10117 results for "cancer rna-seq"

in 38.31 milliseconds.

• Genetic regulation of RNA splicing in human pancreatic islets

  Genetic variants that influence transcriptional regulation in pancreatic islets play a major role in the susceptibility to type 2 diabetes (T2D). For many susceptibility loci, however, the mechanisms are unknown. To this end, we examined splicing and gene expression QTLs (sQTLs and eQTLs) in pancreatic islets from 399 human donors from publicly available cohorts and in-house data. Here we provide newly generated RNA-seq data and genotyping array data from 101 donors.

  Study EGAS00001006440

• Direct Comparative Analysis of 10X Genomics Chromium and Smart-seq2

  Single cell RNA sequencing (scRNA-seq) is widely used for profiling transcriptomes of individual cells. The droplet-based 10X Genomics Chromium (10X) approach and the plate-based Smart-seq2 full-length method are two frequently-used scRNA-seq platforms, yet there are only a few thorough and systematic comparisons of their advantages and limitations. Here, by directly comparing the scRNA-seq data by the two platforms from the same samples of CD45- cells, we systematically evaluated their features using a wide spectrum of analysis. Smart-seq2 detected more genes in a cell, especially low abundance transcripts as well as alternatively spliced transcripts, but captured higher proportion of mitochondrial genes. The composite of Smart-seq2 data also resembled bulk RNA-seq data better. For 10X-based data, we observed higher noise for mRNA in the low expression level. Despite the poly(A) enrichment, approximately 10-30% of all detected transcripts by both platforms were from non-coding genes, with lncRNA accounting for a higher proportion in 10X. 10X-based data displayed more severe dropout problem, especially for genes with lower expression levels. However, 10X-data can better detect rare cell types given its ability to cover a large number of cells. In addition, each platform detected different sets of differentially expressed genes between cell clusters, indicating the complementary nature of these technologies. Our comprehensive benchmark analysis offers the basis for selecting the optimal scRNA-seq strategy based on the objectives of each study.

  Study EGAS00001003973

• SPECTA Lung cancer RNA FASTQ files

  SPECTA Lung cancer RNA FASTQ files (Illumina TST170 targeted analysis)

  Dataset EGAD00001006222

• Oncogenic FOXL2C134W has gain-of-function chromatin remodeling activity that reprograms glucocorticoid receptor occupancy to promote ovarian granulosa cell tumor growth

  This dataset contains bam files from the whole exome sequencing performed on granulosa cell tumors and 7 sequencing experiments performed on human-derived KGN granulosa cell tumor cells and isogenic cell lines. The latter include transcription factor ChIP-seq for Foxl2 as well as transcription factor ChIP-seq for Foxl2 and GR under dexamethasone treatment and untreated conditions, two ATAC-seq data sets, two RNA-seq data sets, and Histone marks ChIP-seq.

  Dataset EGAD50000000880

• Understanding the Progression of Metastatic Colorectal Cancer

  This study is to understand (1) the clonal evolution of metastatic colorectal cancer using DNA sequencing and (2) long non-coding RNAs associated with metastatic colon cancer using RNA sequencing. Our goal is to better understand the progression of aggressive colorectal cancer.

  Study phs001722

• GENCORD2_RNAseq

  GENCORD2 RNA-seq BAM files using BWA

  Dataset EGAD00001000425

• Transcriptomic profiling of lymphedema

  RNA-seq of skin from human subjects with and without lymphedema

  Dataset EGAD00001006246

• Normal CD19

  Bulk RNA-seq on normal human CD19+ cells

  Dataset EGAD00001011105

• Single-Cell Sequencing Reveals Distinct Microenvironment Cell Types Associated with Response to High Dose Melphalan and Autologous Stem Cell Transplant in Multiple Myeloma

  The aim of this study is to understand the transcriptome of microenvironment cells in pre- and post- autologous stem cell transplantation (ASCT) samples between patients with complete response and partial response to transplant. Here, we studied immune cells from 40 multiple myeloma patients who have undergone ASCT. Samples were collected from 40 multiple myeloma patients before and after ASCT. Samples were sorted using magnetic activated cell sorting (MACS) and the non-tumor CD138- fraction underwent 3' single cell RNA-sequencing (scRNA-seq) or 5' scRNA-seq + 5' T cell receptor sequencing (TCRseq), to determine the scRNA transcriptome and TCR repertoire. This study includes 24 samples with 3' scRNA-seq, 56 samples with 5' scRNA-seq, and 56 samples with 5' TCRseq data.

  Study phs003219

• Idiosyncratic and generic single nuclei and spatial transcriptional patterns in papillary and anaplastic thyroid cancers

  Thyroid cancer is the most common endocrine malignancy. This dataset encompasses two types of thyroid cancer : anaplastic which is the most de-differentiated and aggressive one, and papillary which is the most common one. We profiled 14 patients, including 10 papillary and 4 anaplastic thyroid carcinomas, using both single nuclei RNA sequencing and spatial transcriptomics to link single cell resolution RNA sequencing with tissue morphology and better understand inter and intratumoral thyroid cancer heterogeneity.

  Study EGAS00001007574

• FBSeq: RNA sequencing of human fetal brain.

  RNA sequencing of 120 human fetal brains (aged 12-19 post-conception weeks) was performed as part of a Medical Research Council (U.K.) funded project (MR/L010674/2) to investigate genetic effects on gene expression in the developing human brain and their role in neuropsychiatric disorders. Human fetal brain tissue from elective terminations of pregnancy was provided by the Human Developmental Biology Resource (HDBR) (http://www.hdbr.org), with ethical approval (#08/H0712/34), and with consent for use of fetal material for medical research provided by female donors. Total RNA was extracted from half of the available brain tissue from each fetus using Tri-Reagent and treated with TURBO DNase. RNA-Seq libraries were prepared using 1µg of purified total RNA and the Illumina TruSeq Stranded Total RNA Library Prep kit, following ribosomal RNA depletion. Libraries were sequenced on the Illumina HiSeq 2500 or HiSeq 4000 systems, generating at least 50 million read pairs per sample.

