15041 results for "cancer studies using rna-seq"

in 40.40 milliseconds.

• RCC_HTA2.0_Reustle2022

  GeneChip HTA 2.0 data of primary renal cell carcinoma (RCC) related to Reustle et al., Clin Transl Med 12:2022 e883. Microarrays were normalized individually using the SCAN method from the R package SCAN.UPC (version 2.26.0, R version 3.6.1). Probe sets were summarized on the Entrez GeneID level using the annotation provided by BrainArray (version 23).

  Dataset EGAD00010002352

• Genetic Etiology of Heterotaxy

  To understand the genetic etiology of heterotaxy, patients with heterotaxy were consented and recruited, with blood drawn for DNA extraction and exome sequencing. Using the exome sequencing dataset obtained, rare coding sequence variants were identified.

  Study phs001691

• Spatial Dynamics of the Developing Human Heart

  68 paired-end raw FASTQ files obtained from 38 tissue sections across 16 hearts, spanning embryonic human heart development between 5.5 and 14 postconceptional weeks. Some libraries were re-sequenced for better coverage. The tissue sections were processed using the 10x Genomics Visium Gene Expression kit, and libraries were paired-end sequenced using Nextseq2000 (Illumina).

  Dataset EGAD50000001615

• Establishment of iPS cells from Japanese healthy volunteers

  We performed whole exome sequencing of Japanese volunteers. We established iPSCs from those volunteers, and the iPSCs were deposited to Riken Bioresource Bank. The whole exome sequencing were performed using their PBMCs.

  Study JGAS000287

• Genome-Wide Bisulfite Sequencing of Urinary Cell-Free DNA

  The current sequencing dataset consists of 85 bisulfite sequencing data files (Fastq files) of human cell-free urine DNA samples. These extracted cfDNA samples were then constructed into DNA libraries using the KAPA HTP Library Preparation Kit (Kapa Biosystems) with bisulfite modification using the EpiTect Bisulfite Kit (Qiagen) and subsequently sequenced on the Nextseq500 platform (Illumina).

  Dataset EGAD50000001902

• The exploratory research of diagnositic biomarker and therapeutic targets of renal cell carcinoma.

  We search more effective markers, which predict worse prognosis in patients with RCC and become targets for therapy of RCC, using tissues of patients with RCC by global transcriptional analysis.

  Study JGAS000149

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

  The dataset includes FASTQ and BAM files from diagnostic and matched remission (control) samples of three hyperdiploid ALL patients (ALLT-329, ALLT-347, ALLT-356). Sequencing libraries were made using NEB Next® Ultra™ DNA Library Prep Kit. Both diagnostic (60x) and remission (30x) samples were sequenced using Illumina HiSeq X.

  Dataset EGAD50000002425

• Project MinE Illumina Infinium HumanMethylation450 (450k) BeadChip data on 2,790 Dutch whole blood samples, including 1,761 ALS patients of which 119 are known carriers of the C9orf72 repeat expansion.

  This dataset includes IDAT files from 2,790 blood samples. The samples were profiled using the Illumina Infinium HumanMethylation450 (450k) BeadChip.

  Study EGAS00001004587

• WholeGenomeSeq-EGAS00001001306

  Whole Genome sequencing. 2 μg of genomic DNA from each sample was used for the construction of two short-insert paired-end sequencing libraries. Both types of libraries were sequenced in paired-end mode on Illumina GAIIx (2 × 151 bp) using Sequencing kit v4 or Illumina HiSeq2000 (2x101 bp) using TruSeq SBS Kit v3.

  Dataset EGAD00001001466

• DNA methylation-based classification of sinonasal tumors [DNA sequencing]

  This dataset contains raw exome sequencing data from nine sinonasal undifferentiated carcinoma FFPE samples and matched normal tissue that were assigned to a shared epigenetic class using DNA methylation-based classification. They were analyzed using the Twist Human Core Exome Plus Kit (Twist Bioscience) on a NovaSeq 6000 sequencer.

  Dataset EGAD00001009668

• cfMeDIP data for 14 Barrier samples

  We analyzed the cell free DNA methylomes using 14 plasma samples from patients with mCRPC in the Barrier cohort. Methylation was profiled using the methylated DNA immunoprecipitation coupled to next generation sequencing (MeDIP) technology.

  Dataset EGAD00001008712

• EGAD00010000600

  Prostate Adenocarcinomas samples using 450K

  Dataset EGAD00010000600

• Reproducibility of 10x Genomics single cell RNA sequencing method in the immune cell environment

  Study EGAS00001005905

• Human small intestinal macrophages whole transcriptome

  RNA sequencing data of human small intestinal macrophage subtypes

  Dataset EGAD00001002744

• Colorectal cancer functional annotation - Micro-C

  Ultra high resolution Micro-C data from multiple colorectal cancer cell lines

  Study EGAS50000000206

• Pancreatic Cancer NGS WGS data

  Whole genome sequencing data for Pancreatic Cancer Samples exploring the tandem duplicator phenotype

  Study EGAS50000001078

• Division of Cancer Evolution National Cancer Center Research Institute Data Access Committee

  Data Access Committee for data from Division of Cancer Evolution, National Cancer Center Research Institute

  Dac EGAC50000000737

• Mutational anysis of breast cancer stem cells

  Exome sequences of breast cancer have been investigated for many patients. Recently it has been shown that there are intra-heterogeneity in tumor tissues. When the tumor cells were sequenced in bulk condition, only the major populations��� (clones���) mutations will be detected. Based on cancer stem theory, each populations��� cells are derived from each cancer stem cells, which their numbers are not so different among different clones. Here, we separated cancer cells into cancer stem cells and non-cancer stem cells exploiting cancer stem cell specific surface markers. By comping two groups��� mutation, we identified mutations, which were only detected in stem cell population. These mutations could be the mutations in cells of small size populations, and maybe the important mutations to understand the heterogeneity of tumor tissues, progression, and/or prediction for the outcome to therapies.

  Study JGAS000304

• WGS-Lung Cancer sample 30 pair

  This study includes 30 paired samples of Korean Lung Cancer paitients. 30 Lung Cancer samples are paired with each normal(Saliva derived for control) sequencing data.The results of this WGS study were analyzed by Mutect and GATK for ranking germline variants and cancer variants to make mutational profile matrix.

  Study EGAS00001001474

• Genomic analysis of Japanese gastric cancer (345 gastric cancers of NCC)

  As a contribution to the International Cancer Genome Consortium, whole exome sequencing of 345 Japanese gastric cancer (345 gastric cancers of NCC) with various histological subtypes have been conducted. This study aims to identify unique and common driver genes and molecular subtypes in Japanese gastric cancer.

  Study EGAS00001002884

• MCO colorectal cancer genomics at UNSW

  This dataset contains DNA sequencing data from 95 colorectal cancer and matched-normal samples. The dataset contains targeted deep sequencing of selected regulatory elements in 95 cancer and matched-normal samples, and data for one sample that was additionally whole-genome sequenced (cancer and matched-normal).

  Study EGAS00001003450

• Primary human hepatocyte ATAC-seq

  Profiling the chromatin accessibility landscape of cultured primary human hepatocytes (PHH) from three female and three male adult, non-diabetic donors.

  Dataset EGAD50000001751

• β-catenin ChIP sequencing in HCC models.

  This dataset contains ChIP sequencing data for β-catenin, H3K27ac and H3K27me3 from three HCC cell lines and five tumour organoids under normal conditions and oleic acid treatment.

  Dataset EGAD50000001816

• Bulk exome sequencing of primary GBM - SF 10282

  We performed bulk exome-seq on a primary GBM and a blood sample from SF10282

  Dataset EGAD00001002275

• Bulk exome sequencing of primary GBM - SF 10345

  We performed bulk exome-seq on a primary GBM and a blood sample from SF10345

  Dataset EGAD00001002273

• scATAC-seq dataset of A cycling, progenitor-like cell population at the root of atypical teratoid rhabdoid tumor subtype differentiation trajectories

  Study describing the differentiation trajectory...

  Dataset EGAD00001015546

• ChIP-Seq of human stimulated and cultured CD4+ Treg cells

  This dataset includes whole genome sequence data for ChIPmentation assays (18 H3K4me3, 20 H3K27ac and 3 input samples) of human stimulated and cultured CD4+ Treg cells.

  Dataset EGAD00001005816

• scRNA-seq dataset of A cycling, progenitor-like cell population at the root of atypical teratoid rhabdoid tumor subtype differentiation trajectories

  Study describing the differentiation trajectory...

  Dataset EGAD00001015545

• Activation of Wnt/β-catenin signalling by mutually exclusive FBXW11 and CTNNB1 hotspot mutations drives salivary gland basal cell adenoma - RNA

  Wnt signalling must be 'just right' to promote tumour growth. Basal cell adenoma (BCA) and basal cell adenocarcinoma (BCAC) of the salivary gland are rare tumours that can be difficult to distinguish from each other and other salivary gland tumour subtypes. Due to their rarity, the genomic profiles of BCA and BCAC have not been explored. Using whole-exome and transcriptome sequencing of BCA and BCAC cohorts, we identify a novel recurrent FBXW11 missense mutation (p.F517S) in BCA, that was mutually exclusive with the previously reported CTNNB1 p.I35T gain-of-functon (GoF) mutation. These driver events collectively accounted for 94% of BCAs. In vitro, mutant FBXW11 had a dominant negative affect, characterised by defective binding to β-catenin and the accumulation of β-catenin in cells. This was consistent with the nuclear expression of β-catenin observed in BCA cases harbouring the FBXW11 p.F517S mutation and activation of the Wnt/β-catenin pathway and defines a novel mechanism of Wnt pathway control. The genomic profiles of BCAC were distinct from BCA, with hotspot DICER1 and HRAS mutations and putative driver mutations affecting PI3K/AKT and NF-κB signalling pathway genes. A single BCAC, which may represent a malignant transformation of BCA, harboured the recurrent FBXW11 mutation. These findings have important implications for the diagnosis and treatment of BCA and BCAC, which, despite histopathologic overlap, may be unrelated entities.

