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• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 8a)

  Whole genome sequencing data of 26 high-grade serous carcinoma (HGSC) patients (87 samples) sequenced with MGISEQ-2000 and HiSeq X Ten.

  Dataset EGAD00001011304

• WGS data of paediatric B-other B cell acute lymphoblastic leukemia (set1)

  The dataset includes FASTQ and BAM files from diagnostic and matched remission (control) samples of five B-other ALL patients (ALLT-327, ALLT-334, ALLT-357, ALLK-108, ALLT-361). Sequencing library was made using NEB Next® Ultra™ DNA Library Prep Kit. Both diagnostic (60x) and remission (30x) samples were sequenced using HiSeq X.

  Dataset EGAD50000002157

• RNA sequencing data of pediatric hypodiploid acute lymphoblastic leukemia

  The dataset includes RNA sequencing FASTQ files from a diagnostic tumor sample of one hypodiploid ALL patient (ALLT-351). NEBNext Ultra Directional RNA Library Prep Kit (New England Biolabs) was used in library preparation, and Ribo-Zero Magnetic Kit (Illumina) was utilized in rRNA removal. The diagnostic tumor sample was sequenced using Illumina Novaseq 6000, and the target sequencing depth was 21 Gb.

  Dataset EGAD50000002605

• Raw BulkRNA sequencing data

  BulkRNA sequencing Human Strand Specific mRNA (WOBI) 40M reads was performed by Novogene (Netherlands) using the NovaSeq X Plus Series (PE150, Q30≥85%) sequencing platform and strategy. 24 samples were included in the study, requiring 12 G of raw data per sample.

  Dataset EGAD50000001848

• Tetralogy of Fallot Exome Trios

  Exome sequencing of 30 parent-offspring trios to >50X mean depth, where the offspring has sporadic TOF, to identify potential causal de novo mutations. We will use the exome plus design for pulldown that incorporates ~6.8Mb of additional regulatory sequences in addition to the ~50Mb GENCODE exome.

  Dataset EGAD00001000344

• Primary plasma cell leukemia genomic abnormalities

  Primary plasma cell leukemia (pPCL) samples were sequenced using the Nimblegen MedExome Plus hybridization capture to detect translocations, copy number changes, and mutations in 20 pPCL samples and patient matched controls. Sequencing was performed on a NextSeq500 using 75 bp paired end reads.

  Dataset EGAD00001004323

• 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

• Whole exome sequencing of 3 primary Plasma Cell Leukemia samples

  Primary plasma cell leukemia (pPCL) samples were sequenced using the Nimblegen MedExome Plus hybridization capture to detect translocations, copy number changes, and mutations in 3 pPCL samples and patient matched controls. Sequencing was performed on a NextSeq500 using 75 bp paired end reads.

  Dataset EGAD00001005306

• multi-region sequencing of tumor samples from PDAC patients

  This study includes 542 of multi-region sampled whole exome sequencing data from 83 pancreatic cancer patients in 6 individual experiments : Kras wildtype, local recurrence, treatment-naive (MetomeV2), radiotherapy plus chemotherapy (Radome), chemotherapy-only group (Treatome) and Proj_B-100-478.

  Dataset EGAD00001011109

• Whole exome sequencing (WES) of 95 previously untreated AML samples

  MNC were isolated from bone of 95 AML patients at initial diagnosis via Ficoll gradient. WES has been performed on all 95 samples. Paired exome sequencing was done on a NovaSeq 6000 sequencer with Twist human core exome plus kit.

  Dataset EGAD00001011125

• Characterization of the molecular signature of human monocytes in aging and myelodysplastic syndrome

  Deep immunophenotypic profiling of peripheral blood immune cells from young and older control subjects as well as patients with MDS was initially performed, using mass cytometry to identify monocyte subpopulations. Abundance of monocyte subpopulations separated the samples from patients with MDS from elderly control subjects was identified. Therefore, targeted immunophenotyping of monocytes was also performed with flow cytometry and RNA sequencing from isolated CD14+ peripheral blood longitudinally in 26 subjects, six young healthy individuals, nine older healthy individuals and eleven patients with MDS.

  Study EGAS00001007676

• Whole Exome Sequencing of Human Gastro-esophageal Cancer PDXs

  The current study investigates biomarkers of response to anti-EGFR therapies in gastro-esophageal cancer. Whole exome sequencing was performed on 26 tumors to explore potential factors influencing treatment outcomes. As part of the analysis, somatic mutations in EGFR, ERBB2, and key downstream signaling genes (KRAS and PIK3CA) were examined to exclude the presence of known mutations conferring sensitivity/resistance. The study aims to contribute to the identification of patients who may benefit from lower-toxicity regimens, improving treatment personalization and minimizing adverse effects.