  Study EGAS00001003214

• Enhancer signatures stratify and predict outcomes of non-functional pancreatic neuroendocrine tumors

  Most pancreatic neuroendocrine tumors (PNETs) do not produce symptoms of hormonal excess and are hence considered “non-functional”. Their clinical behaviors vary widely, emphasizing the need for a robust classification with prognostic power. Using enhancer maps to infer regulatory programs, we find that the large majority of non-functional PNETs fall into two major sub-types that reflect alpha and beta endocrine cell ontogeny, respectively. Tumors of the different subtypes have similar clinical presentations and histology, but express distinct lineage-specifying transcription factors, ARX or PDX1. Here we provide the raw ChIP-seq and RNA-seq data of the PNET cohort in this study, as well as ChIP-seq data of ileal carcinoids.

  Study phs001910

• Discovery of cancer prognostic markers based on comparison of gene expression in colorectal cancer samples.

  Here, we analyse bulk mRNA-seq data derived from normal tissues adjacent to tumors (NATs) and tumour tissues of colorectal cancer (CRC), including 80 NAT samples and 80 tumour samples.

  Study EGAS00001005068

• RNA-Sequencing data of patient derived normal fibroblasts (NFs), cancer associated fibroblasts (CAFs) and tumor spheroid samples

  RNA-Sequencing data of patient derived normal fibroblasts (NFs), cancer associated fibroblasts (CAFs) and tumor spheroid samples performed in the context of the characterization of an IL1R1 positive CAF population in CRC tumour samples.

  Study EGAS00001007205

• PBMC scRNA-seq data using 10X Genomics platform

  Matrices of counts from single-cell RNA-seq data and single-cell CITE-seq data collected from 16 patients enrolled in GO30103 trial, and the cell level annotation. Specifically, PBMCs at C1D1, C1D15 (2 weeks after treatment), C2D1 (3 weeks after treatment) and C4D1 (9 weeks after treatment) were collected and subject to 10x Genomics protocol. Associated metadata also included.

  Dataset EGAD50000000370

• DRIP-seq data for Molecular Characterization of ETMRs

  This dataset contains DRIP-seq data from 2 patients. DNA–RNA hybrids were extracted from tissue derived from ETMR patient-derived xenograft (PDX) models (BT183) that were treated using topotecan or saline as described previously27. Tumours were subsequently frozen and pelleted using ultracentrifugation. DNA–RNA hybrids were extracted as described previously using the same protocol that is applied for cultured cells21. DNA was extracted using proteinase K followed by phenol–chloroform extraction and ethanol precipitation. Subsequently the DNA was fragmented using the restriction enzymes HindIII, EcoRI, BsrGI, XbaI and SspI (New England Biolabs). Digested DNA was subsequently incubated with the anti-DNA–RNA hybrid anti- body S9.6 (Merck, MABE1095) and immunoprecipitated using agarose beads. Bound DNA–RNA hybrids were eluted and incubated with pro- teinase K and cleaned with an additional phenol–chloroform–ethanol extraction. The DNA was subsequently sonicated and sequenced using a Hiseq 2000 machine with a 50-bp single-read protocol. Each treat- ment condition was performed in duplicate and both RNase H and the input was included as negative controls resulting in 10 Fastq files.

  Dataset EGAD00001006219

• RNAseq data for EGAS00001004572

  Bulk RNA-seq data of tumours in EGAS00001004572.

  Dataset EGAD00001006876

• RNA-seq of iPSC-derived neurons treated with miRNA mimics and inhibitors

  iPSC-derived neurons were treated with mimics and inhibitors of the miRNAs miR-150-5p, hsa-mir-193a-3p and hsa-miR-19b-3p. RNA-sequencing was then performed to examine the effects of miRNA up-regulation and inhibition.

  Dataset EGAD00001006844

• Stereotyped subset CLL RNA-seq from 100 patient with CLL

  RNA-sequencing data for 100 stereotypes CLL subset cases. Illumina based short-read sequencing data from a 100 samples from patients with CLL. Oxford Nanopore Technologies long-read sequencing data from 5 samples from patients with CLL.

  Dataset EGAD00001009729

• Targeted_gene_fusion_sequencing__Fus_seq__in_mesothelioma

  This is a small pilot data set to test the feasibility of cDNA exomes across 1200 cancer cell line panel. cDNA exomes or Fus-seq is further explained in this studies Abstract.

  Study EGAS00001000390

• Genomic and epigenomic study of Japanese renal cell carcinoma including WGS, RNA-seq, ATAC-seq, and methyl-seq

  We performed whole-genomic and transcriptomic sequencing of more than 100 Japanese renal cell carcinoma (RCC) cases, including clear cell RCC, papillary RCC, chromophobe RCC, and TFE3-translocated RCC. In addition, we conducted epigenome sequencing analyses: the assay for transposase-accessible chromatin sequencing (ATAC-seq) and enzymatic methyl sequencing.

  Study EGAS00001006919

• Genomic Profiling of Pediatric B-cell Acute Lymphoblastic Leukemia

  Pediatric leukemia is the most common type of childhood cancer and, despite tremendous progress in treatment, remains the second leading cause of cancer deaths in children. B-cell acute lymphoblastic leukemia (B-ALL) is the most common type of pediatric leukemia. Recent studies using transcriptional profiling of large cohorts of pediatric B-ALL have shown that patients can be grouped into transcriptional subtypes that are often defined by specific driver mutations. Interestingly, many of these mutational subtypes are defined by gene fusions or rearrangements that drive altered expression of transcription factors (ETV6-RUNX1, PAX5, DUX4, TCF3-PBX1, ZNF384) or in chromatin regulatory machinery (KMT2A), suggesting that transcriptional dysregulation is a major driver of B-ALL. While the transcriptional distinctions are clear, the relationship between patients in terms of their chromatin regulatory landscape remains unclear. To address this, we profiled gene expression, open chromatin, and 3D genome folding in patient derived B-ALL samples. We identified that at the level of 3D genome organization, many chromatin interactions and looping events are shared across mutational subtypes, suggesting that shared transcriptional programs, in addition to group specific driver mutations, possibly regulate the chromatin landscape in B-ALL. Using RNA-seq and ATAC-seq data, we were able to identify "latent" signatures of expression related to non-mutant transcription factors (TFs) that also contribute to expression heterogeneity across TF subtypes. These are related to patient specific patterns of 3D genome folding, and in some cases, are predictive of disease outcomes. This study helps shed light on the chromatin landscape in B-ALL and furthers our understanding of the interactions between diverse mutant TFs that drive B-ALL and non-mutant TFs that help shape the B-ALL chromatin landscape.