  Dataset EGAD00001015366

• BRCA Mutation Status Shapes the Microenvironment of Pancreatic Adenocarcinoma

  This study was established in order to address how the stromal landscape is influenced by BRCA-mutated and BRCA Wild-type (WT) pancreatic ductal adenocarcinoma (PDAC). A primary cohort of 12 PDAC patients (7 BRCA-WT and 5 germline BRCA-mut) was analyzed by laser-capture microdissection, RNA-sequencing and multiplexed immunofluorescence.

  Study phs002994

• T-cell receptor repertoire profiling (PBMC)

  This study assessed the TCR repertoire in peripheral blood from patients before, during and after neoadjuvant chemoimmunotherapy. TCR beta chain sequences in RNA from peripheral blood were amplified with the OncomineTM long read assay, templated and sequenced. TCR metrics such as clonality, evenness and diversity were assessed in relation with response metrics.

  Study EGAS50000001137

• T-cell receptor repertoire profiling (FFPE tissue)

  This study assessed the TCR repertoire in tumor tissue from NSCLC patients before, during and after neoadjuvant chemoimmunotherapy. TCR beta chain sequences in RNA from FFPE tissue were amplified with the OncomineTM short read assay, templated and sequenced. TCR metrics such as clonality, evenness and diversity were assessed in relation with response metrics.

  Study EGAS50000001138

• Transcriptomic analysis of hiPSC-derived vascular cells from CADASIL and isogenic control patient lines

  Bulk-RNA sequencing from hiPSC-derived cells (hiPSC; Endothelial Cells; Neural Crests Cells; Vascular Smooth Muscle Cells) from CADASIL patient lines (n=3) and respective isogenic-controls (n=3). CADASIL is a hereditary brain small vessel disease caused by pathogenic variants in the NOTCH3 gene, which lead to deposits of NOTCH3 protein in the walls of small arteries. This causes pathological vessel wall changes including degeneration of vascular smooth muscle cells. To investigate the impact of pathogenic NOTCH3 variants in hiPSC and differentiated cells we performed a bulk-RNA sequencing.

  Dataset EGAD50000002181

• Analysis_of_resistance_to_PLX4032

  We have collected material from a patient who had BrafV600E mutant melanoma that wastreated with PLX4032. We have germline DNA from the patient and DNA and RNA fromdistinct lesions before and after treatment with PLX4032. We would like to exome sequencethese samples to gain a snap shot of the mechanisms of resistance that are operative.

  Study EGAS00001000415

• Hypothalamic transcriptome in Prader-Willi syndrome

  Transcriptional analysis of brain tissue from people with molecularly defined causes of obesity may highlight novel disease mechanisms and therapeutic targets. Prader-Willi syndrome (PWS) is a genetic obesity syndrome characterised by severe hyperphagia. We performed RNA sequencing of the hypothalamus from 4 individuals with PWS and 4 age-matched controls.

  Study EGAS00001002901

• Oncogenic gene fusions in primary colon cancers

  This study represents RNA-sequencing data from 278 primary colon cancers obtained from fresh-frozen tumor sections. The project goal was to identify novel oncogenic gene fusions in these data. In addition, we studied the detected gene fusions at the molecular level and defined their effects on downstream pathways.

  Study EGAS00001002197

• The_Transcriptome_of_PLX4032_resistance

  We have collected material from a patient who had BrafV600E mutant melanoma that wastreated with PLX4032. We have germline DNA from the patient and DNA and RNA fromdistinct lesions before and after treatment with PLX4032. We have transcriptome sequenced these samples to obtain a snap shot of the mechanisms of resistance that are operative.

  Study EGAS00001000413

• Whole-genome and transcriptome sequencing of tumor-stage mycosis fungoides

  Mycosis fungoides (MF) is the most common cutaneous T-cell lymphoma (CTCL), a group of malignancies derived from skin-homing malignant T cells. We subjected tumor biopsies from MF patients to whole-genome sequencing and RNA-sequencing to investigate genomic alterations and deregulated gene expression in the disease.

  Study EGAS00001002860

• The genomic landscape of primary cutaneous anaplastic large cell lymphoma (pcALCL)

  Primary cutaneous anaplastic large cell lymphoma (pcALCL) is the second most common variant of cutaneous T-cell lymphoma. We subjected tumor biopsies from patients with pcALCL to whole-genome sequencing, whole-exome sequencing and RNA-sequencing to investigate genomic alterations and deregulated gene expression in the disease.

  Study EGAS00001004429

• Natural Killer Cell Plasticity During IL-15-driven Homeostatic Proliferation

  Here we performed single-cell RNA sequencing to address repertoire stability and subset plasticity during IL-15 driven homeostatic proliferation. Sorted NK cell subsets representing discrete stages of NK cell differentiation are compared with the corresponding subsets after proliferation and further sorted into two subsets depending on the rate of proliferation.

  Study EGAS00001003946

• Transcriptomic signatures of CD4+ T cells from visceral leishmaniasis (VL) patients

  Bulk RNA-sequencing was performed on CD4+ T cells isolated from the blood of visceral leishmaniasis patients (n = 12) and endemic controls (EC; n = 12). CD4+ T cells were obtained by magnetic-activated cell sorting (MACS). Alterations in the transcripts of T helper (Th) cells during infection were identified.

  Study EGAS00001004152

• Facioscapulohumeral dystrophy transcriptome signatures correlate with different stages of disease and are marked by different MRI biomarkers

  This project includes RNA-sequencing data from human FSHD and control skeletal muscle biopsies. This project includes data from 28 FSHD patients (total 37 samples, including vastus lateralis and tibialis anterior muscles) and 12 control individuals (total 24 samples, including vastus lateralis and tibialis anterior muscles).

  Study EGAS00001005782

• Epithelioid sarcoma dataset

  This deposit consists of DNA and RNA sequencing data from 32 EPS patients. 28 samples had tumor DNA sequencing data. 2 had matched normal sequencing data. 27 samples had tumor RNA sequencing data.

  Dataset EGAD00001008515

• RNA sequencing of CD8 T cells from melanoma patients prior to and during checkpoint immunotherapy and untreated healthy controls

  We are interested in inter-individual variation in transcriptional response to immune checkpoint blockade. We have analysed poly A purified RNA expression from CD8 T cells (297 transcriptomes in total) isolated from metastatic melanoma patients (n=106) prior to and during treatment with either single agent (Pembrolizumab) or combination (Ipilimumab/ Nivolumab) immune checkpoint blockade. We compare expression at different stages of treatment and additionally contrast this with that from healthy controls (n=68).

  Dataset EGAD00001005973

• Mapping the Evolution of T Cell States During Response and Resistance to Adoptive Cellular Therapy

  We investigated single T cell transcriptional states that define donor lymphocyte infusion (DLI) response and resistance from cryopreserved bone marrow mononuclear cells from 15 patients with relapsed chronic myeloid leukemia (CML) after allogeneic hematopoietic stem cell transplant. By integrating bulk ATAC-seq data from sorted T cell populations from these bone marrow samples, we also defined gene regulatory networks that underlay these clusters.

  Study phs002877

• DAC for a single-cell multi-omic atlas of nodal B-cell non-Hodgkin lymphomas

  Nodal B-cell non-Hodgkin lymphomas (B-NHL) are a clinically diverse set of cancers thought to originate from distinct stages of B-cell maturation. To characterize intratumor heterogeneity across B-NHL entities, we performed CITE-Seq (cellular indexing of transcriptomes and epitopes) on 51 lymph node samples including mantle cell lymphoma (MCL, n = 8), follicular lymphoma (FL, n = 12), germinal center (GCB, n = 5) or activated B-cell (non-GCB/ABC, n = 7) diffuse large B-cell lymphoma (DLBCL) and marginal zone lymphoma (MZL, n = 11) tumors, in addition to non-malignant reactive lymph nodes (rLN, n = 8). We also performed 5 prime scRNA-seq with immune receptor profiling for 11 of these samples (2 rLN, 2 MCL, 3 FL, 2 DLBCL, and 2 MZL).

  Dac EGAC50000000226

• SUM-seq data for Primary T-cells differentiated to helper subtypes

  Briefly, naive CD4+ T cells were isolated from PBMCs obtained from buffy coats from three healthy human donors, and differentiated into Th0, iTreg, Th2, Th1, Th17, and IFN-β-activated subsets. This allowed us to study the differentiation of naive CD4+ T cells into distinct helper subsets under the influence of a specific cytokine environment. Following 5 days of differentiation, T cells were left unstimulated or re-stimulated with phorbol 12-myristate 13-acetate (PMA) and ionomycin to assess their functional responses. Thus, this SUM-seq experiment consisted of 36 multiplexed conditions (3 donors x 6 stimulations x with/without re-stimulation). Single-cell chromatin accessibility and gene expression data is provided as demultiplexed fastq files.

  Dataset EGAD50000001204

• cfMeDIP-seq for 18 patients with pleural mesothelioma

  The dataset contains cfMeDIP-sequencing data (bam files) for 18 plasma samples from pleural mesothelioma patients. The libraries were prepared according to the published protocol (Shen, S. Y., Burgener, J. M., Bratman, S. V. & De Carvalho, D. D. Preparation of cfMeDIP- seq libraries for methylome profiling of plasma cell-free DNA. Nat. Protoc. 14, 2749–2780 (2019)). Whole genome sequencing (WGS) was performed for pre-made libraries on NovaSeq X Plus with a 150 paired-end strategy. Low-quality reads and adapters were removed with Trim Galore version 0.6.6 (https://www.bioinformatics.babraham.ac.uk/projects/trim_galore). The trimmed reads were aligned to hg38 with Bowtie2 version 2.3.4.3. SAMTools version 1.9 was used to convert the SAM alignment files to BAM files, sort and index reads, and remove duplicates.