  Study EGAS50000000966

• Datasets of RNA-seq of tumor samples from clear cell renal cell carcinoma patients included in the Translational Program of the NIVOREN GETUG-AFU-26 trial

  RNA-seq analyses were performed on tumor tissue samples of 115 advanced clear cell renal cell carcinoma patients who participated in the NIVOREN GETUG-AFU-26 trial. The samples were obtained prior to treatment initiation. RNA-seq was performed to evaluate previously published gene expression signatures. These included: the IMmotion T effector (CD8A, EOMES, PRF1, IFNG and CD274) and the IMmotion Myeloid (IL-6, CXCL1, CXCL2, CXCL3, CXCL8, and PTGS2) gene signatures represent gene expression patterns associated with T effector cells and myeloid cells, respectively, while JAVELIN Renal 101 Immuno (T-cell receptor signaling: CD3G, CD3E, CD8B, THEMIS, TRAT1, GRAP2, CD247; T-cell activation, proliferation, and differentiation: CD2, CD96, PRF1, CD6, IL7R, ITK, GPR18, EOMES, SIT1, NLRC3; Natural killer cell mediated cytotoxicity: D2, CD96, PRF1, CD244, KLRD1, SH2D1A; Chemokine: CCL5, XCL2; and Other immune response genes: CST7, GFI1, KCNA3, PSTPIP1) represents gene expression patterns associated with both innate and adaptive immune response.

  Dataset EGAD50000001541

• Sequencing data for oesophageal and related samples - ICGC DCC release 26 (WGS)

  WGS sequencing for 303 cases (620 samples) from the ICGC ESAD-UK project Tumours 50x Normals 30x HiSeq X BAM files These samples are all available in ICGC release 26

  Dataset EGAD00001003580

• single-cell RNA-Seq samples of CRC patients

  The dataset contains samples of 11 CRC patients (2 samples for each patient, tumor and normal adjacent tissue site, 22 samples in total). Dataset is composed by fastq file (paired end) type from 10x single-cell RNA-Seq.

  Dataset EGAD00001009634

• Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY)

  The National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) of the National Institutes of Health (NIH) has sponsored a consortium of investigators to conduct a clinical treatment trial, Treatment Options for type 2 Diabetes in Adolescents and Youth (TODAY). The primary objective of the TODAY trial is to compare the efficacy of three treatment arms on time to treatment failure based on glycemic control. The secondary aims are to:compare and evaluate the safety of the three treatment arms;compare the effects of the three treatments on the pathophysiology of type 2 diabetes (T2D) with regards to beta cell function and insulin resistance, body composition, nutrition, physical activity and aerobic fitness, cardiovascular risk factors, microvascular complications, quality of life, and psychological outcomes;evaluate the influence of individual and family behaviors on treatment response; andcompare the relative cost effectiveness of the three treatment arms.The three treatment regimens are: (1) metformin alone, (2) metformin plus rosiglitazone, and (3) metformin plus an intensive lifestyle intervention called the TODAY Lifestyle Program (TLP). The study recruits patients over a three-year period and follows patients for a minimum of two years. Patients are randomized within two years of the diagnosis of T2D.

  Study phs002447

• Whole genome and transcriptome sequencing of lung cancer patients and cell lines at Genentech

  Version 1 Whole genome sequencing was applied to tumor and adjacent normal lung tissue in an individual non-small-cell lung cancer patient. We present an analysis of somatic changes identified throughout the tumor genome, including single-nucleotide variants, copy number variants, and large-scale chromosomal rearrangements. Over 50,000 high-confidence single-nucleotide variants were identified, revealing evidence of substantial smoking-related DNA damage as well as distinct mutational pressures within the tumor resulting in uneven distribution of somatic mutations across the genome. Version 2 Lung cancer is a highly heterogeneous disease in terms of both underlying genetic lesions and response to therapeutic treatments. We performed deep whole genome sequencing and transcriptome sequencing on 19 lung cancer cell lines and 3 lung tumor/normal pairs. Overall, our data show that cell line models exhibit similar mutation spectra to human tumor samples. Smoker and never-smoker cancer samples exhibit distinguishable patterns of mutations. A number of epigenetic regulators are frequently altered by mutations or copy number changes. A systematic survey of splice-site mutations identified over 100 splice site mutations associated with cancer specific aberrant splicing, including mutations in several known cancer-related genes. Differential usages of splice isoforms were also studied. Taken together, these data present a comprehensive genomic landscape of a large number of lung cancer samples and further demonstrate that cancer specific alternative splicing is a widespread phenomenon that has potential utility as therapeutic biomarkers.