  Study phs003226

• single cell RNA-seq and ATAC-seq of human fetal forebrain tissue

  Oligodendrogenesis in the human central nervous system has been mainly observed at the second trimester of gestation, a much later developmental stage compared to mouse. Here we characterize the transcriptomic neural diversity in the human forebrain at post conceptual weeks (PCW) 8 to 10, using single-cell RNA-Seq. We find evidence of the emergence of a first wave of oligodendrocyte lineage cells as early as PCW 8, which we also confirm at the epigenomic level with single-cell ATAC-Seq. Using regulatory network inference, we predict key transcriptional events leading to the specification of oligodendrocyte precursor cells (OPCs). Moreover, by profiling the spatial expression of fifty key genes using In Situ Sequencing (ISS), we identify regions in the human ventral fetal forebrain where oligodendrogenesis first occurs. Our results indicate evolutionary conservation of the first wave of oligodendrogenesis between mouse and human and describe regulatory mechanisms involved in human OPC specification.

  Study EGAS00001006136

• RNA-Seq data of hepatoma (Huh7 derived) and Ph5CH cells and primary hepatocytes

  The innate immune response of cells of hepatic origin (Huh7, Huh7.5, PH5CH and primary human hepatocytes (PHH), 66 samples) was analyzed by transcriptome analysis (RNAseq) upon supernatant delivery or transfection of synthetic dsRNA (poly(I:C)). Expression of TLR3 and RIG-I was reconstituted by lentiviral transduction in Huh7 and Huh7.5 cells. The sequencing is single RNA-Seq on an Illumina HiSeq 4000 with the Illumina TruSeq stranded mRNA kit.

  Dataset EGAD00001007083

• Transcriptome profiling of three giant cell tumour of bone (GCTB) cell lines

  This dataset contains RNA-seq data of giant cell tumour of bone (GCTB) cell lines (n=3). Cell lines consist of neoplastic "stromal" cells harboring a heterozygous H3F3A p.G34W mutation. RNA-seq was performed on the BGISEQ-500 platform (PE100) and uploaded data contains fastq files, vcf files, and gene expression values (TPM). Cell lines, data generation, and data analysis are described in the following publication: Venneker et al., Histone deacetylase inhibitors as a therapeutic strategy to eliminate neoplastic “stromal” cells from giant cell tumors of bone, 2022.

  Dataset EGAD00001009074

• Transcriptome analysis of adolescents and young adults with Acute Lymphoblastic Leukemia

  The primary purpose of the research is identification of novel chromosome translocations in adolescents and young adults (AYA) with Acute Lymphoblastic Leukemia (ALL). We searched for novel chromosome translocations in 99 philadelphia-chromosome negative ALL cases (including 76 AYA cases) by RNA-seq using next-generation sequencers, and have discovered some novel chromosome translocations.

  Study JGAS000047

• Single-cell RNA-seq of immune cells from human tumor fragments after 48 hour culture ex vivo (Kaptein et al., 2024)

  Single-cell RNA-seq profiling of immune cells from human ovarian carcinoma, renal carcinoma and melanoma samples after 48h of ex vivo culture using the patient-derived tumor fragment platform (5 samples total). Samples were cultured in various conditions, including: untreated, CD8-IL2v-treated, CD8-IL2v + LCKi -treated, aPD1-treated, CD8-IL2v + aPD1 -treated, Untargeted IL2-treated, aCD3-treated and aCD3 + CD8-IL2-treated . FASTQ files contain gene expression data, feature barcode antibody capture or TCR data on immune cells from all conditions combined per patient.

  Dataset EGAD50000000377

• PACA-CA RNASeq bam files

  Bam files for PACA-CA RNA Seq analysis, for DCC release 27

  Dataset EGAD00001003945

• SF4324 Primary Wildtype GBM Female, 57.

  Single Cell RNA-Seq of Primary GBM. Gender Female, Age, 57.

  Dataset EGAD00001006017

• Follicular T cell lymphoma

  Paired-end RNA-seq of follicular T cell lymphoma for the discovery of fusion transcripts

  Dataset EGAD00001006379

• Facioscapulohumeral muscular dystrophy (FSHD): RNA-seq of isogenic TIRM+, TIRM- muscle and PBMCs from patients and matched controls

  FASTQ files describing paired-end RNA-sequencing of isogenic TIRM+ and TIRM- muscle biopsies from 24 FSHD patients (48 samples) and vastus lateralis muscle biopsies from 11 matched control individuals. FASTQ files are also provided describing RNA-sequencing of 15 FSHD peripheral blood mononuclear samples and 14 matched controls. For muscle biopsies sequencing was at 21.7-35.5 million reads/sample. RNA was extracted from PBMCs followed by globin depletion with sequencing at 19.7-46.5 million reads/sample.

  Dataset EGAD00001011077

• RNA-seq data from 27 glioblastoma samples

  27 Fresh frozen tissue specimens were crushed by mortar and pestle, homogenized using the QIAShredder kit (Qiagen), and genomic DNA and total RNA were extracted using the AllPrep DNA/RNA Mini kit (Qiagen), according to the manufacturer’s instructions. RNA libraries were synthesized using 200 ng of total RNA using the Ilumina TruSeq Stranded RNA LT Sample Prep Kit (Illumina), and subsequently sequenced on the NextSeq550 platform to a read depth of 80 million clusters and 160 million paired end reads (75 bp X 75 bp) using V2 chemistry.

  Dataset EGAD00001008362

• RNA seq before and after cold pressor test

  The cold pressor test (CPT) is a widely used pain provocation test to investigate both pain tolerance and cardiovascular responses. Twenty-two females were phenotypically assessed before and after a CPT, and blood samples were taken for RNA-sequencing.