  Dataset EGAD50000002126

• ATAC_SEQ_MAIN___PHASE_1

  This is a study to test ATAC-seq protocols. CD4+ and CD8+ cells have been obtained from three different anatomical compartments. We aim to assay open-chromatin regions across these cells and perform comparative analyses.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/

  Study EGAS00001000947

• GEX CITE-Seq performance dataset

  To understand the impact of enzymatic treatments on gene expression and epitope preservation on major immune cell populations, skin dissociation (SkinD) and solid soft tumor dissociation (TumorD) were tested on three healthy PBMC samples in triplicate (D1, D2, D3), against an untreated control. CITE-seq performance was assessed on a solid biopsy cohort of 11 samples (5 healthy skin samples, 3 primary melanoma samples, 3 melanoma metastasis samples) as well as on a liquid biopsy PBMC cohort consisting of three healthy donors and three immunotherapy-treated melanoma patients. This dataset contains the GEX data for each sample. Data is provided in the form of pooled BAM files. Linkage between samples, BAM files and hashtags is provided in a separate linkage file.

  Dataset EGAD00001008418

• ADT/SPEX CITE-Seq performance dataset

  To understand the impact of enzymatic treatments on gene expression and epitope preservation on major immune cell populations, skin dissociation (SkinD) and solid soft tumor dissociation (TumorD) were tested on three healthy PBMC samples in triplicate (D1, D2, D3), against an untreated control. CITE-seq performance was assessed on a solid biopsy cohort of 11 samples (5 healthy skin samples, 3 primary melanoma samples, 3 melanoma metastasis samples) as well as on a liquid biopsy PBMC cohort consisting of three healthy donors and three immunotherapy-treated melanoma patients. This dataset contains the ADT/SPEX data for each sample. Data is provided in the form of pooled BAM files. Linkage between samples, BAM files and hashtags is provided in a separate linkage file.

  Dataset EGAD00001008419

• UK Biobank Access - http://www.ukbiobank.ac.uk/using-the-resource/

  Dac EGAC00001000641

• DEHNRUKE

  Methylation data using 450K

  Dataset EGAD00010001294

• CYTOSCANHD_Genotyping

  samples using Affymetrix CYTOSCANHD

  Dataset EGAD00010000921

• README-for-EGAS00001004349-linking-HIPO-K09R-RNA-files

  Dataset EGAD00001006785

• RNA-sequençing of 21 inflammatory hepatocellular adenomas and 1 non-tumoral sample

  Dataset EGAD00001005284

• ADARIO Dataset

  RNA editing analyses of BRCA-isogenic cell lines and patient-derived xenografts (PDX)

  Dataset EGAD50000000739

• Adrenal scRNA sequencing data access

  Raw sequencing datasets for manuscript "Hybrid untargeted and targeted RNA sequencing facilitates genotype-phenotype associations at single-cell resolution".

  Dac EGAC50000000869

• The landscape of cancer genes and mutational processes in breast cancer

  The landscape of cancer genes and mutational processes in breast cancer

  Dataset EGAD00001000133

• Whole exome and transcriptome analysis of UV-exposed epidermis and carcinoma in situ reveals early drivers of carcinogenesis

  Squamous cell carcinoma in situ (SCCIS) is a prevalent precancerous lesion that can progress to cutaneous squamous cell carcinoma (cSCC). Although SCCIS is common, its pathogenesis remains poorly understood. To better understand SCCIS development, we performed laser-captured microdissection of human SCCIS and adjacent epidermis to isolate genomic DNA and RNA for next generation sequencing. Whole exome sequencing (WES) identified UV-signature mutations in multiple genes including Notch 1-3 (GeneID:4851, GeneID:4853, GeneID:4854) in the epidermis and SCCIS and oncogenic TP53 (GeneID:7157) mutations in SCCIS. Novel gene families, including SCHLAFEN genes, contained UV/oxidative-signature disruptive (UVD) epidermal mutations that manifested positive selection in SCCIS. The frequency and distribution of NOTCH and TP53 mutations indicate that NOTCH mutations may precede TP53 mutations. RNA sequencing identified 1166 differentially expressed genes; the top 5 enriched GO biological processes included: 1) immune response, 2) epidermal development, 3) protein phosphorylation, 4) regulation of catalytic activity, and 5) cytoskeletal regulation. The NEURL1 ubiquitin ligase, which targets Notch ligands for degradation, was upregulated in SCCIS. Neuralized 1 protein was found to be elevated in SCCIS suggesting that increased levels could represent a novel mechanism for downregulating Notch during UV-induced carcinogenesis. The data from DNA and RNA sequencing of epidermis and SCCIS provide insights regarding SCCIS formation.

  Study phs002019

• DUX4 activates novel intergenic transcripts and isoforms in a tissue-specific context

  DUX4, a transcription factor driving zygotic genome activation during the embryonic cleavage stage in mammals, regulates the expression of genic and non-genic elements and modulates chromatin accessibility. Its misexpression in skeletal muscle causes Facioscapulohumeral muscular dystrophy (FSHD). The sporadic expression of DUX4 in FSHD muscle and the limitations of short-read RNA sequencing challenge, however, a comprehensive grasp of its consequences on the muscle transcriptome. Here, leveraging full-length isoform RNA sequencing with short-read RNA sequencing on DUX4-inducible myoblasts, we elucidated DUX4-induced transcriptomic changes within a myogenic context. DUX4 yields a complex transcriptome featuring numerous unannotated isoforms from known and novel loci. Moreover, we observed distinct isoform usage of DUX4 target genes between myogenic and embryonic cleavage states highlighting the distinct differences between DUX4 transcription factor activity in skeletal muscle and during the cleavage stage. We also identified ~1,400 unannotated intergenic isoforms predominantly originating from repetitive elements such as LTRs, LINEs, and SINEs. Integration with available datasets delineates the transcriptional and epigenetic landscape of these loci across myogenic and embryonic backgrounds. Like the cell type-specific isoform production, the usage of DUX4 binding sites at these intergenic loci is in part cell type-specific. Collectively, these findings demonstrate substantial and context-specific transcriptomic alterations induced by DUX4 further enriching our understanding of DUX4-induced muscle pathology.

  Study EGAS50000000503

• Defining T cell States Associated with Response to Checkpoint Immunotherapy in Melanoma

  Checkpoint blockade therapy using antibodies targeting CTLA4, PD1 or PDL1 have changed the way cancer patients with advanced disease are being treated, as evident by their FDA approval in a wide variety of malignancies, and their ability to induce high response rates when compared to conventional therapies (e.g. chemotherapy). However, even in melanoma, despite the high response rate, most patients are refractory to therapy or acquire resistance in 10-12 months. To identify key immunological elements coupled with response or resistance to checkpoint immunotherapy, we performed an unbiased analysis on 16,291 CD45+ immune cells from 32 patients (48 samples) treated with checkpoint therapy (anti-PD1=37; anti-PD1/CTLA4=11), using single cell transcriptomics. Initial unsupervised clustering of all CD45+ cells identified 11 clusters. When examining the association of these clusters with clinical outcome, we found that two clusters (B-cells, p=0.005; memory T-cells, p=0.03) were significantly enriched in responder lesions while 4 clusters (monocytes/macrophages, p=0.003; dendritic cells, p=0.015; exhausted CD8+ T-cells, p=0.005; and exhausted/cell-cycle lymphocytes, 1.3x10-5) are enriched in non-responder lesions. Next, by leveraging our unbiased single cell approach, we identified not only clusters but also specific markers associated with either responder lesions (PLAC8, LTB, LY9, SELL, TCF7, IGKC and CCR7) or non-responder ones (CCL3, CD38, HAVCR2, ENTPD1 and WARS), many of which were not previously reported to be associated with clinical outcome to checkpoint therapy. Due to the importance of CD8+ T-cells in controlling tumors, the significant association of T-cell states with clinical outcome, and their high abundance in melanoma tumors, we next focused our analysis on CD8+ T-cells and identified 2 main clusters CD8_G (with increased expression of genes linked to memory) and CD8_B (enriched for genes linked to cell dysfunction), that were significantly enriched in responder (CD8_G, p=1.4x10-6) and non-responder (CD8_B, p=0.005) lesions, respectively. Since cells with both states coexist in each of the responder and non-responder lesions, we decided to calculate the ratio between the number of cells in these 2 clusters and observed a significant separation between responders (CD8_G/CD8_B>1) and non-responders (CD8_G/CD8_B<1) when looking at all samples, baseline or post samples separately. Similar results were detected when looking at the expression of a single transcription factor, TCF7, in CD8 T-cells in an independent cohort (n=43) using a simple immunofluorescence assay. Additionally, we validated the identity and function of some of the newly identified cell states as well as their epigenetic landscape, and found that cells expressing the inhibitory molecules CD39 and TIM3, on top of being enriched in non-responder lesions, are likely to play a crucial role in T-cell exhaustion in melanoma. Collectively, our study provides extensive unbiased data in human tumors for discovery of predictors and therapeutic targets to checkpoint immunotherapy.