  Study phs000299

• Mutational Signature and Transcriptomic Classification Analyses as the Decisive Diagnostic Tools for a Cancer of Unknown Primary with Neuroendocrine Differentiation

  PURPOSE: Cancer of unknown primary (CUP) is a group of metastatic tumors in which the standard diagnostic work-up fails to identify the site of origin of the tumor. The potential impact of precision oncology on this group of patients is large since their tumors might have actionable driver mutations that can provide treatment options otherwise not available for patients with these fatal cancers. This study investigated if comprehensive genomics analyses could inform on the origin of the tumor. PATIENT AND METHODS: Here we describe a patient whose tumor was misdiagnosed at least three times. Next-generation sequencing, a PDX mouse model and bioinformatics was used to identify an actionable mutation, predict resistance development to the targeted therapy, and to correctly diagnose the origin of the tumor. The Cancer Genome Atlas was used to benchmark the bioinformatics workflow. RESULTS: Despite the lack of a known primary tumor site and the absence of diagnostic immunohistochemical markers, the origin of the patient's tumor was established using the novel bioinformatics workflow. This included a mutational signature analysis of the sequenced metastases and comparison of their transcriptomic profiles to a pan-cancer panel of tumors from The Cancer Genome Atlas. We further discuss the strengths and limitations of the latter approaches in the context of three potentially incorrectly diagnosed TCGA lung tumors. CONCLUSION: Comprehensive genomics analyses could inform on the origin of tumors in patients suffering from CUP.

  Study EGAS00001003026

• Alzheimer's Disease Sequencing Project (ADSP)

  NOTICE OF CHANGE IN LOCATION FOR ALZHEIMER'S DISEASE SEQUENCING PROJECT (ADSP) GENETIC AND PHENOTYPIC DATA: ADSP whole exome and whole genome sequence data that are shared through dbGaP were mapped to the Genome Reference Consortium human genome GRCh37 (build 37). These data are from the Discovery Phase of the project (described below) and will continue to be available at this site. Please see the ADSP Design page for the complete study description. All data that are mapped to GRCh38 (hg38) are being shared through the NIA Genetics of Alzheimer's Disease Data Storage Site (NIAGADS) Data Sharing Service (DSS). For instructions on how access the ADSP Build 38 data that are shared through NIAGADS DSS, visit the Application Instructions page. STUDY DESCRIPTION FOR dbGaP BUILD 37 ADSP DATA: The overarching goals of the Alzheimer's Disease Sequencing Project (ADSP) are to: (1) identify new genomic variants contributing to increased risk of developing Alzheimer's Disease (AD), (2) identify new genomic variants contributing to protection against developing AD, and (3) provide insight as to why individuals with known risk factor variants escape from developing AD. These factors will be studied in multi-ethnic populations in order to identify new pathways for disease prevention. Such a study of human genomic variation and its relationship to health and disease requires examination of a large number of study participants and needs to capture information about common and rare variants (both single nucleotide and copy number) in well phenotyped individuals. Using existing samples from NIH funded and other studies, three NHGRI funded Large Scale Sequencing and Analysis Centers (LSAC) - Broad, Baylor, and Washington University - produced the DNA sequence data. Variant call data are being made available to the scientific community through NIH-approved data repositories. Statistical analysis of the sequence data is anticipated to identify new genetic risk and protective factors. The ADSP will conduct and facilitate analysis of sequence data to extend previous discoveries that may ultimately result in new directions for AD therapeutics. Analysis of ADSP data will be done in two phases. The Discovery Phase analysis (2014-2018) is funded under PAR-12-183. The entire Discovery dataset contains whole-genome sequencing data on 584 subjects from 113 families, and pedigree data for > 4000 subjects; whole exome sequencing data on 5096 cases 4965 controls; and whole exome sequence data on an additional 853 (682 Cases [510 Non-Hispanic, 172 Hispanic]), and 171 Hispanic Control subjects from families that are multiply affected with AD. The Replication Phase (2016-2021) analysis will be funded under RFA-AG-16-001 and RFA-AG-16-002 and is expected to include a combination of genotyping and sequencing approaches on at least 30,000 subjects. Targeted sequencing will be done by the LSACs. GRCh37 Data Releases The first ADSP data release occurred on November 25, 2013. It included the whole-genome sequencing data in BAM file format on 410 individuals. The second ADSP data release occurred on March 31, 2014, and included the whole-genome sequencing data in BAM file format for an additional 168 individuals. The third ADSP data release occurred on November 03, 2014 and included whole-exome sequencing data in BAM file format for 10,939 individuals. The fourth ADSP data release occurred on February 13, 2015 and included revised ethnic data for subjects with whole-exome sequencing data. The fifth ADSP data release occurred on July 13, 2015 and included whole-genome genotypes and updated phenotypes as well as changes to pedigree structures and sample IDs. The sixth ADSP data release occurred on December 8, 2015, and included whole-exome genotypes and updated phenotypes as well as changes to subject IDs. This seventh ADSP data release on April 12, 2016 includes: (1) WES and WGS SNV VCF files (2) WES and WGS Indel PLINK files ADSP Data Available through dbGaP: ADSP - Whole Genome Sequencing ADSP - Whole Exome Sequencing Comments DNA-Seq (BAM) n=578 n=10913 Sequence data available (plus n=38 replications w/out genotype data) Concordant SNV Genotypes (PLINK format) N/A n=10913 QC'ed genotypes that are concordant between the Atlas (Baylor's) and GATK (Broad's) calling pipelines (a subset of the consensus genotype set) Consensus Genotypes (PLINK and VCF format) n=578 n=10913 QC'ed genotypes that are concordant between Atlas and GATK pipelines as well as those that that were called uniquely by Atlas or GATK Concordant Indel Genotypes (PLINK format) n=578 n=10913 QC'ed genotypes that are concordant between the Atlas and GATK calling pipelines Phenotype Data n=4735 n=10913 Data of n=53 phenotype variables available (plus administrative data), including APOE genotype. WGS phenotypes include data of connecting family members. Please use the release notes provided by dbGaP to obtain detailed information about study release updates. The ADSP data portal provides a customized interface for users to quickly identify and retrieve files by covariates, phenotypes, and data properties such as sequencing facility or coverage. For more information about the ADSP study and the data portal, please visit https://www.niagads.org/adsp/.