  Study EGAS00001006690

• 110 "KOREAN" never-smoker female adenocarcinoma RNA-seq

  All sequencing was performed within the DNAlink (Korea) by using the Solexa sequencing technology (Illumina, San Diego, CA). mRNA was isolated from total RNA using poly-T oligo-attached magnetic beads and was fragmented with fragmentation buffer to an average size of 300 bp. The libraries were prepared by using TruSeq RNA Library Prep Kit v2 (Illumina) and were sequenced on the Illumina HiSeq2000 using the manufacturer’s recommended protocols

  Dataset EGAD00001005358

• RNA-seq of atypical 3q26 samples

  RNA was isolated using phenol-chloroform extraction followed by DNase digestion or using the Qiagen Allprep DNA/RNA kit and protocol (Qiagen, #80204). cDNA synthesis was done using the SuperScript II Reverse Transcriptase kit (Invitrogen). Quantitative real-time PCR was performed by using primers as described previously13,21 on the 7500 Fast Real-time PCR System (Applied Biosystems). Relative levels of gene expression were calculated using the ΔΔCt method

  Dataset EGAD00001006106

• RNA-seq of multiple myeloma patient samples

  RNA from CD138+ plasma cells from patients with a plasma cell dyscrasia were sequenced using the TruSeq Stranded Total RNA Ribo-zero Gold kit (Illumina). Paired-end 75bp reads were generated on a NextSeq500 or HiSeq4000 (Illumina). The dataset consists of 1 MGUS sample, 5 SMM samples, 69 newly diagnosed myeloma samples, 1 relapsed myeloma sample, 1 previously treated myeloma samples, and 4 PCL samples. Matching whole genome sequencing data are available for these samples under study EGAS00001003164.

  Dataset EGAD00001004543

• Single Cell and Spatial Transcriptomic Profiling of Haemophilus ducreyi Infection

  We investigated the immune response in end-point pustules formed by Haemophilus ducreyi in volunteers using an experimental infection model. Six volunteers were infected in the skin of the upper arm at three sites with 41-85 CFU of H. ducreyi loaded on an allergy testing device; a sham-inoculated (e.g., wound) site was also performed. Five volunteers (4 men and 1 woman; 2 Asians and 3 Whites; aged 27-46 years) formed pustules 6-8 days post infection; 1 volunteer spontaneously resolved all sites. If a volunteer formed pustules, biopsies were performed to collect their pustule and wound sites. Biopsy pairs for all 5 pustule formers were subjected to single cell (sc) RNA-seq. Sequencing libraries were prepared using the 10X Genomics Single-cell 3' RNA-seq kit. Spatial transcriptomics was performed on biopsy pairs from 4 of the 5 pustule formers. Ten micron sections were placed on 10X Genomics Visium slides for fresh-frozen tissue, and libraries were prepared with the 10X Genomics Visium spatial 3' gene expression kit. All samples were sequenced on an Illumina NovaSeq 6000. Count tables were produced with CellRanger and SpaceRanger, respectively, and Seurat was used to analyze the data. We identified 13 major cell types by scRNA-seq; the proportion of some immune cell subsets was increased in pustules compared to wound sites. We also localized the major cell types within the tissue by using the scRNA-seq data to deconvolve the spatial transcriptomic data. The FASTQ files and count tables from CellRanger and SpaceRanger are provided.

  Study phs003754

• Somatic Mutations in Single Human Neurons from Patients with Congenital Neurodegenerative Diseases

  It has been hypothesized that accumulating DNA lesions in neurons contribute to aging and neurodegeneration. Despite their pathophysiological importance, the DNA lesions have not been systematically examined with effective methods. In this study, we developed a computational method for detecting genomic deletions in single-cell whole-genome sequencing (scWGS) data, and analyzed the whole genome of human single neurons. Single neurons were obtained from neurotypical individuals of various ages and from patients with three different congenital neurodegenerative diseases: Ataxia telangiectasia (AT), Cockayne syndrome (CS), and Xeroderma pigmentosum (XP). Single-neuron WGS data of AT brains are released here, and the data of other two diseases are released in a separate dbGaP study (phs001485).To understand the molecular mechanisms underlying AT, we performed single-nucleus RNA-sequencing (snRNA-seq) of postmortem cerebellar vermis and prefrontal cortex from individuals with AT and controls. To genetically confirm the diagnosis of AT, we also performed WGS on postmortem brain tissue from each individual with AT. Induced pluripotent stem cells (iPSCs) from individuals with AT and controls were differentiated into microglia, and the transcriptomes were profiled with bulk RNA-sequencing (RNA-seq).

  Study phs003005

• ChIP-seq in colorectal cancer and paired adjacent normal mucosa

  This dataset includes ChIP-seq data for H3K27ac and H3K4me1 on 20 paired samples of colorectal cancer and adjacent normal mucosa. One tumor sample that failed QC is not available.

  Dataset EGAD00001007707

• Contribution of systemic and somatic factors to clinical response and resistance in urothelial cancer: an exploratory multi-omic analysis

  Patients with metastatic urothelial cancer (n=29) were treated with atezolizumab (anti-PD-L1). All 29 patients had T-cell receptor sequencing (TCR-seq) of the pre-treatment blood; 24 also had TCR-seq on at least one post-treatment blood sample. 24 patients had TCR-seq of their pre-treatment tumors. TCR-seq data can be found at http://doi.org/10.5281/zenodo.546110. 26 patients also had RNAseq of their tumors and whole exome sequencing (WES) of their tumors and matched normal blood. WES results for one sample were excluded from our analysis after failing to meet coverage requirements.

  Study phs001743

• SF10432 Wildtype Primary GBM Female, 50

  Single Cell-RNA Seq of Wildtype Primary GBM for Female, Age 50.

  Dataset EGAD00001006019

• PDAC organoid genomic heterogeneity

  Two primary tumor-derived PDAC organoids were subjected to SNP array, RNA-seq, and single-cell WGS

  Dataset EGAD00010002408

• Validated Single-cell RNA sequencing in early breast cancer

  Single-cell RNA and VDJ sequencing of early breast cancer

  Dataset EGAD00001006608

• Immune Responses in Checkpoint Myocarditis Across Heart, Blood, and Tumor

  Immune checkpoint inhibitors (ICIs) are widely used in anti-cancer therapies, but they can cause morbid and potentially fatal immune-related adverse events (irAEs), such as ICI-related myocarditis (irMyocarditis). The pathogenesis of irMyocarditis and its relationship to anti-tumor immunity remain poorly understood. We sought to define immune responses in heart, tumor, and blood in irMyocarditis patients and controls by leveraging single‐cell RNA sequencing (scRNA‐seq) coupled with T-cell Receptor Sequencing (TCR-Seq). Our analysis demonstrated increased frequencies of cytotoxic T cells, inflammatory mononuclear phagocytes (MNPs), conventional dendritic cells (cDCs), and inflammatory fibroblasts in irMyocarditis heart tissue. Additionally, we revealed decreased frequencies of plasmacytoid dendritic cells, cDCs, and B lineage cells but an increased frequency of MNPs in the blood of irMyocarditis patients. Raw data for heart and blood can be found in dbGaP. All processed data and raw TCRseq data from heart tissue and tumor samples for this study can be found in GEO (Accession number GSE228597).Subject IDs with the prefix "SIC" were collected by the Severe Immunotherapy Complications (SIC) service at MGH due to suspicion of immune-related adverse events. Subject IDs with the prefix "donor" were collected by the MGH Melanoma Biobank at scheduled timepoints; this biobank systematically collects samples from patients at MGH at clinically relevant timepoints.