  Study phs001680

• Blood Somatic Mutations in TCGA Donors Suffering from Solid Tumors

  Blood somatic mutations identified across 8,530 solid tumor patients in TCGA cohort. We reasoned that low-coverage whole-genome sequencing of blood samples routinely carried out in cancer genomics projects may be repurposed to detect clonal hematopoiesis (CH). Thus, inspired by a previous approach to identify early mutations in the development of the hematopoietic system, we implemented a pipeline to systematically carry out this "reverse" somatic mutation calling on the paired blood/tumor samples. Blood somatic mutations were called using a 'reverse' approach, in which the tumor sample taken from each patient was used as control of their germline genome. Blood somatic mutations are thus detected as variants in the blood (with respect to the human reference genome) that are absent in the tumor sample. The variant calling was carried out in our in house cluster on downloaded blood/tumor BAM files. The matched blood and tumoral BAM files -- masked and deduplicated using GATK -- of 8,530 whole-exome patients were obtained as described above. The variant calling was carried out using Strelka2 (employing default parameters) with the blood sample as the tumoral input and the tumor sample as control (reverse calling). All variants with two or more supporting reads matching the caller PASS filter and with VAF<0.5 were kept. Mutations in lowly mappable regions as defined by the DUST algorithm (k=30) and UMAP68 (36-kmers) were excluded. Contiguous variants were merged into double-base substitutions. Variants with greater frequency across the cohorts than the DNMT3A R882H or JAK2 V617F hotspot in a cohort-specific Panel of Normals and in gnomAD v2.1 were removed. This was equivalent to discarding variants present in these datasets with an allele frequency greater than 0.008 in PoN TCGA and 0.0003 in gnomAD v2.1. Additionally, common SNPs as defined by the dbSNP 151 Common UCSC track and dbSNP were excluded. Mutations within segmental duplications, simple repeats and masked regions as defined in UCSC tracks were also removed. Finally, samples with the mutation count above the 97.5 percentile of the mutation burden across the cohort were deemed unreliable and excluded for further analyses. We call the set of variants obtained after the application of these filters the full set. A more conservative subset of somatic mutations was generated from the full set of blood somatic mutations. To this end, we applied MosaicForecast, a software designed to phase mutations to polymorphisms with the aim of identifying somatic mutations in a small number of cells and also predict mosaicism for the unphased ones with a random forest classifier. As a result, we obtained a subset of mosaic-phased mutations, and a subset of mutations likely to be somatic (mosaic set).In order to obtain access to this study, please first obtain access to TCGA study (phs000178).

  Study phs002867

• 3q-capture DNA sequencing of primary AMLs with 3q26 rearrangements

  This dataset contains DNA sequencing of the chromosome 3q region in 28 primary AML cases with 3q26 rearrangements (3q26-rearranged AML). Genomic DNA was fragmented using the Covaris shearing device (Covaris), and sample libraries were assembled following the TruSeq DNA Sample Preparation Guide (Illumina). After ligation of adapters and an amplification step, target sequences of chromosomal regions 3q21.1-q26.2 were captured using custom in-solution oligonucleotide baits (Nimblegen SeqCap EZ Choice XL). The design of target sequences was based on the human genome assembly hg19: chr3q21.1:126036241-130672290 - chr3q26.2:157712147-175694147. Amplified captured sample libraries were paired-end sequenced (2x100 bp) on the HiSeq 2500 platform (Illumina) and aligned against the hg19 reference genome using the Burrows-Wheeler Aligner (BWA).

  Dataset EGAD00001006820

• Shotgun metagenome sequencing of saliva samples using PromethION

  Using PromethION, we conduct shotgun metagenome sequencing of human saliva, where both bacteria and bacteriophages are densely living, to study both microbiome and virome. We aim to explore, for example, relative abundance of bacteira and bacteriophages, distribution of contig lengh. types of phages and prophages, frequency of novel phages revealed by the long-reads and their taxonomic classification, and characteristics of genes encoded by the phages.

  Study JGAS000186

• Liver CD14+CD8+ T cells scRNAseq dataset

  Sorted single CD8+T cells expressing CD14 from human liver for SMARTSeq2. Livers processed: Kucykowicz et al STAR Prot 2022:pubmed.ncbi.nlm.nih.gov/35516846/ Published: Pallett et al Nature 2022 Tissue CD14+CD8+T-cells are reprogrammed by myeloid cells and modulated by LPS A modified SMART-seq2 protocol was performed on the single flow cytometry sorted-cells as previously described58. After cDNA generation, libraries were prepared (384 cells per library) using the Illumina Nextera XT kit (Illumina). Each library was sequenced to achieve a minimum depth of 1-2 million raw reads per cell using an Illumina HiSeq 4000 using v. 4 SBS chemistry to generate 75-bp paired-end reads.

  Dataset EGAD00001009831

• UCSF WCDT WGS/WGBS mCRPC

  This dataset contains 29 paired FASTQ files from whole-genome bisulfite sequencing (WGBS) assay performed on mCRPC tumors. Sequencing was performed using 150nt paired reads generated by a Novaseq 6000 instrument. It also contains whole-genome sequencing bam files aligned to hg38 using BWA from 36 patients, with tumor and matched tumor-adjacent normal samples. Sequencing was generated using HiSeq X Ten.

  Dataset EGAD00001009505

• ICGC PanCancer Analysis of Whole Genomes

  The Pancancer Analysis of Whole Genomes (PCAWG) study is an international collaboration to identify common patterns of mutation in more than 2,800 cancer whole genomes from the International Cancer Genome Consortium. Building upon previous work which examined cancer coding regions (Cancer Genome Atlas Research Network, The Cancer Genome Atlas Pan-Cancer analysis project, Nat. Genet. 2013 45:1113), this project is exploring the nature and consequences of somatic and germline variations in both coding and non-coding regions, with specific emphasis on cis-regulatory sites, non-coding RNAs, and large-scale structural alterations.

  Study EGAS00001001692

• WTCCC case-control study for Hypertension - Combined Controls

  WTCCC genome-wide case-control association study for Hypertension (HT) using six disease collections together with the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000010

• SCLC

  The aim of this study is to use sequence data generated from 500 bp paired end reads using the Illumina platform to characterise the breakpoints of chromosomal translocations, amplifications and deletions at high resolution (to the bp).

  Study EGAS00001000009

• Saliva Microbiota of Finnish children from the PANIC study

  Saliva microbiota of 407 participants of PANIC study, is profiled with 16S rRNA gene sequencing (regions V3-V4). Amplification was performed using the TruSeq-switched tail amplicons. The sequencing was performed using the 2 × 301 base-pair on the Illumina MiSeq PE300 platform. Data includes information on sex, age, and caries status of participants. File format is fastq.gz.

  Dataset EGAD50000000989

• Picuris Pueblo oral history and genomics reveal continuity in US Southwest

  Following the decision of Picuris Pueblo to study their population history using DNA, this project generated 16 ancient and 13 present-day genomes from the Pueblo, spanning 1,000 years of history.

  Study EGAS50000000855

• Comprehensive analysis of interaction between human gene expression and environmental metagenomes.

  WGS, 10x scRNA, 10X TCR, 10X BCR and CyTOF analyses were performed using blood samples collected from healthy volunteers aged 18 years or older who worked or lived in the Kashiwa-no-ha area.

  Study JGAS000321

• 419 Japanese healthy control

  Genotypes of 419 Japanese healthy individuals genotyped by using of SNP arrays (Genome-Wide Human SNP Array 6.0 and Axiom Genome-Wide ASI 1 Array). CEL files and CHP files are included in this data set.

  Study JGAS000120

• Whole exome sequencing variant data for Mendelian disorders cohort

  This dataset contains whole exome sequencing variant data (VCF files) from individuals with suspected Mendelian disorders, including sickle cell disease, muscular dystrophy, haemophilia, and Fanconi anemia. Variant calling was performed using the Illumina DRAGEN pipeline, with downstream variant prioritisation conducted using the Zi-Mendelian bioinformatics pipeline. The dataset supports research into rare genetic diseases and genomic variation in African populations.

  Dataset EGAD50000002453

• Enhanced reduced representation bisulfite sequencing (eRRBS) on 45 multiple myeloma samples and 3 normal plasma cell

  Enhanced reduced representation bisulfite sequencing (eRRBS) on 45 multiple myeloma samples and 3 normal plasma cell. Libraries were sequenced on a HiSeqTM4000 Illumina machine using 75bp paired-end reads

  Study EGAS00001004348

• SNP array study in Autism Spectrum Disorder patients

  The aim of this study was to investigate two ancestral inversions (inv17q21.31 and inv8p23.1) in Autism Spectrum Disorder (ASD) patients. We have performed SNP array in order to genotype these inversions using the package scoreInvHap.

  Study EGAS00001005606

• Characterization of Arabian Peninsula whole exomes

  We conducted whole exome sequencing (using the SureSelect Human All Exon V5 + UTRs target enrichment kit) of 90 individuals from AP (23 from Saudi Arabia, 24 from Yemen, 24 from Oman and 19 from UAE).

  Study EGAS00001006487

• CGH Array

  DNA samples were extracted from peripheral blood lymphocytes using commercially available kit (Puregene Core Kit A, Qiagen) according to manufacturer's protocol. Agilent SurePrint G3 Human CGH Microarray 180K platform was used for screening of copy number aberrations (CNAs) using array-CGH protocol recommended by manufacturer (Agilent Technologies), data mining and interpretation of array-CGH results was performed in same manner as in our previously published results.

  Dataset EGAD00001007743

• Exome sequencing data

  Exome sequencing fastq files from 6 mutation carriers and 5 non-carriers from 2 families. One µg DNA was used for library preparation using the TruSeq DNA LT Sample Prep Kit v2 according to the manufacturer’s instructions (Illumina). Hybridization was performed using Nimblegen SeqCap EZ Exome v3 (Roche) and Paired-end Sequencing (2x100 bp) on the Illumina HiSeq 2000 with TruSeq v3 chemistry (Illumina).

  Dataset EGAD00001003745

• Whole genome sequencing of metastatic cutaneous squamous cell carcinoma

  This dataset includes somatic small variant calling files derived from fifteen metastatic samples from cutaneous squamous cell carcinoma matched to normal blood samples. These samples were whole-genome sequenced by HiSeq X Ten and the resulting reads were mapped against the human genome (hg37) using BWA-MEM 0.7.10-r789. Somatic variant calling was then performed using strelka 1 (version 2.0.17).

  Dataset EGAD00001004530

• Metagenome for FINRISK2002

  The dataset contains data for n=7211 FINRISK 2002 participants who underwent fecal sampling. Demultiplexed shallow shotgun metagenomic sequences were quality filtered and adapter trimmed using Atropos (Didion et al., 2017), and human filtered using Bowtie2 (Langmead and Salzberg, 2012). The files are in FASTQ format.

