay "ATAC-seq": Sequencing of transposase-accessible chromatin as described by Buenrostro et al. (Nature Methods 10, 1213?1218 (2013) doi:10.1038/nmeth.2688)

  Dataset EGAD00001001300

• BLUEPRINT: WGBS-seq for monocytes and neutrophils

  WGBS-seq for monocytes and neutrophils

  Dataset EGAD00001000673

• Dataset for whole exome sequencing of 113 pairs of tumor and normal DNA samples along with 8 cell lines

  Dataset for whole exome sequencing of 113 pairs of tumor and normal DNA samples along with 8 cell lines.

  Dataset EGAD00001001006

• 10x Genomics Single Cell Gene Expression for SA535X9XB03617

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 9

  Dataset EGAD00001009157

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: pancreas_LCM (2020-01-15)

  Samples prepared by LCM - 5 cases for pilot study. Bulk DNA not available. . This dataset contains all the data available for this study on 2020-01-15.

  Dataset EGAD00001005789

• HV31 - Illumina PCR-free sequencing

  Illumina PCR-free sequencing data for individual HV31 generated using DNA from peripheral blood mononuclear cells, to a sequencing depth of ~44×. Sequencing was performed at the Wellcome Centre for Human Genetics on the Illumina Novaseq platform.

  Dataset EGAD00001007042

• A98282A

  Whole genome sequencing for single cells for library A98282A 1198 cells; filetype=bam

  Dataset EGAD00001007129

• Evaluation of somatic mutations in cervicovaginal samples as a non-invasive method for the detection and molecular classification of endometrial cancer

  Evaluation of somatic mutations in cervicovaginal samples as a non-invasive method for the detection and molecular classification of endometrial cancer

  Dataset EGAD00001011123

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

  Data supporting: "TBC" Ganguli et al (RNA for 394 samples)

  Dataset EGAD00001011190

• Ultra-sensitive ctDNA monitoring required for predicting response and resistance to immunotherapy in advanced melanoma

  Circulating tumor DNA (ctDNA) monitoring in peripheral blood has shown promise for disease surveillance and prognostication of ICI response. Yet even in the metastatic context, ctDNA signals can be missed, suggesting the need for increased assay sensitivity. We used a tumor-informed ctDNA assay capable of detection down to 1 part-per-million (PPM) ctDNA to profile 188 plasma samples from 23 melanoma patients receiving ICI over several years. Residual disease was detected in ctDNA over a broad range, from 130,000 PPM down to 2.3 PPM, with approximately a quarter of detections below 50 PPM. Early on-treatment increases in ctDNA level, and both ctDNA-based molecular clearance (mCR) and molecular progression (mPD) were all prognostic of both OS and PFS. Additionally, mCR consistently preceded radiographic imaging. Our results show the importance and utility of an ultra-sensitive ctDNA assay in advanced melanoma treated by ICI with potential implications for other cancers.

  Study EGAS50000000550

• Full genome sequencing of a monozygotic twin discordant for schizophrenia

  We sequenced the genomes from a monozygotic twin discordant for schizophrenia and a tumor-normal pair of an ovarian cancer patient. Using whole-genome twin data to discriminate between correctly identified single nucleotide variants (SNVs) and errors a strategy for the accurate detection of SNVs was developed. By applying stringent sequencing quality measures, excluding error-prone regions and selecting SNVs identified by different mapping and variation calling algorithms, error rates were ~37-fold reduced. This enabled us to identify the first discordant SNVs in monozygotic twins using whole-genome sequencing. In addition, by showing that novel SNVs are highly enriched in errors, accurate estimates of the number of novel and rare SNVs occurring in unrelated Caucasian individuals were obtained. Finally, somatic mutations in coding and regulatory sequences were reliably identified in the highly rearranged ovarian tumor. Overall, our data demonstrate that strategies to reduce error rates in whole-genomes are required for disease gene discovery.