  Study phs003413

• Transcriptome sequencing of gingivo-buccal oral squamous cell carcinoma for integrative analysis: alterations in expression of genes attributable to methylation changes

  Gingivo-buccal oral squamous cell carcinoma (OSCC-GB) is the most common cancer among men in India and is associated with high mortality. Although OSCC-GB is known to be quite different from tongue cancer in its genomic presentation and its clinical behavior, it is treated identically as tongue cancer. Predictive markers of prognosis and therapy that are specific to OSCC-GB are, therefore, required. To achieve this, we have carried out transcriptome (n=72) profiling of paired tumor-normal tissues collected from OSCC-GB patients from India. RNA sequencing was performed on tumor and paired adjacent normal samples from 72 OSCC-GB patients. From each patient, total RNA was extracted from tumor and normal tissue samples using AllPrep DNA/RNA Mini Kit (QIAGEN). The quality and concentration of isolated total RNA were checked using Agilent 2100 Bioanalyzer and NanoDrop 2000 (Thermo Fisher Scientific). The OD260/OD280 ratio was ≥ 2 and RNA Integrity Number (RIN) was ≥ 7.0 for all sequenced samples. Ribosomal RNA (rRNA) was removed from the RNA samples, using Ribo-Zero Magnetic Kit (Epicentre). Sequencing libraries were prepared from rRNA depleted samples using TrueSeq RNA Sample Preparation Kit (Illumina). Each triplex cDNA library pool was sequenced as 100bp paired-end on HiSeq-2000 or HiSeq-2500 (Illumina). Protocols suggested by the manufacturers were used for all assays.

  Study EGAS00001003893

• MESA colorectal cancer cfDNA EM-seq dataset

  This dataset contains the methylation sequencing data of 60 nonCancer and 70 colorectal cancer cfDNA samples. The methylation library is constructed by using NEBNext Enzymatic-seq Kit.

  Dataset EGAD00001009165

• Characterizing the cell-free transcriptome in a humanized DLBCL patient-derived tumor xenograft model for RNA-based liquid biopsy in a preclinical setting

  This study explores the cell-free transcriptome in a humanized DLBCL patient-derived tumor xenograft (PDTX) model. Blood plasma samples (n=171) derived from a DLBCL PDTX model including 27 humanized (HIS) PDTX, 8 HIS non-PDTX and 21 non-HIS PDTX NOD-scid IL2Rgnull mice were collected during humanization, xenografting, treatment, and sacrifice. The mice were treated with either R-CHOP, huCD20-Fc-AFN-CHOP, or phosphate-buffered saline (PBS). RNA was extracted using the miRNeasy serum/plasma kit and sequenced on the NovaSeq 6000 platform using the SMARTer Stranded Total RNA-seq pico v3 kit.

  Study EGAS50000000566

• Transcriptome (RNA-seq) data for the validation of the glioblastoma progression study (GBMatch).

  37 transcriptomes derived from fresh-frozen glioblastoma tumor samples. These transcriptomes have been produced for validation purposes and match the corresponding RRBS and WGS profiles in that DNA and RNA was extracted from the same tumor samples.

  Dataset EGAD00001004076

• Genomic (WGS) data for the validation of the glioblastoma progression study (GBMatch).

  43 low-coverage genomes derived from fresh-frozen glioblastoma tumor samples. These genomes have been produced for validation purposes and match the corresponding RRBS and RNA-seq profiles in that DNA and RNA was extracted from the same tumor samples.

  Dataset EGAD00001004077

• KNS42 and SF188 H3K36me3 chipSeq

  Chromatin immunoprecipitation (ChIP) was carried out employing antibodies against H3K36me3 and RNA polymerase II using the HistonePath and TranscriptionPath assays by ActiveMotif. Whole genome sequencing was carried out using an Illumina HiSeq2000 and data is provided as 6 BAM files. H3K36me3 chipseq RNA polymerase II chipseq and input coverage for each cell line.

  Dataset EGAD00001004119

• COLONOMICS small RNA sequencing

  This dataset consists of SOLiD small RNA-seq of 250 colorectal samples: 100 tumor tissue samples, 100 normal tissue samples (adjacent to tumor sites) and 50 matched control samples of healthy individuals. CSfasta and qual files converted to single fastq files prior to uploading.

  Dataset EGAD00001004827

• Single cell RNA-Seq of Clear Cell Sarcoma of the Kidney

  Dataset EGAD00001007498

• UTSW ChRCC Cohort 2024

  This DAC controls access to the WES and RNA-Seq data for study: Molecular underpinnings of dedifferentiation and aggressiveness in chromophobe renal cell carcinoma.

  Dac EGAC50000000203

• Time course acetalax bisacodyl treatment

  RNA-Seq raw data of PDX treated with acetalaxor bisacodyl for 4h00 to 24h00.

  Dataset EGAD50000000875

• CPTAC: Proteogenomic Studies of Ovarian Tumor Responses to Agents Targeting the DNA Damage Response

  There is a critical unmet need for predictors of chemo-refractory High-grade serous ovarian cancer (HGSOC). Despite over 3 decades of research on platinum responses in cancer, no predictive biomarker has been translated into clinical use. Predictors of refractory disease could spare these patients the unnecessary toxicity of a platinum-based regimen and provide a means to triage these patients to clinical trials to identify effective therapies for refractory disease. This study has approached the development of a predictor in a novel way enabling detection of a multi-analyte panel biomarker capable of detecting a subset of refractory HGSOCs with high specificity and implicating potential treatment vulnerabilities for refractory disease. We reported the first proteogenomic analysis of platinum refractoriness in HGSOC and made the novel dataset available as a resource to the community, including a ProTrack portal: http://ptrc.cptac-data-view.org/. Detailed proteogenomic profiles were generated for this study from a retrospective cohort of 242 treatment-naive HGSOCs with enriched representation of "exceptional non-responders" (i.e., patients with chemo-refractory disease). Whole genome sequence (WGS) and RNA seq FASTQ files are available through dbGaP. Proteomic data are available through the NCI Proteomic Data Commons (PDC): https://pdc.cancer.gov/pdc/.