  Dataset EGAD00001007035

• Targeted_analysis_of_chondrosarcoma_cancer_genes

  Targeted analysis of chondrosarcoma cancer genes

  Study EGAS00001001765

• Perceptions, Prevalence, and Patterns of Cannabis Use among Cancer Patients in NCI-Designated Cancer Centers

  This study aimed to better understand the evolving landscape of cannabis use among patients undergoing cancer treatment across diverse geographic regions. It sought to characterize patterns of use, patient perceptions, and contextual influences such as legal status and provider engagement that affect cannabis use. Given the shifting legal environment, this study addresses a critical gap in the literature by providing data on how cancer patients integrate cannabis into their care. The available delivery methods of cannabis have also undergone dramatic changes and now include edibles, oils, tinctures, topicals, and inhaled forms. State-based policy changes are rapidly changing. Yet research on cannabis use by cancer patients across a variety of geographic settings remains limited. The extent of cannabis use, the perceived and real benefits and risks of use, potential interactions with cancer treatment and other medications, and impact on comorbid conditions are uncertain. Clinicians should be aware of the extent of use in order to assess potential drug-drug interactions, side effects, and contraindications; hence, an understanding of how cancer patients and clinicians engage in discussions about cannabis use is essential. Twelve NCI-designated cancer centers were awarded supplemental funding to conduct surveys assessing cannabis use among recently diagnosed cancer patients. Selected sites were in 8 states with varied legal status for medical and recreational cannabis use at the time of the survey. The 12 cancer centers independently received approval from their institutional review boards (IRB) and collected data from September 2021 to August 2023. Eligible participants were cancer patients or survivors who resided in their respective cancer center's catchment area. Cancer centers were responsible for sampling patients within their catchment area with the goal of 1,000 completed surveys. Ten out of 12 cancer centers drew probability samples of patients from patient lists defining their catchment area with some stratifying the sample in various ways including by cancer type, by sex, by race/ethnicity or by a combination of demographic variables.

  Study phs004046

• Bulk-RNA Sequencing of high-grade pancreatic and non-pancreatic Neuroendocrine Neoplasms

  Therapeutic decisions in oncology depend on a precise pathological classification of individual neoplasms. Recent years have seen an intensification of research activities aimed at the extraction of clinically relevant information from patient-derived 'omics' data based on Machine-Learning models. However, a comprehensive training of Machine-Learning models requires sufficiently large numbers of training samples, which are usually not available for rare cancer types. The problem is worsened when individual tissues segregate into different cancer subtypes, as their discrimination would require even more training samples. Methods: Here, we report on a new data-augmentation technique to support the training of Machine-Learning models on ‘omics’ data from pancreatic neuroendocrine neoplasms (panNEN). PanNENs display all properties described above: Only about 2-3% of all pancreatic neoplasms are neuroendocrine and they fall into different subtypes with distinctly different prognosis, which makes the precise classification of such samples both difficult and important for therapy decisions. The approach reconstructs a given transcriptome based on healthy pancreatic cell type signatures and creates a Machine-Learning model that integrates the observed reconstruction error and predicted cell type proportions as features. Results: A benchmark of the deconvolution model predictions with the ground-truth found that the model could efficiently predict the sample grading, disease-related patient survival time, and differentiate between different subtypes in four panNEN and one mixed panNEN and non-pancreatic NENs dataset. We compared the predictive performance of the deconvolution-trained model to that of a model trained directly on the transcriptomic data, under inclusion of the Ki-67 classification gold standard biomarker, and found the performances to be comparable. Conclusion: Our approach serves as a data-augmentation technique to facilitate the training of Machine Learning models for rare cancer types via utilization of data from healthy origin. Additionally, the deconvolution results were clinically interpretable and further research can render the deconvolution approach an effective complementary asset for the clinical classification of neoplasms.

  Study EGAS00001004861

• Rapid detection of expanded short tandem repeats in personal genomics using hybrid sequencing.

  Long expansions of short tandem repeats (STRs); i.e., DNA repeats of 2-6 nucleotides, are associated with some genetic diseases. Cost-efficient high throughput sequencing can quickly produce billions of short reads that would be useful for uncovering disease-associated STRs. However, enumerating STRs in short reads remains largely unexplored because of the difficulty in elucidating STRs much longer than 100 bp, the typical length of short reads. We propose ab initio procedures for sensing and locating long STRs promptly by utilizing the frequency distribution of all STRs and paired-end read information. We validated the reproducibility of this method using biological replicates and used it to locate an STR associated with a brain disease (SCA31). Subsequently, we sequenced this STR site in eleven SCA31 samples using SMRT? sequencing (Pacific Biosciences), determined 2.3-3.1 kb sequences at nucleotide resolution, and revealed that (TGGAA)- and (TAAAATAGAA)-repeat expansions determined the instability of the repeat expansions associated with SCA31. Our method could also identify common STRs, (AAAG)- and (AAAAG)-repeat expansions, which are remarkably expanded at four positions in an SCA31 sample. This is the first proposed method for rapidly finding disease-associated long STRs in personal genomes using hybrid sequencing of short and long reads.

  Study JGAS000002

• A proteogenomic atlas of the human neural retina

  The human neural retina is enriched for alternative splicing, and it is estimated that more than 10% of variants associated with inherited retinal diseases (IRDs) alter splicing. Previous research mainly used short-read RNA-sequencing techniques to investigate retina-specific splicing and splicing factors. However, this technique provides limited information about transcript isoforms. To gain a deeper understanding of the human neural retina and its isoforms, we generated a proteogenomic atlas that combines PacBio long-read RNA-sequencing data with mass-spectrometry and whole-genome sequencing data from three healthy human neural retina samples. About one third of the nearly 60,000 transcript isoforms were novel, and ten novel peptides that confirmed novel isoforms were detected. This study highlights the importance of studying tissue-specific transcriptomes in greater detail to better understand tissue-specific regulation and to identify disease-causing variants.

  Study EGAS50000000070

• Controlling cell differentiation with precision through understanding the structure and dynamics of gene regulatory networks

  We established a set of transgenic human ES cell lines that carry inducible expression gene cassette for singe transcriptional factor induction with Tet-ON system. Transcriptome data was obtained 48h after transgene induction by Microarray. We established inducible human ES lines about more than 700 genes, and achieved microarray analysis on 115 genes. Our data set has multiple characteristic properties; 1) the same platform across data set, 2) analyzed with dynamic cell status, 3) pre-determined initiation point on gene perturbation, 4)inducible in different cell status. In parallele, we also performed RNA sequenncig analysis on 435 transgene induced ES lines as well. 32 transgene induced transcriptome data were obtained from both Microarray and RNA sequencing, normalizing technical gaps between them. We hope those systematic data set to reveal transcriptional network structure and molecular mechanisms of cell differentiation.

  Study JGAS000121

• RA-Map, A multi-omic survey of whole blood and subsets in early rheumatoid arthritis and vaccine study controls

  Rheumatoid arthritis (RA) is a chronic inflammatory disorder of unknown aetiology characterised by synovial inflammation with variable disease severity and drug responsiveness. To investigate the molecular heterogeneity and pathogenesis of RA, we performed a comprehensive clinical and molecular profile of 267 RA patients for up to 18 months to establish a high quality biobank of barcoded samples that included plasma, serum, peripheral blood cells, whole blood RNA, RNA from lymphocyte and monocyte subsets, genomic DNA and urine. We have performed extensive multi-omic immune phenotyping, including genomic, metabolomic, proteomic, transcriptomic and auto-antibody profiling. We anticipate that these detailed clinical and molecular data will serve as a fundamental resource for the development and application of targeted therapies for RA and reveal further insights into disease pathogenesis and therapeutic response.

  Study EGAS00001004424

• RBSC11

  One retinoblastoma sample was studied by single-cell RNA-sequencing (10X genomics Chromium).

  Dataset EGAD00001007497

• Genomic Analysis of Mucinous Tumours (GAMuT) - RNA

  RNASeq for Genomic Analysis of Mucinous Tumours (GAMuT)

  Dataset EGAD00001005190

• AI_NF1glioma_RNAseq

  The dataset includes 29 tumor samples from NF1-glioma patients profiled by RNA sequencing.

  Dataset EGAD00001004376

• EGAD00010000652

  Genotyped samples using Illumina HumanOmni2.5

  Dataset EGAD00010000652

• EGAD00010000096

  DBA case samples using 250K Nsp

  Dataset EGAD00010000096

• EGAD00010000381

  MRCE sample using 300K

  Dataset EGAD00010000381

• EGAD00010000383

  MRCA sample using 100K

  Dataset EGAD00010000383

• EGAD00010000385

  MRCA sample using 300K

  Dataset EGAD00010000385

• Methylation_JMML

  Methylation JMML samples using 450K Array

  Dataset EGAD00010001450

• Methylation_Controls

  Methylation Control samples using 450K Array

  Dataset EGAD00010001449

• HUMANOMNI1QUAD_Genotyping

  samples using Illumina HUMANOMNI1QUAD

  Dataset EGAD00010000919

• HUMANOMNIEXPRESS_Genotyping

  samples using Illumina HUMANOMNIEXPRESS

  Dataset EGAD00010000920

• Cancer Genetic Markers of Susceptibility (CGEMS) Prostate Cancer Genome-Wide Association Study (GWAS) - Primary Scan (Stage 1) - PLCO Screening Trial

  The Cancer Genetic Markers of Susceptibility (CGEMS) prostate cancer genome-wide association study (GWAS) included genotyping approximately 550,000 SNPs (Phase 1A with HumanHap300 and Phase 1B HumanHap240, both from Illumina, San Diego, CA) in 1,172 prostate cancer patients and 1,157 controls of European ancestry from the Prostate, Lung, Colon and Ovarian (PLCO, http://www.cancer.gov/prevention/plco/) Cancer Screening Trial. The original analysis published in Nature Genetics [PMID: 17401363] included 2,282 subjects. After improvement and revisions of the original analysis, 2,252 subjects were submitted to dbGaP.