  Study EGAS00001000152

• Control iPSC lines with clinically annotated genetic variants for versatile multi-lineage differentiation

  Induced Pluripotent Stem Cells (iPSC) derived from healthy individuals are important controls for disease modeling studies. To create a resource of genetically annotated iPSC, we reprogrammed footprint-free lines from four volunteers in the Personal Genome Project Canada (PGPC). Multilineage directed differentiation efficiently produced functional cortical neurons, cardiomyocytes and hepatocytes. Pilot users further demonstrated line versatility by generating kidney organoids, T-cells and sensory neurons. A frameshift knockout was introduced into MYBPC3 and these cardiomyocytes exhibited a hypertrophic phenotype as expected. WGS annotation of PGPC lines revealed on average 20 coding variants. Importantly, nearly all annotated PGPC and HipSci lines harboured at least one pre-existing or acquired variant with cardiac, neurological or other disease associations. Overall, PGPC lines were efficiently differentiated by multiple users into cell types found in six tissues for disease modelling, and clinical annotation highlighted variant-preferred lines for use as unaffected controls in specific disease settings.

  Study EGAS00001003684

• APCDR Uganda GWAS: Genome-wide sequence variation and susceptibility loci for cardiometabolic traits in a sub-Saharan African population (UG2G component)

  Genomic studies in African populations provide unique opportunities to understand disease aetiology, human genetic diversity and population history in a regional and a global context. To leverage the relative benefits of different strategies, we undertook a combined approach of genotyping and whole-genome sequencing (WGS) in a population-based study of 6,400 individuals from a geographically defined rural community in South-West Uganda. We present data from 4,778 individuals with genotypes for ~2.2 million SNPs from the Uganda GWAS resource (UGWAS), and sequence data on up to 1,978 individuals spanning 41.5M SNPs and 4.5M indels (UG2G); 343 individuals overlap between the two datasets. We highlight the value of the largest sequence panel from Africa to date as a global resource for variant discovery, imputation and understanding the mutational spectrum and its clinical relevance in African populations. Alongside phenotype data, we provide a rich new genomic resource for researchers in Africa and globally.

  Study EGAS00001000545

• White blood cell and cell-free DNA analyses for detection of residual disease in gastric cancer

  Liquid biopsies are providing new opportunities for detection of residual disease in cell-free DNA (cfDNA) after surgery but may be confounded through identification of alterations arising from clonal hematopoiesis. Here, we identify circulating tumor-derived DNA alterations (ctDNA) through ultrasensitive targeted sequencing analyses of matched cfDNA and white blood cells from the same patient. We apply this approach to analyze samples from patients in the CRITICS trial, a phase III randomized controlled study of perioperative chemotherapy in patients with operable gastric cancer. After filtering alterations derived from matched white-blood cells, the presence of ctDNA predicts recurrence when analyzed within nine weeks after preoperative treatment and after surgery in patients eligible for multimodal treatment. These analyses provide a facile method for distinguishing ctDNA from other cfDNA alterations and highlight the utility of ctDNA as a predictive biomarker of patient outcome to perioperative cancer therapy and surgical resection in patients with gastric cancer.

  Study EGAS00001004114

• Targeted Sequencing of Primary ER-positive Breast Tumors Treated with 5 Years of Tamoxifen

  Targeted massively parallel sequencing analysis was conducted on DNA extracted from archived 22-28 year old, formalin-fixed primary breast tumors from 625 patents from British Columbia treated with five years of adjuvant tamoxifen monotherapy and followed for over 10 years. Genes were selected for targeted sequencing by review of existing large-scale breast cancer sequencing studies and breast cancer literature. In total, 83 genes were identified and 3,029 probes were designed to tile across all known exons. Illumina sequencing libraries were constructed, indexed, pooled, and enriched for target sequences by hybrid-capture followed by sequencing of paired-end 100bp reads. All samples met minimum quality controls of 80% targeted space covered at 20X or greater. On average, each sample had 336M aligned bases and a mean coverage of 135.8X.

  Study phs001234

• Mayo Clinic and Illumina Collaborative Early Stage Ovarian Cancer (ESOC) Study

  Twenty five patients with early stage carcinoma (Stage I and II) of the ovary were consented for this study. As part of a collaborative agreement with Illumina Inc, Tumor-DNA and patient matched normal DNA from blood underwent whole genome sequencing and microarray genotyping and RNA underwent RNASeq. Tissue also underwent IHC staining for TP53 mutations. The aim of the study was to profile the genomic landscape of these early tumors to discover biomarkers for early detection or subgrouping into different genomic or outcome subgroups. Analyses performed include somatic mutation analysis, RNASeq mutation analysis, LOH analysis, structural variant detection. The current release of this study focusses on 17 patients with serous carcinoma and stage 1 or 2 and with high grade (3 or 4).