  Study phs003152

• Molecular determinants of response to PD-L1 blockade across tumor types

  Immune checkpoint inhibitors targeting the PD-1/PD-L1 axis lead to durable clinical responses in subsets of cancer patients across multiple indications, including non-small cell lung cancer (NSCLC), urothelial carcinoma (UC) and renal cell carcinoma (RCC). Herein, we complement PD-L1 immunohistochemistry (IHC) and tumor mutation burden (TMB) with RNA-seq in 366 patients to identify unifying and indication-specific molecular profiles that can predict response to checkpoint blockade across these tumor types. Multiple machine learning approaches failed to identify a baseline transcriptional signature highly predictive of response across these indications. Signatures described previously for immune checkpoint inhibitors also failed to validate. At the pathway level, significant heterogeneity was observed between indications, in particular within the PD-L1+ tumors. mUC and NSCLC were molecularly aligned, with cell cycle and DNA damage repair genes associated with response in PD-L1- tumors. At the gene level, the CDK4/6 inhibitor CDKN2A was identified as a significant transcriptional correlate of response, highlighting the association of non-immune pathways to the outcome of checkpoint blockade. This cross-indication analysis revealed molecular heterogeneity between mUC, NSCLC and RCC tumors, suggesting that indication-specific molecular approaches should be prioritized to formulate treatment strategies.

  Study EGAS00001004343

• Ribosomal Depleted Total RNA-Seq of PBMCs and Skin from Controls and Systemic Sclerosis Patients

  This study involved prospective collection of skin biopsies and peripheral blood mononuclear cell (PBMC) samples from controls with no self-reported history of autoimmune or inflammatory disease and cases with Rheumatologist-confirmed systemic sclerosis: limited cutaneous systemic sclerosis (lcSSc), diffuse cutaneous systemic sclerosis (dcSSc), very early diagnosis of systemic sclerosis (VEDOSS), and systemic sclerosis sine scleroderma (SSS). Some SSc cases were sampled at a 6 month routine follow-up visit. PBMCs were collected and lysed immediately. Skin punches were stabilized in RNAlater until extraction. All RNA-Seq libraries were created using Takara/Clontech ribosomal depletion kits, and sequenced on either a HiSeq2500 or HiSeq3000.

  Study phs002902

• BLUEPRINT RNA-seq data for common cells in the haematopoietic lineages, from adult and cord blood samples.

  RNA-seq data for common cells in the haematopoietic lineages, from adult and cord blood samples.

  Study EGAS00001000327

• Childhood Cancer Data Initiative (CCDI): Comprehensive Genomic Sequencing of Pediatric Cancer Cases (CMRI/KUCC)

  This study provides paired tumor normal genomic sequencing data from approximately 200 children with cancer, including both solid tumors and leukemias, done by the Children’s Mercy Research Institute (CMRI) and University of Kansas Cancer Center (KUCC). These data include whole genome sequencing (generally, ~20x), whole exome sequencing (generally, ~300x), bulk RNA sequencing (generally, ~80 million reads), and single-cell RNA and ATAC sequencing (>50,000 reads/cell). Additional phenotypic, pathologic, and genetic data, gathered clinically for these samples, are also provided.

  Study phs002529

• Non-coding RNAs in breast cancer

  Using RNA CaptureSeq we annotated non-coding RNAs transcribed from genome intervals surrounding breast cancer risk signals in a range of mammary-derived tissue and cell lines.

  Study EGAS00001003353

• Single-Cell and Spatial Multi-Omics Highlight Effects of Anti-Integrin Therapy Across Cellular Compartments in Ulcerative Colitis

  This is a focused, nested case-control study within our larger cohort "Immunoprofiling of the Blood and Intestine and Creation of a Gut Cell Atlas". This sub-study is titled as "Single-cell and spatial multi-omics highlight effects of anti-integrin therapy across cellular compartments in ulcerative colitis”. We examined the impact of Vedolizumab (VDZ), an anti-integrin antibody therapy, on the cellular landscape of ulcerative colitis (UC). While VDZ is primarily recognized for its role in preventing lymphocyte migration to the gut, the extent of its influence on other cellular populations has not been fully characterized. We used single-cell RNA sequencing (scRNA-seq) and cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) to profile cells from both the blood and colon tissue samples. We pooled single-cell suspensions together before running scRNA-seq and CITE-seq, and subsequently deconvoluted the samples using the freemuxlet and demuxlet algorithms and variant call files (vcf) from bulk RNA-seq. This allowed us to assign cells to individual study subjects. We compared the cellular compositions of healthy individuals to those of UC patients undergoing treatment with VDZ or mesalamine (5-aminosalicylic acid/5-ASA). Our results revealed that VDZ induces significant changes in the variety and dynamics of mononuclear phagocytes within both the bloodstream and intestinal tissue, accompanied by subtle variations in lymphocyte populations. The dbGaP submission will provide raw sequencing data and participant phenotype data regarding disease and treatment status.

  Study phs003502

• NKI-AvL CRC-OVC DNA-seq

  The dataset “NKI-AvL CRC-OVC DNA-seq" includes 4 normal and 4 tumor BAM files from paired-end whole exome sequencing on Illumina HiSeq2500 and Illumina NovaSeq6000 for 2 colorectal cancer and 2 ovarian cancer patients.

  Dataset EGAD00001004340

• Patient-derived lung cancer organoids

  Patient-derived lung cancer organoids cram files : targeted seq 13 samples, whole exome seq 12 samples mutation profiles of PDO and matched tissue : aggregated vcf 1 file details : https://www.nature.com/articles/s41467-019-11867-6

  Dataset EGAD00001005317

• CITE-seq of early breast cancer

  CITE-seq of early breast cancer samples.