  Study phs000207

• Rare germline sequence variants, copy number variations, expression alterations, methylation variations and disease susceptibility in familial melanoma

  Although a number of high-risk melanoma genes have been identified, they account for melanoma risk in less than 40% of melanoma-prone families. The major goals of our research are to identify novel high-penetrance genes for familial melanoma in melanoma-prone families without known mutations and to identify modifier factors, including genetic and epigenetic, in melanoma-prone families with and without known major mutations. We are using whole exome sequencing to identify additional high-risk susceptibility genes and using targeted sequencing to follow up on the top genes in additional family members and in population-based melanoma cases and controls. We are also using RNASeq to investigate genome-wide allele-specific expression and eQTLs in these families to identify genes with expression alteration, which will provide additional information for gene discovery. In addition, we also conducted genome-wide copy number variation (CNV), methylation, and miRNA expression profiling analyses in our melanoma families with the goal of identifying genetic and epigenetic factors as disease modifiers.

  Study phs001177

• WES in HCCOs with varying Doxorubicin resistance

  We aimed to identify somatic mutations that could explain the resistance to Doxorubicin. Therefor, we purified Exomes from liver biopsies and HCC organoids using Agilent SureSelectXT (clinical research exome, HS2 V8, or Human all Exon V6 Cosmic) and performed WES. Matched non-tumoral liver biopsies served as the control for germline mutations. 12 of these samples were previously reported. Sequence reads were aligned to the reference human genome GRCh38 using Burrows-Wheeler Aligner (BWA, v0.7.17). Duplicate removal, base quality adjustment, mutation calling (Mutect2, intervals: SureSelectXT_HS_V8_S33266340, germline-recourse: gnomad.exomes.r2.1.1.sites.liftover_grch38, Panel-of-Normal: 1000g_pon.hg38), filtering of Mutect calls, and functional annotation (Funcotator, funcotator_dataSources.v1.7.20200521g) were performed using the Genome Analysis Toolkit (GATK, v4.4) according to the Broad Institute best practices in Somatic short variant discovery workflows. Mutations with a functional annotation of Deletion, Insertion, Non-stop, Splice-Site, Start-Codon and Missense mutations were kept. A list of 43 commonly mutated genes in HCC was analyzed in the HCC organoids [TCGA, Comprehensive and Integrative Genomic Characterization of Hepatocellular Carcinoma. Cell, 2017. 169(7): p. 1327-1341.e23].

  Study EGAS50000000043

• FetalQuant-SD: Accurate quantification of fetal DNA fraction by shallow-depth sequencing of maternal plasma DNA

  Noninvasive prenatal testing using massively parallel sequencing of maternal plasma DNA has been rapidly adopted in clinical use worldwide. Fetal DNA fraction in a maternal plasma sample is an important parameter for accurate interpretations of these tests. However, there is a lack of methods involving low-sequencing depth and yet would allow a robust and accurate determination of fetal DNA fraction in maternal plasma for all pregnancies. In this study, we have developed a new method to accurately quantify the fetal DNA fraction by analysing the maternal genotypes and sequencing data of maternal plasma DNA. Fetal DNA fraction was calculated based on the proportion of non-maternal alleles at single-nucleotide polymorphisms where the mother is homozygous. This new approach achieves a median deviation of 0.6% between predicted fetal DNA fraction and the actual fetal DNA fraction using as low as 0.03-fold sequencing coverage of the human genome. We believe that this method will further enhance the clinical interpretations of noninvasive prenatal testing using genome-wide random sequencing.

  Study EGAS00001001611

• ATAC Dataset for 19 T-ALL patient samples and 1 normal control sample

  19 ATAC-seq from T-ALL patient samples and one healthy normal control sample. Reads were aligned to HG38 reference

  Dataset EGAD50000000024

• ChIPseq data for Glioblastoma (EGAS00001003953, H016)

  ChIPseq data for human glioblastoma patients, EGAS00001003953. Mix of input, H3K27ac, H3K27me1, H3K27me3, H3K36me3, H3K4me1, H3K4me3, H3K9me3 and BRD, 20 human samples, 2 cell lines (LN229, ZH487).

  Dataset EGAD00001006548

• ATAC Analysis of Treg and Tfh cells

  Treg and Tfh cells (8 Samples)from the same donors was subject to ATAC-seq processing. Paired end fastq-files are supplied.

  Dataset EGAD00001007660

• G&T-seq: Parallel sequencing of single-cell genomes and transcriptomes

  Development of a method for separation and parallel sequencing of the genomes and transcriptomes of single cells.

  Dataset EGAD00001001332

• Epigenomic profile of diverse cancer

  Epigenomic profile of diverse cancer.

  Study EGAS00001004352

• High volume culture initiating in vitro evolution in neuroblastoma cell lines

  Despite the advent of advanced molecular prognostic tools, it is still difficult to predict the course of disease for cancer patients at the individual level. This lack of predictability is also reflected in many experimental cancer model systems, begging the question of whether certain biological aspects of cancer (eg. growth, evolution etc.) can ever be anticipated or if there remains an inherent unpredictability to cancer, similar to other complex biological systems. We demonstrate by a combination of agent-based mathematical modelling, analysis of patient-derived xenograft systems from multiple cancer types, and in-vitro culture that certain conditions may invoke chaotic fluctuations in the clonal landscape of cancer growth. Our findings indicate that under those conditions, the cancer genome may behave as a complex dynamic system, making its long-term evolution inherently unpredictable.

  Study EGAS00001007962

• Reference_DNA_standards_for_GCLP_pipeline

  The use of reference DNA standards generated from cancer cell lines sequenced in the Cancer Genome Project to establish the sensitivity, specificity, accuracy and reproducibility of the WTSI GCLP sequencing pipeline

  Study EGAS00001001173

• cfDNA methylation profiling in Metastatic Cancer and Cancer of Unknown Primary

  This study contains methyl-binding domain sequencing and shallow whole genome sequencing from circulating cell-free DNA (cfDNA) for 143 patients with metastatic cancer of known type, 41 patients with Cancer of Unknown Primary (CUP) and 27 non-cancer controls.

  Dataset EGAD00001011178

• Genome-Wide Association Study of Hypertriglyceridemia in Mexicans

  Coronary artery disease (CAD) is the number one cause of death and mortality world-wide. High levels of serum triglycerides (TGs) and low levels of serum high-density lipoprotein cholesterol (HDL-C) are major risk factors for CAD. Previous epidemiological studies have shown that these two lipid disturbances are highly common dyslipidemias in Mexicans. However, the genetic factors underlying high serum TGs and low HDL-C are underinvestigated and poorly identified in Mexicans. As the Mexican-American and the genetically related Latin-American populations represent the fastest growing minority in the United States, elucidation of the unknown genetic factors influencing the increased susceptibility of Mexicans to these common dyslipidemias is of great relevance to these U.S. minorities and the American healthcare system. This study is a research collaboration between investigators at the University of California, Los Angeles (UCLA) and Instituto Nacional de Ciencias Médicas y Nutrición (INCMN), Mexico City, to perform a two-stage genome-wide association study (GWAS) for hypertriglyceridemia and low high-density lipoprotein cholesterol (HDL-C) in Mexicans (Weissglas-Volkov et al. 2013, PMID: 23505323). This study was funded by an RO1 grant from NIH/NHLBI (PI Paivi Pajukanta; PI of the subaward Teresa Tusie-Luna). In stage 1 of the GWAS, we tested all GWAS SNPs from the Illumina Infinium Human610-Quad platform that passed quality control for association in ~2,200 hypertriglyceridemia cases and controls. In stage 2, we genotyped the ~1,200 positive signals of stage 1 in additional ~2,200 hypertriglyceridemia cases and controls, and performed a combined analysis of the two stages to identify genome-wide significant variants. The subjects were recruited at the INCMN. The DNA isolation and clinical laboratory measurements of the case-control study samples were performed at INCMN using standardized procedures. Genotyping and statistical analyses of the data were performed at UCLA. A summary of this GWAS can be found in Weissglas-Volkov et al. 2013 Journal of Medical Genetics, PMID: 23505323. Briefly, using the two-stage GWAS design, we identified a novel Mexican-specific genome-wide significant locus for serum TG levels close to the Niemann-Pick type C1 protein (NPC1) gene (Weissglas-Volkov et al. 2013, PMID: 23505323). Of the European lipid GWAS loci, three TG loci (APOA5, GCKR, and LPL) and four HDL-C loci (ABCA1, CETP, LIPC and LOC55908) resulted in genome-wide significant signals in Mexicans. Furthermore, our cross-ethnic mapping narrowed three European TG GWAS loci, APOA5, MLXIPL, and CILP2 that exhibited long range LD and a large number of candidate SNPs in the European GWAS scan. In the apolipoprotein A1C3A4A5 gene cluster region, the cross-ethnic fine mapping and LD comparisons reduced the number of candidate variants to one SNP, rs964184. We also found that although 52% of the associations from European lipid GWAS meta-analysis could be generalized to Mexicans, in 82% of the European GWAS loci, a different variant other than the European lead SNP provided the statistically strongest evidence of association in the Mexican scan (Weissglas-Volkov et al. 2013, PMID: 23505323). Taken together, our Mexican GWAS for lipids identified a novel Mexican-specific locus for high serum TGs; restricted three European GWAS loci; and investigated which European lipid GWAS variants extend to the Mexican population (Weissglas-Volkov et al. 2013, PMID: 23505323). This NHLBI sponsored RO1 project aimed to identify genetic variants contributing to serum lipid levels in Mexicans. In addition to de-identified genome wide genotypic data, a selected list of de-identified phenotypic data related to hypertriglyceridemia and related metabolic traits are also available in dbGaP.