  Study phs000897

• Construction of Thousands of Single Cell Genome Sequencing Libraries Using Combinatorial Indexing

  Single-cell genome sequencing has proven valuable for the detection of somatic variation, particularly in the context of tumor evolution. Current technologies suffer from high library construction costs which restrict the number of cells that can be assessed and thus impose limitations on the ability to measure heterogeneity within a tissue. Here, we present Single cell Combinatorial Indexed Sequencing (SCI-seq) as a means of simultaneously generating thousands of low-pass single cell libraries for somatic copy number variant detection. We constructed libraries for 16,698 single cells from a combination of cultured cell lines, primate frontal cortex tissue, and two human adenocarcinomas, including a detailed assessment of subclonal variation within a pancreatic tumor. "Reprinted from Vitak, S.A., et. al. 2017 with permission from Nature Methods."

  Study phs001268

• Radiation-induced gliomas represent H3-/IDH-wild type pediatric gliomas with recurrent PDGFRA amplification and loss of CDKN2A/B

  Long-term complications such as radiation-induced second malignancies occur in a subset of patients following radiation-therapy, particularly relevant in pediatric patients due to the long follow-up period in case of survival. Radiation-induced gliomas (RIGs) have been reported in patients after treatment with cranial irradiation for various primary malignancies such as acute lymphoblastic leukemia (ALL) and medulloblastoma (MB). We perform comprehensive (epi-) genetic and expression profiling of RIGs arising after cranial irradiation for MB (n=23) and ALL (n=9). Our study reveals a unifying molecular signature for the majority of RIGs, with recurrent PDGFRA amplification and loss of CDKN2A/B and an absence of somatic hotspot mutations in genes encoding histone 3 variants or IDH1/2, uncovering diagnostic markers and potentially actionable targets.

  Study EGAS00001005243

• Synthetic data - Genome in a Bottle

  In May, the National Institute of Standards and Technology (NIST) released its first genome in a bottle, a reference sample of DNA for validating human genome sequences. This so-called truth sequence comes from a decades-old sample donated by a Utah woman for (other) research purposes (NA12878 cell line), which, over the years, has been one of the most studied, and hence best-characterized, human samples. Seeing genomic medicine moving toward mainstream healthcare, researchers at NIST recognized the need for a reference human genome and assembled a private-public consortium in 2012 to create one. As detailed in a 2014 Nature Biotechnology paper (Nat. Biotechnol.32, 246–251, 2014), the group integrated and arbitrated among sequences from 14 data sets, five sequencing technologies, seven read mappers and three variant callers.

  Study EGAS00001005591

• Professors Colin Palmer and Ewan Pearson, from University of Dundee, are both members of the Access Group panel for the GoDARTS bioresource, which provided the data for the current study. The current Study used genotypes (EGAD00010000282) generated by the WTCCC2 (EGAS00000000121), on which both Colin and Ewan are also DAC panel members.

  Dac EGAC00001000504

• Whole Exome Sequencing for Characterization of Disease Causing Mutations in two Pakistani Families Suffering from Autosomal Recessive Ocular Disorders.

  Whole Exome Sequencing for Characterization of Disease Causing Mutations in two Pakistani Families Suffering from Autosomal Recessive Ocular Disorders.

  Dataset EGAD00001000024

• Dataset for WGS and RNA melanoma samples

  This dataset contains WGS and RNA sequencing data for 4 melanoma samples. Sequencing was performed on Illumina Novaseq 6000 and Illumina HiSeq X. The sequencing was always paired.

  Dataset EGAD50000000093

• WGS of ecDNA neuroblastoma cell lines

  ecDNA reconstruction for MYCN-amplified neuroblastoma cell lines using shallow long-read whole-genome sequencing (MinION platform, WGS mean-coverage 5-10X).