  Dataset EGAD00001007058

• Extracellular transcriptome in seminal plasma for non-invasive prostate cancer diagnosis

  A diagnostic non-invasive biomarker test for prostate cancer at an early stage, with high sensitivity and specificity, would improve diagnostic decision making. Extracellular RNAs present in seminal plasma might contain biomarker potential for the accurate detection of clinically significant prostate cancer. So far, the extracellular messenger RNA (mRNA) profile of seminal plasma has not been interrogated for its biomarker potential in the context of prostate cancer. Here, we investigate the mRNA transcriptome in seminal plasma samples obtained from prostate cancer patients (n=25), patients with benign prostate hyperplasia (n=26) and individuals without prostatic disease (n=6). Seminal plasma harbors a complex mRNA repertoire that reflects prostate as its tissue of origin. The endogenous RNA content is higher in the prostate cancer samples compared to the control samples. Prostate cancer antigen 3 (PCA3), a long non-coding RNA with prostate cancer-specific overexpression, and ATP-binding cassette transporter 1 (ABCA1), known to be involved in the prostate cancer pathogenesis, were more abundant in the prostate cancer group. In addition, twelve high confidence fusion transcripts could be detected in prostate cancer samples, including the bona-fide prostate cancer fusion transcript TMPRSS2-ERG. Our findings provide proof-of-principle that the extracellular transcriptome of seminal plasma can reveal information of an underlying prostate cancer.

  Study EGAS00001005277

• Recurrent somatic mutations in POLR2A define a distinct subset of meningiomas: RNAseq variants

  Variants called from RNA-seq data of meningioma tumors.

  Dataset EGAD00001002649

• Berlin Neuroblastoma Dataset

  Paired tumor/normal WGS and RNA-seq of primary neuroblastoma.

  Dataset EGAD00001005488

• Covacta RNAseq merged EGA metadata

  Sample metadata for the RNA-seq dataset. This dataset includes subject-level data and longitudinal visit day information for the corresponding samples.

  Dataset EGAD00001011162

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

  This dataset includes whole transcriptome data of human stimulated and cultured CD4+ Treg cells (39 samples).

  Dataset EGAD00001005964

• RNA-seq data of CRC-PDX tumors

  We obtained bulk RNAseq data of CRC-PDX tumors and performed molecular subtype classification.

  Dataset EGAD50000000850

• Single cell RNA sequencing of colorectal cancer

  To understand intrinsic cancer cell signatures and the surrounding microenvironemt and their interactions, we performed single-cell RNA sequencing on 63,689 cells from 23 patients with 23 primary colorectal cancer and 10 matched normal mucosa samples. Analyzing of primary colorectal cancer and normal mucosa samples show a comprehensive cellular landscape of colon cancer, which is a valuable resource for the development of therapeutic strategies.

  Dataset EGAD00001005198

• Pancreatic cancer RNA sequencing

  Study EGAS00001004706

• Tumor detection by analysis of both symmetric- and hemi-methylation of plasma cell-free DNA

  Aberrant DNA methylation plays a critical role in tumorigenesis. While DNA methylation has been used for cancer detection and classification, DNA hemi-methylation, a novel epigenetic mark has not been analyzed extensively in cancer epigenomes. Here we report a strand-specific (ss) sequencing method (MeDIP-Seq) for plasma cell free (cf) DNA (sscf-MeDIP-Seq), which can analyze both symmetrically methylated DNA regions (DMRs) as well as hemi-methylated regions (DHMRs). Using the sscf-MeDIP-Seq method, we analyzed plasma cfDNA methylomes of 271 samples from subjects with liver cancer and brain cancer and from individuals without cancer (controls). Among them, 215 samples were chosen as the discovery cohort for the identification of DMRs and DHMRs specific in each subject group and for the training of machine learning models of multi-cancer detection (MCD) using DMRs, DHMRs and DMRs+DHMRs as inputs. These models were then used to predict the 56 samples in the validation cohort. We found that models trained with DMRs+DHMRs as inputs in general outperformed models trained with DMRs or DHMRs alone, with AUROC being 0.971, 0.981, and 0.99 in predicting control, liver and brain cancer samples in the validation cohort, respectively, by the DMR+DHMR-trained models.

  Study phs003462

• Cellular and Molecular Characterization of Renal Cell Carcinoma

  We are performing a comprehensive cellular and molecular characterization of renal cell carcinoma. This work includes an initial cohort of patients whose tumors (and adjacent normal tissue) underwent single cell analysis. Single-cell RNA sequencing (scRNA-seq) and TCR sequencing (scTCR-seq) analysis of untreated clear cell renal cell carcinoma tumor and adjacent normal tissue was performed across disease stages. This initial cohort includes 13 patients: 4 with early stage disease (stage I/II), 4 with locally advanced disease (stage III), and 5 with advanced/metastatic disease (stage IV). Whole exome sequencing on tumor and normal tissue was also performed. 

  Study phs002252

• The Effect of the Menstrual Cycle on DNA Expression in the Normal Human Breast Epithelium

  The Susan G. Komen for the Cure® Tissue Bank at the IU Simon Cancer Center [www.komentissuebank.iu.edu] (KTB) was established expressly for the prospective collection of normal, healthy breast tissue from volunteer donors. Blood is also obtained from donors at the time of donation and is processed for serum, plasma and peripheral blood leukocyte DNA. Specimens are annotated and data includes age, race, ethnicity, personal health history, family cancer history, medication usage at the time of donation, and breast cancer risk factors. Premenopausal donors to the KTB were identified by a query of the Bank's database. Hematoxylin and eosin stained sections of the formalin-fixed paraffin-embedded tissue of the identified donors were reviewed and tissue was graded on the basis of the abundance of epithelium within the section. Only tissue containing abundant epithelium was considered for this study. Based on dates, the specimens of nine women in the follicular phase of the menstrual cycle and five in the luteal phase were chosen. Six donors using hormonal contraception at the time of donation were also included. Whole blood obtained from 19 of the 20 donors at the time of tissue donation was available and it was processed for serum. Estradiol, estriol, luteinizing hormone and progesterone concentrations were determined by the Indiana University Health Pathology Laboratory using a Beckman Unicel DxI 800 Immunoassay System. The phase of the menstrual cycle was verified by serum progesterone concentration. The epithelium of these 20 specimens was microdissected from multiple 8 micron frozen tissue sections. Total RNA extracted from the tissue was subsequently depleted of rRNA via locked nucleic acid probes. This enabled profiling of both poly-A and non-poly-A RNA species. Barcoded cDNA libraries from the 20 normal breast epithelia were prepared and sequenced on an Applied Biosystems (AB) SOLiD3 or SOLiD 4 platform. RNA-seq reads for each sample were then mapped to the human genome (hg19) using the LifeScope software version 2.5.1 (Life Technologies, Foster City, CA) and BAM (Binary Alignment/Map) files generated. Read counts for each gene were derived from the output BAM files using the RefSeq database (UCSC Genome Brower) as the gene model.