  Study phs000618

• The UCSD / O'Connor "TSP" (Twin/Sibling/Pedigree) Resource in Hypertension

  Study Design: The UCSD / O'Connor "TSP" (Twin/Sibling/Pedigree) Resource in Hypertension contains N=797 participants. At the time of recruitment individuals ranged from 15-84 years of age and had varying ethnic backgrounds (Whites, African-Americans and Hispanics). The cohort was developed to study the genetic basis of autonomic dysfunction in human essential hypertension (reviewed in Zhang et al. Curr Hypertens Rep. 2011 13: 36-45. PMID: 21104344) and contains cross-sectionally collected phenotypes related to blood pressure regulation.  Phenotypes: Phenotype data specifically focuses on the sympathetic branch of the autonomic system, which is a key regulator of blood pressure. Data includes circulating concentrations of the secretory "quantum" (catecholamines, neuropeptides, chromogranins) which influence vascular responses to sympatho-adrenal activation resulting in blood pressure. Other measures on the twins and a subset of family members include a standard urine panel with absolute concentrations of potassium, sodium, uric acid, phosphorous; DynaPulse acquired heart rate and blood pressure measures including systolic and diastolic blood pressure, mean arterial pressure, heart rate, Left Ventricular (LV) ejection time, LV contractility, cardiac output, stroke volume data including; and absolute concentrations of plasma aldosterone, endothelin, leptin, and insulin. Phenotype data is included for the 697 individuals sequenced here and 100 family members.  Whole Genome Sequence Data Generation: Whole genome sequencing (20X coverage) was conducted on plasma-derived DNA. The WGS was generated using the Illumina HiSeq X Ten sequencing platform with variants called by Human Longevity, Inc (HLI; Ref 1). Preparation of sample libraries was conducted by mechanical shearing of gDNA (100-800 bp), isolation of DNA fragments 300-500bp in size, followed by library PCR amplification employing high-fidelity, low-bias PCR to amplify library fragments consisting of appropriate adapter sequences on both ends. BAM files were created by alignment of sequence reads to the reference genome (GRCh38) using iSAAC-01.14.02.06 (Python2.7). Note: The user may want to realign the sequence data and recall variants. In total, the WGS dataset contains 30 monozygotic twin pairs represented by one member of the twin pair, 133 monozygotic twin pairs with both individuals sequenced, 7 dizygotic twin pairs represented by one member of the twin pair, 67 dizygotic twin pairs with both individuals sequenced, 8 twin pairs with undetermined zygosity (both individuals sequenced) and 1 triplet with mother (all individuals sequenced). The dataset also contains sequences of 260 family members of twins including their mother, father, non-twin sibling, and offspring. Table 1 describes the composition of families ("sibling" refers to a non-twin sibling in the cohort). Note: We suggest users check gender and family relatedness. Table 1: Description of the families with sequence data                                                                                                               Units with:Twin PairsTwin (no pairs)No twinSibshipsMother and Father511Mother only1222Father only113One or more siblings22133Mother and siblings132Father and siblings(s)211Offspring of twins11Non twin siblings2Sib with unknown relative1Only one member of8The UCSD/O'Connor "TSP" (Twin/Sibling/Pedigree) Resource in Hypertension is now being managed at the UCSD School of Medicine's Institute for Genomic Medicine (IGM). The TSP Resource has collected a wide range of information (phenotypic, genotypic, demographic, metabolomic) and reagents (blood, plasma, urine, DNA, human induced pluripotent stem cells). For additional information about the resource, including other data types available as well as references and links to data from studies with previous collaborators, please go to the resource website at IGM [http://igm.ucsd.edu/research/twins-resource.shtml] or contact Dr. Brinda Rana at UCSD [bkrana@ucsd.edu]. 

  Study phs002230

• The Collaborative Study on the Genetics of Alcoholism (COGA)

  COGA is a family study of alcoholism, in which the subjects have been drawn from the Collaborative Study on the Genetics of Alcoholism (COGA), a large, ongoing family-based study that includes subjects from seven sites around the US. COGA has gathered detailed, standardized data on study participants, including diagnostic and neurophysiological assessments. This project has already proved successful in identifying several genes that influence the risk for alcoholism and neurophysiological endophenotypes, which have been independently replicated. COGA data were included as part of two Genetic Analysis Workshops, and the phenotypes are familiar to the genetics community. Alcoholic probands were recruited from treatment facilities, assessed by personal interview, and after securing permission, other family members were also assessed. A set of comparison families was drawn from the same communities as the families recruited through an alcoholic proband. Assessment involved a detailed personal interview developed for this project, the Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA), which gathers detailed information on alcoholism related symptoms along with other drugs and psychiatric symptoms. Many participants also came to the laboratories for electroencephalographic studies. Neurophysiological features that have been shown to be useful endophenotypes for which we have linkage and in some cases association results, are included for a subset of the case-control sample: the beta power of the resting electroencephalogram (EEG), the P3(00) amplitude of the visual event-related potential (ERP), and the theta and delta event-related oscillations (EROs) underlying the P3. As part of COGA, a set of informative families was selected to have Genome-Wide Association data obtained within families. Genotyping was performed using the Illumina Human OmniExpress array 12.VI to genotype 2,282 subjects selected from 118 densely affected families. Genotyping was performed at the Genome Technology Access Center at Washington University School of Medicine in St. Louis. In addition, we also included genotypes for subjects (n=275 subjects) from these 118 families who were genotyped in a previous case-control GWAS using the Illumina 1M array. For quality control purposes, 51 of the 275 subjects were genotyped again on the Illumina Human OmniExpress array at the Washington University School of Medicine core facility.In addition, exome sequencing data on a subset of individuals with GWAS were added in version 2 (v2). For v2, a subset had 30X Whole Genome Sequencing (WGS) as part of the NIDA Sequencing Initiative. The subset contained two distinct sets: Sibling pairs where one sibling had at least two dependence diagnoses in the set (alcohol, cannabis, cocaine, and opioid), and the other had none, and non-related Case-Control pairs matched for age and ethnicity where the cases had alcohol and at least 2 other dependence diagnoses and controls had none. After sequencing, some sibling pairs are re-classified as half siblings. Three VCF files (small variants, structural variants, and copy number variations) are provided. Additional substance use variables are made available in v2. We note that the full sample data are deposited in four dbGaP submissions and the sequenced samples are split across all four: CIDR: Collaborative Study on the Genetics of Alcoholism Case Control Study [phs000125]. GWAS data on cases (primarily probands) and controls drawn from the families. Families with highest density of alcohol dependence and/or extreme event-related oscillation data [phs000763]. GWAS data on 119 extended families of European descent are available here, along with extensive documentation. Study on the Genetics of Alcoholism (COGA): African American Family GWAS [phs000976]. GWAS data on all available COGA families of African descent are available. COGA: Smokescreen GWAS [phs001208]. GWAS data on all remaining COGA DNA samples, primarily of other racial background, were genotyped on the Smoke Screen array. A listing of all sequenced pairs is provided in the documentation to facilitate the merging of these samples.

  Study phs000763

• Birth Defects: Moebius Syndrome and Related Congenital Facial Weakness Disorders

  It is estimated that about 1 in every 33 infants in the United States is born with a birth defect. Among these, the subset of birth defect syndromes associated with facial weakness and lack of facial expression can have profound implications for social interactions and psychosocial development. Moebius syndrome is defined by congenital and non-progressive facial weakness and limited eye abduction, and most cases are believed to result from dysfunction of cranial nuclei/nerves VI and VII. Although rare, this syndrome causes significant impairment because of facial weakness and associated intellectual disabilities, autism, hearing loss, difficulty swallowing and breathing, peripheral neuropathy, muscle hypotonia, heart defects, chest wall abnormalities, and limb malformations. The phenotypic spectrum and the associated genetic and environmental factors underlying Moebius syndrome are poorly understood. The goal of this research is to identify causative gene mutations for Moebius syndrome and related conditions, such as Moebius-Poland or -Robin sequence, hereditary congenital facial paresis (HCFP), and oculoauriculovertebral dysplasia (Goldenhar syndrome). This proposal builds on an ongoing collaboration among researchers at Mount Sinai Medical Center, Boston Children's Hospital, NHGRI intramural program, and the Moebius Syndrome Foundation, but aims to greatly extend that work by collaboration with investigators in the NIH Clinical Center (CC). Our groups have already defined a new autosomal dominant syndrome with Moebius syndrome, Kallmann syndrome, cyclic vomiting resulting from a TUBB3 E410K substitution. We have also identified a new autosomal recessive Moebius-related syndrome with bilateral facial palsy, hearing loss, and strabismus resulting from a HOXB1 R207C substitution. Through collaborative efforts of these extramural teams with intramural investigators, whole exome sequencing (WES) has been conducted for four families with Moebius-like features, and data analyses are ongoing. The overall goal of this new grant application will be to conduct extensive phenotype analysis on approximately 24 families per year with Moebius and other undefined syndromes with facial weakness. Studies to be conducted at the CC include neurology, psychiatry, neurocognitive, rehabilitation medicine (muscle strength, speech/language pathology), ophthalmology, audiology, and genetics evaluations; autism screening; electromyography, nerve conduction, and blink reflex studies; videoscopy of quantitative eye movement recordings; 3D-CT craniofacial imaging; MRI of the brain, orbit, internal auditory canals, posterior fossa including brain diffusion tensor imaging for tractography; and genetic counseling. Jointly with the extramural teams, WES analysis and variant confirmation will be performed. A more comprehensive definition of the phenotypic and genotypic spectrum of these birth defects will have a significant impact on our understanding of the molecular pathways underlying dysmorphologies, cranial nerve development, and more common childhood disorders such as autism. Thus, this project will lead to strategies for prevention and treatment of birth defects.