  Study EGAS50000000349

• Dataset for "HPV integration induces gene fusions" (pacBio)

  pacBio whole-genome sequencing data for "HPV integration induces gene fusions" We performed long read whole-genome sequencing on four HPV+ head and neck cancer samples using pacBio HiFi. The sequence reads were submitted in fastq format.

  Dataset EGAD50000001304

• miRNA

  miRNA Sequencing of olfactory mucosa (OM) cells derived from cognitively healthy and individuals with AD exposed to traffic-related ultrafine particles (UFPs) for 72h in submerged cultures. The UFPs used for exposures were: A0 and A20. Exposures were compared to the corresponding blank samples.

  Dataset EGAD50000001532

• RNA-seq dataset for two NUP98-Rearranged Acute Myeloid Leukemia PDX samples

  This dataset includes RNA-seq of two patient-derived xenograft (PDX) samples with NUP98-Rearranged Acute Myeloid Leukemia. Bam files are provided for each sample.

  Dataset EGAD50000001564

• NGS-based targeted exome sequencing of osteosarcoma

  The present study aimed to identify potential genomic markers for the prediction of chemosensitivity in patients with OS using a genomic approach.

  Study JGAS000282

• Clinical and neuroimaging study on preclinical Alzheimer's disease.

  This clinical study aims to discriminate MCI individuals at risk for development of Alzheimer dementia, as well as preclinical AD without clinical manifestations.

  Study JGAS000272

• Zimbabwe Mendelian Disorders Genomics DAC

  Data Access Committee responsible for reviewing and approving access requests to human genomic data generated from individuals with suspected Mendelian disorders. The DAC ensures ethical use of genomic data in accordance with institutional, national, and international guidelines, protecting participant privacy while enabling responsible data sharing for research purposes.

  Dac EGAC50000000963

• Exome_sequencing_of_Non_syndromic_Congenital_Heart_Defects

  Exome sequencing of ~1,800 patients with non-syndromic Congenical Heart Defects (CHD) to identify genes enriched for damaging rare variants that increase risk of CHD

  Study EGAS00001002522

• WTCCC2 Bacteraemia Susceptibility (BS) samples

  A WTCCC2 project genome-wide association study for bacteraemia susceptibility in 4924 individuals from Kenya, genotyped on the Affymetrix 6.0 array.

  Study EGAS00001001756

• A118869A

  Whole genome sequencing for single cells for library A118869A 1165 cells; filetype=bam

  Dataset EGAD00001007099

• A98258B

  Whole genome sequencing for single cells for library A98258B 1357 cells; filetype=bam

  Dataset EGAD00001007127

• A98285A

  Whole genome sequencing for single cells for library A98285A 1422 cells; filetype=bam

  Dataset EGAD00001007131

• Single Cell Genome Sequence for DLP+ library A98243B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient SA1096A, patient-derived xenograft SA1052D passage 1 on DLP+ library A98243B

  Dataset EGAD00001009481

• A96183B

  Whole genome sequencing for single cells for library A96183B 1191 cells; filetype=bam

  Dataset EGAD00001007619

• A98289A

  Whole genome sequencing for single cells for library A98289A 1066 cells; filetype=bam

  Dataset EGAD00001007634

• A98253B

  Whole genome sequencing for single cells for library A98253B 1388 cells; filetype=bam

  Dataset EGAD00001007630

• A110618B

  Whole genome sequencing for single cells for library A110618B 1047 cells; filetype=bam

  Dataset EGAD00001007600

• A108863A

  Whole genome sequencing for single cells for library A108863A 1301 cells; filetype=bam

  Dataset EGAD00001007597

• A110621A

  Whole genome sequencing for single cells for library A110621A 1137 cells; filetype=bam

  Dataset EGAD00001007601

• A98172B

  Whole genome sequencing for single cells for library A98172B 941 cells; filetype=bam

  Dataset EGAD00001007641

• WGBS for T-Cell and B-Cell, control and tumor

  WGBS data for 75 paired fastq, spread over 31 samples (4 healthy T-cell, 7 healthy B-cell, 20 B-cell CLL tumors) of the CancerEpiSys-PRECiSe project.

