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• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB22_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB22_F

  Dataset EGAD00001001707

• Whole exome sequencing for HELIC

  The HELIC study has been whole genome sequencing individuals from 2 Greek isolatedpopulations at 1x depth. The genotype calling process crucially involves a VQSR stepfollowed by imputation-based refinement. We have been investigating optimal ways toincrease calling accuracy. To aid us in setting appropriate parameters for VQSR and otherQC steps, we have carried out whole exome sequencing of a small number ofHELIC samples.

  Dataset EGAD00001001638

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB22_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB22_C

  Dataset EGAD00001001706

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB51_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB51_M

  Dataset EGAD00001001762

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB52_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB52_F

  Dataset EGAD00001001764

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB55_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB55_C

  Dataset EGAD00001001766

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB55_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB55_M

  Dataset EGAD00001001768

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB58_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB58_F

  Dataset EGAD00001001773

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB58_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB58_M

  Dataset EGAD00001001774

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB8_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB8_C

  Dataset EGAD00001001781

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: BvB8_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: BvB8_M

  Dataset EGAD00001001783

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW14_F

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW14_F

  Dataset EGAD00001001788

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW20_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW20_C

  Dataset EGAD00001001796

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW22_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW22_C

  Dataset EGAD00001001799

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW2_M

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW2_M

  Dataset EGAD00001001813

• WGS of 50 Intellectual Disability (ID) trios with Complete Genomics Sequencing. Dataset of sample: MW32_C

  50 trios were whole genome sequenced with Complete Genomics to a depth of 80x. For each trio the child was affected with severe ID, and the parents were unaffected. All trios were negative for array, targeted gene and whole exome screening. Dataset consists of sample: MW32_C

  Dataset EGAD00001001814

• BLUEPRINT release August 2016, RNA-Seq for macrophage - T=6days B-glucan, on genome GRCh38

  RNA-Seq data for 4 macrophage - T=6days B-glucan sample(s). 4 run(s), 4 experiment(s), 4 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002522

• BLUEPRINT release August 2016, RNA-Seq for macrophage - T=6days LPS, on genome GRCh38

  RNA-Seq data for 4 macrophage - T=6days LPS sample(s). 4 run(s), 4 experiment(s), 4 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002337

• Transcriptome/Exome for glioblastoma intra-tumoral heterogeneity

  Total of 49 tumor specimens from 20 patients were subjected for whole-exome and/or whole-transcriptome sequencing including matched normal/blood. Tumor samples are acquired based on 4 categories; 1) locally adjacent tumors, 2) multifocal/multicentric tumors, 3) 5-ALA (+/-) tumors and 4) Longitudinal tumors.

  Dataset EGAD00001002248

• Sequencing Data for Sample 51_Hf01_BlCM_Ct

  Sequencing Data for DEEP Paper: "reChIP-seq reveals widespread bivalency of H3K4me3 and H3K27me3 in CD4+ memory T-Cells" Sample: 51_Hf01_BlCM_Ct (human, female, Blood, CD4+ central memory cell, normal control) Sequencing types are: total RNA, Whole Genome Bisulfite, ChipSeq (H3K27ac, H3K9me3, H3k36me3, H3K4me1, H3k27me3, H3K4me3, Input), reChipSeq (H3K27me3, H3K4me3)

  Dataset EGAD00001002255

• 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

• BLUEPRINT release August 2016, RNA-Seq for macrophage - T=6days untreated, on genome GRCh38

  RNA-Seq data for 4 macrophage - T=6days untreated sample(s). 4 run(s), 4 experiment(s), 4 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002457

• BLUEPRINT release August 2016, DNase-Hypersensitivity for alternatively activated macrophage, on genome GRCh38

  DNase-Hypersensitivity data for 2 alternatively activated macrophage sample(s). 2 run(s), 2 experiment(s), 2 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_dnaseseq_analysis_20160816

  Dataset EGAD00001002481

• WES of oral-mucosa-derived organoids

  Tumor and matching normal tissues were collected from 8 patients and organoids were derived from each tissue. Whole exome libraries were prepared for tumor tissue, normal tissue, tumor organoids and normal organoids, and paired-end sequencing was performed using Illumina Novaseq 6000 system. Only tumor and matching normal tissues were sequenced for the patients without available organoids.