  Study phs001383

• Action to Control Cardiovascular Risk in Diabetes (ACCORD) Clinical Trial

  The Action to Control Cardiovascular Risk in Diabetes (ACCORD) clinical trial was a randomized, multicenter, double 2 x 2 factorial design study involving 10,251 middle-aged and older participants with type-2 diabetes who are at high risk for CVD events because of existing CVD or additional risk factors. The purpose of ACCORD was to determine if intensive glycemic control, intensive lipid management and intensive blood pressure control could prevent major cardiovascular events (myocardial infarction, stroke or cardiovascular death) in adults with type 2 diabetes mellitus. Secondary hypotheses included treatment differences in other cardiovascular outcomes, total mortality, microvascular outcomes, health-related quality of life and cost-effectiveness. The ACCORD trial failed to show a beneficial effect of intensive blood pressure or lipid therapy on the primary outcome, and intensive glycemia management actually increased mortality. The hypothesis underlying this ancillary study is that the failure of ACCORD to achieve its goal of reducing cardiovascular risk in diabetic patients through intensive management of hyperglycemia, dyslipidemia, and hypertension may be the result of variation in drug response due to genetic variation between individual participants. Benefits of intensive therapy may accrue to subsets of subjects with specific genetic variants predisposing to efficacious responses to particular therapeutic regimens, and harms may accrue to those with other variants predisposing to poor efficacy or adverse events. Identifying these variants could lead to a precision medicine approach to treating diabetes where each patient's genetic profile could identify the most efficacious treatment regimen with the lowest likelihood of adverse events. To test this hypothesis, a genome-wide genetic analysis was undertaken, incorporating both common variants distributed across the genome and rare variants targeted to exonic regions. Associations of genetic variants with short term responses to individual medicines as well as long term outcomes were investigated. The dataset is composed of genetic data from the ~6100 participants who agreed to participate in the ACCORD optional genetic studies and who allowed broad investigator access to their samples and the data derived from those samples, and from whom a DNA sample of sufficient quality was obtained. While a total of 8514 participants consented to the optional genetics studies, not all consented to broad investigator access, and those who did not are not included in this dataset, although they were also genotyped. Access to these additional genotypes can only be obtained by direct collaboration with the investigators of this study. Phenotype data used in the association analyses are derived from the ACCORD public release clinical data set, which has been made available through BioLINCC.

  Study phs001411

• The Genetic Basis of Aggressive Prostate Cancer, The Role of Rare Variation

  In this study, we will apply a multi-staged approach to reveal genes harboring rare variants that are associated with aggressive PCa. Whole-exome sequencing (Aim 1a) of 2,774 aggressive cases and 2,776 non-aggressive cases of European ancestry will be conducted followed by rare variant analysis of single sites and gene burden testing to identify novel susceptibility loci/genes for aggressive disease. We will validate the most significantly associated genes (~500) through targeted sequencing in an additional 6,415 aggressive and 5,586 non-aggressive cases and 1,890 controls (Aim 1b). Next, we will investigate the clinical predictive utility of the genes/variants identified in 2,291 cases in the STHM3 trial who are undergoing biopsy based on PSA and genetic risk score stratification (Aim 2). Through this tiered approach we expect to significantly advance knowledge of aggressive PCa etiology and health disparities as well as guide the development of early detection and prognostic strategies for the subset of men who are most susceptible to this fatal form of disease. In this case-case study of aggressive vs non aggressive prostate cancer, aggressive cases are defined as prostate cancer as cause of death, (T4 disease or T3 disease) and Gleason 8+. Non-aggressive cases are men with T1/2 disease and Gleason ACKNOWLEDGMENTS and CONTRIBUTING SITES CAPS, PROCAP, STHM1, STHM2: Swedish Cancer Society (CAN 2016/818), Swedish Research Council (2014/2269).STHM3: Stockholm County Council (Stockholms Läns Landsting).MEC: Funding provided by the National Cancer Institute: Understanding Ethnic Differences in Cancer, 2U01CA164973 and The Genetic Basis of Aggressive Prostate Cancer, The Role of Rare Variation, 5R01CA196931-02.ATBC: The ATBC Study is supported by the Intramural Research Program of the U.S. National Cancer Institute, National Institutes of Health, and by U.S. Public Health Service contract HHSN261201500005C from the National Cancer Institute, Department of Health and Human Services.COSM: The Swedish Research Council/National Research Infrastructure Grant (VR 2014/6397; VR 2015/5997) The Swedish Cancer Foundation (CAN 2013/456; CAN 2016/727)CPSII: The authors express sincere appreciation to all Cancer Prevention Study II participants and to each member of the study and biospecimen management group. The American Cancer Society funds the creation, maintenance, and updating of the Cancer Prevention Study-II cohort.MCCS/APCS/PCFS: The Melbourne Collaborative Cohort Study (MCCS) recruitment was funded by VicHealth and Cancer Council Victoria and further supported by Australian National Health and Medical Research Council (NHMRC) grants 209057 and 396414. The Aggressive Prostate Cancer Case-Control Study (APCS) was funded by NHMRC grant 623204. The Prostate Cancer Family Study (PCFS) was fully funded by Cancer Council Victoria. Cancer Council Victoria funds the continuing maintenance and updating of the MCCS, APCS and PCFS. Cases and their vital status are ascertained and followed up through the Victorian Cancer Registry and the Australian Institute of Health and Welfare, including the National Death Index and the Australian Cancer Database.PLCO: The Prostate Lung Colorectal Ovarian Cancer Screening Trial (PLCO) was supported by the Intramural Research Program of the Division of Cancer Epidemiology and Genetics and by contracts from the Division of Cancer Prevention, National Cancer Institute, US National Institutes of Health, Department of Health and Human Services. EPIC: The coordination of EPIC is financially supported by International Agency for Research on Cancer (IARC) and also by the Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London which has additional infrastructure support provided by the NIHR Imperial Biomedical Research Centre (BRC). The national cohorts are supported by: Danish Cancer Society (Denmark); Ligue Contre le Cancer, Institut Gustave Roussy, Mutuelle Générale de l'Education Nationale, Institut National de la Santé et de la Recherche Médicale (INSERM) (France); German Cancer Aid, German Cancer Research Center (DKFZ), German Institute of Human Nutrition Potsdam- Rehbruecke (DIfE), Federal Ministry of Education and Research (BMBF) (Germany); Associazione Italiana per la Ricerca sul Cancro-AIRC-Italy, Compagnia di SanPaolo and National Research Council (Italy); Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF), Statistics Netherlands (The Netherlands); Health Research Fund (FIS) - Instituto de Salud Carlos III (ISCIII), Regional Governments of Andalucía, Asturias, Basque Country, Murcia and Navarra, and the Catalan Institute of Oncology - ICO (Spain); Swedish Cancer Society, Swedish Research Council and County Councils of Skåne and Västerbotten (Sweden); Cancer Research UK (14136 to EPIC-Norfolk; C8221/A19170 and C8221/A29017 to EPIC-Oxford), Medical Research Council (1000143 to EPIC-Norfolk; MR/M012190/1 to EPIC-Oxford). (United Kingdom). DFCI: Linda and Arthur Gelb and Rebecca and Nathan Milikowsky. HPFS and PHS: The Health Professionals Follow-up Study was supported by U01 167552 and P01 CA228696 from the National Cancer Institute, and with support from the Prostate Cancer Foundation. The Physicians' Health Study was supported by grants CA34944, CA40360, CA097193, HL26490 and HL34595.Northwestern: P50CA180995 (Catalona) 08/01/15 – 07/31/20 NIH/NCI SPORE in Prostate Cancer; The Urological Research FoundationPROMPT: MRC UK - Project reference G0500966, Cambridge BRC infrastructure funding, Cambridge Biomedical Research Campus (BRC-1215-20014), CRUK Cambridge Cancer Centre infrastructure funding (they are requesting this statement is written in blue for publications).ICR: This work was supported by the NIH R01 grant 5R01CA196931-02. The samples from the UK were from UKGPCS and PrompT. The UKGPCS study was supported by Cancer Research UK (grant numbers C5047/A7357, C1287/A10118, C1287/A5260, C5047/A3354, C5047/A10692, C16913/A6135 and C16913/A6835). We would like to acknowledge the NCRN nurses and Consultants for their work in the UKGPCS study. We thank all the patients who took part in this study. We also acknowledge The Institute of Cancer Research, The National Cancer Research Network UK, The National Cancer Research Institute (NCRI) UK for their ongoing support. We are grateful for support of NIHR funding to the NIHR Biomedical Research Centre at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust.Funding:CIDR grant X01HG008336

  Study phs001524

• Evaluation of the ERa binding region activity in breast and endometrial cancer

  Evaluate the activity of ERa binding site activity in breast and endometrial cancer.

  Study EGAS50000000009

• NOWAC blood-based breast cancer case-control study

  Tumor-host interactions extend beyond the local microenvironment and cancer development largely depends on the ability of malignant cells to hijack and exploit the normal physiological processes of the host. Although abnormalities in a host’s systemic immunity are associated with increased cancer susceptibility, the functional interplay between tumor cells and circulating immune cells in regulating tumorigenic responses is unclear. We employed the Norwegian Women and Cancer study, a large prospective population-based cohort study, to identify gene expression changes in blood cells that provide a robust and reproducible diagnostic signal specific to breast cancer patients. We further show that circulating blood cells in breast cancer patients are enriched in genes involved in systemic immunosuppression and the motility, metabolism, growth, and proliferation of immune cells. By mining of the cancer-associated blood transcriptome, we identified immune mediators or biomarkers that could permit early detection of breast cancer and open avenues to novel targeted immunotherapies.

  Study EGAS00000000134

• Isolation of bacteria in infected brains in patients with Parkinsons disease. Here we used next generation sequencing of 16S ribosomal RNA gene PCR amplicons (NGS 16S amplicon analysis).

  Dac EGAC00001001197

• RNAseq of fibroblasts

  RNA sequencing data of fibroblasts from 3 controls and 3 patients with RBMX variants.

  Dataset EGAD50000002371

• Direct RNA sequencing of 10 postmortem human brain samples

  Contains fast5 data for each of the 10 samples sequenced.

  Dataset EGAD00001015347