  Dataset EGAD00001005970

• HV31 - Oxford Nanopore PromethION long-read sequencing

  Oxford Nanopore long-read sequencing data for individual HV31 generated using DNA from CD14+ monocytes, to a sequencing depth of ~63×. Sequencing was performed at the Wellcome Centre for Human Genetics using the Oxford Nanopore PromethION platform.

  Dataset EGAD00001007043

• A98256A

  Whole genome sequencing for single cells for library A98256A 1372 cells; filetype=bam

  Dataset EGAD00001007124

• A95646B

  Whole genome sequencing for single cells for library A95646B 507 cells; filetype=bam

  Dataset EGAD00001007306

• A98168A

  Whole genome sequencing for single cells for library A98168A 1294 cells; filetype=bam

  Dataset EGAD00001007624

• Glioblastoma stem cell lines WGS data

  WGS data for 20 Glioblastoma stem cell (GSC) lines and matched blood samples. Fastq files are available. For 10 GSC samples and the 10 matched blood samples the reads are on 3 fastq files per sample

  Dataset EGAD00001006488

• Data for the genome‐wide association study of cutaneous leishmaniasis in Brazil

  DNAs were genotyped on Illumina Infinium HumanCoreExome Beadchips (Illumina Inc., San Diego, CA, USA) with probes for 551,004 single nucleotide variants (SNVs): 282,373 informative across ancestries; 268,631 exome-focused. Human genome build 37 (hg19) was used.

  Dataset EGAD00001006681

• A118830A

  Whole genome sequencing for single cells for library A118830A 912 cells; filetype=bam

  Dataset EGAD00001007604

• Single Cell Genome Sequence for DLP+ library A118808A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1096B passage 1 on DLP+ library A118808A

  Dataset EGAD00001009440

• A96175C

  Whole genome sequencing for single cells for library A96175C 1473 samples; filetype=bam

  Dataset EGAD00001008243

• A96186C

  Whole genome sequencing for single cells for library A96186C 525 samples; filetype=bam

  Dataset EGAD00001008250

• A96130B

  Whole genome sequencing for single cells for library A96130B 1267 cells; filetype=bam

  Dataset EGAD00001007114

• 10x Genomics Single Cell Gene Expression for SA1054

  10x Genomics Single Cell Gene Expression for Telomerase immortalized breast epithelium cell line 184-hTERT-22 L9 83.86

  Dataset EGAD00001009113

• 10x Genomics Single Cell Gene Expression for SA1096BX1XB02037

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1096 passage 1

  Dataset EGAD00001009137

• 10x Genomics Single Cell Gene Expression for OV2295(R2)

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma cell line OV2295(R2)

  Dataset EGAD00001009144

• Single Cell Genome Sequence for DLP+ library A96180A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA604 passage 6 on DLP+ library A96180A

  Dataset EGAD00001009463

• 10x Genomics Single Cell Gene Expression for SA1035X6XB03211

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA1035 passage 6

  Dataset EGAD00001009150

• 10x Genomics Single Cell Gene Expression for TOV2295(R)

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma cell line TOV2295(R)

  Dataset EGAD00001009158

• A96183C

  Whole genome sequencing for single cells for library A96183C 1036 samples; filetype=bam

  Dataset EGAD00001008247

• A95697B

  Whole genome sequencing for single cells for library A95697B 1233 cells; filetype=bam

  Dataset EGAD00001007610

• A110673B

  Whole genome sequencing for single cells for library A110673B 1153 cells; filetype=bam

  Dataset EGAD00001007603

• A96115B

  Whole genome sequencing for single cells for library A96115B 1201 cells; filetype=bam

  Dataset EGAD00001007112

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

  ATAC-seq data for 4 sample(s) from bone marrow, on Genome GRCh38. 4 run(s), 4 experiment(s), 4 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002710

• A98253A

  Whole genome sequencing for single cells for library A98253A 1250 cells; filetype=bam

  Dataset EGAD00001007629

• Single Cell Genome Sequence for DLP+ library A96130A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA609 passage 8 on DLP+ library A96130A

  Dataset EGAD00001009454

• Single Cell Genome Sequence for DLP+ library A96154A

  Single Cell Genome Sequence for triple negative breast cancer patient SA1135, patient SA1162SA on DLP+ library A96154A

  Dataset EGAD00001009456