  Dataset EGAD00001005063

• The dataset for Genome-wide cell-free DNA fragmentation in patients with cancer

  The dataset for Genome-wide cell-free DNA fragmentation in patients with cancer includes 538 bam files from whole genome next-generation sequencing on the Illumina HiSeq2500. The samples analyzed include plasma samples from healthy individuals and patients with cancer.

  Dataset EGAD00001005339

• IBD Whole Genome Sequencing (2019-08-14)

  Whole genome sequences at 15X depth of patients with Inflammatory Bowel Disease. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2019-08-14.

  Dataset EGAD00001005254

• RNA-sequencing

  RNA-sequencing for a cohort of B-ALL samples : 5 Down Syndrome (DS), 16 Hyperdiploid (HeH), 6 iAMP21, 9 other. RNA-sequencing for B-cell progenitors from 3 healthy. It also contains RNA-sequencing datasets of Patient-Derived Xenografts (X) developed from the B-ALL samples : 4 Down Syndrome (DS), 4 Hyperdiploid (HeH), 1 iAMP21, 3 other.

  Dataset EGAD00001005426

• Sequencing files for "A Unifying Paradigm for Transcriptional Heterogeneity and Squamous Features in Pancreatic Ductal Adenocarcinoma."

  Files from DNA and RNA sequencing from primary tumors and metastases from pancreatic cancer patients along with matched normal tissues.

  Dataset EGAD00001005519

• Validation data for the SV analysis package: GRIDSS, PURPLE, LINX

  Validation data containing sequencing data of 13 samples. An hybrid capture approach was used to validate findings of both Manta and GRIDSS for the samples in the validation set. The dataset also contains the reference sequences used.

  Dataset EGAD00001005525

• DESIGN II HNSCC RNA-Seq

  RNA-Seq data of 28 HPV-negative HNSCC specimens from patients treated at the Netherlands Cancer Institute (Amsterdam), VU Medical Centre (Amsterdam) or MAASTRO Clinic (Maastricht) in The Netherlands. HNSCC biopsy samples were obtained prior to treatment (chemo-radiotherapy) for the prospective study within the DESIGN project and used for polyA mRNA sequencing.

  Dataset EGAD00001005722

• Human tumour ChIP-seq.

  We profiled 16 patient tumour samples by ChIP-seq. H3K27ac and Input are provided for 16 samples and H3K27me3 is provided for 14 samples. Among the 16 samples, 9 are G34WT and 7 are G34R/V. The raw fastq or bam files are provided.

  Dataset EGAD00001006100

• H3Africa CAfGEN Exome

  Whole Exome Sequencing data from a retrospective paediatric HIV-disease progression cohort defined on the World Health Organization's criteria for paediatric HIV progression. Data comprises of BAM and VCF files for 314 participants from 2 countries: Botswana and Uganda. DNA and RNA samples are linked in bio-repository.

  Dataset EGAD00001006224

• Genomic and transcriptomic data of glioma specimens

  Dataset consists of 207 glioma samples of WHO grades II, III and IV. Dataset consists 182 tumor derived genomic data of ~700 cancer-related and epigenetic-related genes with matched blood samples for 48 specimens. Dataset also consists transcriptomic data for 105 specimens. In total 335 bam files were deposited.

  Dataset EGAD00001006299

• A110673A

  Whole genome sequencing for single cells for library A110673A 1089 cells; filetype=bam

  Dataset EGAD00001007602

• A98172B

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

  Dataset EGAD00001007641

• single-cell RNAseq FASTq files for three muscle-invasive bladder tumors

  single-cell RNAseq FASTq files for three muscle-invasive bladder tumors

  Dataset EGAD00001008001

• Tumour sample for patient SA992

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA992

  Dataset EGAD00001009616

• Tumour sample for patient SA610

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA610

  Dataset EGAD00001009617

• Normal sample for patient SA416

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA416

  Dataset EGAD00001009618

• Normal sample for patient SA1070

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1070

  Dataset EGAD00001009619

• Tumour sample for patient SA1070

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1070

  Dataset EGAD00001009620

• Tumour sample for patient SA997

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA997

  Dataset EGAD00001009621

• Normal sample for patient SA1058

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1058

  Dataset EGAD00001009672

• Dual spatially resolved transcriptomics for human host-pathogen colocalization studies in FFPE tissue sections

  Advamced Visium Spatial Gene Expression assay for FFPE tissues with human and SARS-CoV-2 whole transcriptome (WT) information at a 55 µm resolution. The dataset consists of 13 tissue sections from 5 patient lung tissue samples, 3 from COVID-19 patients and 2 from control patients.