  Study phs000572

• Immunoglobulin Heavy-Chain locus in Multiple Sclerosis (n=4)

  Peripheral-blood or monocyte DNA from two healthy donors and two individuals with multiple sclerosis were sequenced on a PromethION-2 Solo (P2 Solo) instrument using R10.4.1 flow-cells and the Ultra-Long DNA Sequencing Kit (SQK-ULK114). For each participant we provide FASTQ reads (on-target), and haplotype-resolved assemblies of the complete IGH locus (~1.3 Mb) in FASTA format.

  Dataset EGAD50000001517

• RNA sequencing data of pediatric TCF3::PBX1 acute lymphoblastic leukemia (set 1)

  The dataset includes RNA sequencing FASTQ files from a diagnostic tumor sample of one TCF3::PBX1 ALL patient (ALLT-335). NEBNext Ultra Directional RNA Library Prep Kit (New England Biolabs) was used in library preparation, and Globin-Zero Gold rRNA Removal Kit (Illumina) was utilized for rRNA removal. The diagnostic tumor sample was sequenced using Illumina Novaseq 6000, and the target sequencing depth was 21 Gb.

  Dataset EGAD50000002577

• RNA sequencing data of pediatric TCF3::PBX1 acute lymphoblastic leukemia (set 2)

  The dataset includes RNA sequencing FASTQ files from a diagnostic tumor sample of one TCF3::PBX1 ALL patient (ALLT-376). NEBNext Ultra Directional RNA Library Prep Kit (New England Biolabs) was used in library preparation, and TruSeq Stranded Total RNA Library Prep (Illumina) kit was utilized for rRNA removal. The diagnostic tumor sample was sequenced using Illumina Novaseq 6000, and the target sequencing depth was 21 Gb.

  Dataset EGAD50000002578

• RNA sequencing data of pediatric BCR::ABL1 acute lymphoblastic leukemia (set 1)

  The dataset includes RNA sequencing FASTQ files from a diagnostic tumor sample of one BCR::ABL1 ALL patient (ALLT-343). NEBNext Ultra Directional RNA Library Prep Kit (New England Biolabs) was used in library preparation, and Globin-Zero Gold rRNA Removal Kit (Illumina) was utilized for rRNA removal. The diagnostic tumor sample was sequenced using Illumina Novaseq 6000, and the target sequencing depth was 21 Gb.

  Dataset EGAD50000002579

• RNA sequencing data of pediatric KMT2A-rearranged acute lymphoblastic leukemia (set 3)

  The dataset includes RNA sequencing FASTQ files from a diagnostic tumor sample of one KMT2A-r ALL patient (ALLT-375). NEBNext Ultra Directional RNA Library Prep Kit (New England Biolabs) was used in library preparation, and TruSeq Stranded Total RNA Library Prep (Illumina) kit was utilized for rRNA removal. The diagnostic tumor sample was sequenced using Illumina Novaseq 6000, and the target sequencing depth was 21 Gb.

  Dataset EGAD50000002581

• RNA sequencing data of pediatric KMT2A-rearranged acute lymphoblastic leukemia (set 2)

  The dataset includes RNA sequencing FASTQ files from a diagnostic tumor sample of one KMT2A-r ALL patient (ALLT-355). NEBNext Ultra Directional RNA Library Prep Kit (New England Biolabs) was used in library preparation, and Ribo-Zero Magnetic Kit (Illumina) was utilized in rRNA removal. The diagnostic tumor sample was sequenced using Illumina Novaseq 6000, and the target sequencing depth was 21 Gb.

  Dataset EGAD50000002583