  Dataset EGAD00001008701

• CHROMATIN ACTIVATION PROFILING OF STEREOTYPED CHRONIC LYMPHOCYTIC LEUKEMIAS

  We used chromatin-immunoprecipitation followed by sequencing (ChIP-Seq) with an antibody for the H3K27ac (a bona fide histone mark for regulatory element activation) in sorted CLL cells from 15 CLL, including cases from stereotyped subsets #1, #2, #4, and #8. The samples were sequenced by Illumina HiSeq 2500.

  Dataset EGAD00001009082

• RNA-Seq data for manuscript titled: Multi-omic features of oesophageal adenocarcinoma in patients treated with preoperative neoadjuvant therapy

  RNA-Seq data for manuscript titled: Multi-omic features of oesophageal adenocarcinoma in patients treated with preoperative neoadjuvant therapy

  Dataset EGAD00001008656

• FACS sorting of ploidy populations in an undifferentiated soft tissue sarcoma for RRBS

  Groups of cells belonging to different ploidy populations (based on PI staining) were collected from an undifferentiated soft tissue sarcoma. The different ploidy populations underwent RRBS, after which copy number signatures for the ploidy-sorted populations and the bulk population were extracted.

  Dataset EGAD00001008667

• Bulk ATAC data

  Bulk ATAC libraries were generated for patient samples A.1, A.3, A.5, A.6, A.7, A.11, A.12, A.13 and A.15. For each patient a library of CD3- cells (myeloid cells, considered tumor cells) and CD3+ cells (T cells, considered healthy) were generated.

  Dataset EGAD00001010188

• Center for Common Disease Genomics (CCDG) - Cardiovascular: Emory Cohort

  The National Human Genome Research Institute (NHGRI) has funded the Centers for Common Disease Genomics (CCDG), a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to common disease phenotypes and to better understand the general principles of genomic architecture underlying common, complex inherited diseases. This study contains variant calls derived from the whole genome sequence data of an early-onset coronary artery disease case-control cohort selected from Emory University Cardiovascular Biobank. Case status was assigned based on the presence of myocardial infarction, coronary artery stenosis greater than 70% in at least one coronary artery, and/or revascularization (coronary angioplasty with or without stent placement or coronary artery bypass grafting) at an early age. For these samples "early age" is defined as men 60 years of age or younger and women 70 years of age or younger. The National Human Genome Research Institute (NHGRI) has funded the Centers for Common Disease Genomics (CCDG), a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to common disease phenotypes and to better understand the general principles of genomic architecture underlying common, complex inherited diseases.

  Study phs001880

• A Whole Genome Association Search for Type 2 Diabetes Genes in African Americans

  Over 2.8 million African Americans have type 2 diabetes mellitus (T2DM). This represents approximately 13% of the African American population and a significant proportion of the 21 million Americans living with diabetes. On average, an African American individual is twice as likely to have T2DM as a European American peer. Our research group has been actively involved in the study of African American diabetes genetics for over 15 years. We hypothesize that genes contributing to the development of T2DM in African Americans exist and can be located using modern molecular genetic methods. With the exception of TCF7L2(Transcription factor 7-like 2) evidence to date suggests variants that contribute T2DM risk in European-derived populations are not significant contributors to African American T2DM risk. We have performed a SNP-based Whole Genome Association (WGA) analysis on the Affymetrix 6.0 in a case control population of over 1000 African American T2DM cases and over 1000 non-diabetic controls. The DNAs have been collected from participants using uniform criteria from North Carolina and neighboring states. Genotype data will be subjected to extensive genetic analysis with the goal of defining a priority list of SNPs for genotyping in independent populations for confirmation and further detailed analysis.

  Study phs000140