  Study phs000644

• Innate and Adaptive Immunity in Parkinson Disease-P20

  Increasing evidence supports the role of brain and systemic inflammation in the etiology of Parkinson disease (PD). We used gene expression profiling (RNA-seq) to examine the activation state of peripheral blood monocytes in 18 patients with early, untreated PD and 16 healthy control (HC) subjects. Monocytes were isolated by negative selection, and gene expression studied by RNA-seq and gene set enrichment analysis. A computational model that incorporated case/control status, sex, and the interaction between case/control status and sex was utilized. We found that there was a striking effect of sex on monocyte gene expression. There was inflammatory activation of monocytes in females with PD, with enrichment of gene sets associated with interferon gamma stimulation. In males, the activation patterns were more heterogeneous. These data point to the importance of systemic monocyte activation in PD, and the importance of studies which examine the differential effects of sex on pathophysiology of the disease.

  Study phs002063

• The transcriptome and DNA methylome profiling of the early human post-implantation embryos

  whole genome sequencing data of parent blood samples. Single cell full-length RNA-seq and PBAT-Seq data of in vitro culture D6 to D14 human embryo.

  Dataset EGAD00001005137

• MPRA-SCZ

  RNA-Seq and ATAC-Seq of iPSC derived neurons under baseline and KCl stimulation conditions from 10 distinct donors, including 5 healthy controls and 5 schizophrenic individuals. scATAC of human post mortem prefrontal cortex from 4 adult individuals including 2 neurotypical individuals and 2 schizophrenic individuals.

  Dataset EGAD00001011335

• Genetic regulation of gene expression in human brain cell types

  We leveraged single nuclei RNA-seq from 192 human brain samples to map cis-eQTLs in 8 brain cell types. We found extensive cell-type specific genetic effect on gene expression and integrated our results with GWAS to identify putative novel risk genes for brain disorders and the cell types in which the disease mechanisms are likely active.

  Study EGAS00001006345

• RNA-Seq data for the paper titled "Orthotopic Patient-Derived Xenografts of Pediatric Solid Tumors"

  RNA-Seq data for the paper titled "Orthotopic Patient-Derived Xenografts of Pediatric Solid Tumors"

  Dataset EGAD00001003433

• Epigenome cohort 30 Patient DNA and RNA

  This dataset includes RNA-seq, DNA and Chip-Seq data of samples from our paper.

  Dataset EGAD00001009041

• Multi-omic dataset of neuroendocrine neoplasm organoids

  This dataset corresponds to one of the first biobanks for the understudied neuroendocrine neoplasms from multiple grades and body sites (lung, pancreas, small intestine). It contains whole-genome sequencing data for original tumors, patient-derived tumor organoids at multiple passages, and matched normal tissue, and RNA-seq data for the original tumor and patient-derived tumor organoids.

  Study EGAS00001005752

• Whole-transcriptome characterization of cell-free RNA (cfRNA) in cancer and non-cancer patients

  Whole-transcriptome characterization of cfRNA in cancer (stage III breast [n=46], lung [n=30]) and non-cancer (n=89) participants from the Circulating Cell-free Genome Atlas (NCT02889978). Dataset includes collapsed BAM files for plasma cfRNA from each patient, as well as collapsed BAM files for RNA from matched tumor tissue (when available).

  Dataset EGAD00001006484

• Gene Expression Study of Individuals with Sex Chromosome Aneuploidies

  Males and females show dramatic differences in their vulnerability to the same diseases. For example, compared to men, lupus is six times more prevalent, thyroid cancer is three times more prevalent, and unipolar depression is twice as prevalent in women. Diseases with a strong male bias include autism (5:1), dilated cardiomyopathy (3:1), and ankylosing spondylitis (5:1). Historically, such differences have been attributed solely to extrinsic factors such as circulating sex hormones or environmental influences. We hypothesized that intrinsic factors - genetic differences between XX and XY cells - have unappreciated biological consequences throughout the body and contribute to sex differences in disease incidence and severity. This hypothesis stems from our long-term effort to sequence the sex chromosomes of diverse mammalian species, which has identified a set of homologous genes on the X and Y chromosomes that are dosage-sensitive, expressed throughout the body, and encode regulators of chromatin modification, transcription, translation, and protein stability. These X- and Y-encoded genes differ in sequence and expression pattern, which likely manifests in genome-wide differences in gene regulation between XX and XY cells and influences all aspects of human biology, including sex differences in disease susceptibility. These hard-wired molecular sex differences have been largely overlooked and understudied, representing a significant gap in our knowledge of human biology.The gene expression study of individuals with sex chromosome aneuploidies takes advantage of natural human variation in sex chromosome number, i.e. sex chromosome aneuploidy, to investigate alterations in genome-wide gene expression that correlate with changes in X- and Y-chromosome dosage. We analyzed samples from 114 individuals with a variety of sex chromosome aneuploidies, including 45,X; 47,XXY; 47,XYY; 47,XXX; 48,XXYY; and 49,XXXXY. We generated lymphoblastoid cell lines (LCLs) from blood samples and, in some cases, fibroblast cultures from skin biopsies. We supplemented our collection with previously-derived cell lines. To evaluate gene expression, we performed deep profiling of the transcriptome (RNA-seq) from these LCLs and fibroblasts. We performed parallel analyses on samples collected from 62 control 46,XX and 46,XY individuals, 6 individuals with trisomy 21, and 14 individuals with structural variations of the X and Y chromosomes. In addition, we performed CRISPRi knockdowns on 3 of the 46,XX and 3 of the 46,XY fibroblast samples for the homologous transcription factors ZFX and ZFY, encoded on the X and Y chromosomes, respectively.In the April 2024 update, we added RNA-seq datasets derived from isolated CD4+ T cells and monocytes from 76 and 72 adults, respectively, with the following sex chromosome constitutions: 45,X; 46,XX; 46,XY; 47,XXX; 47,XXY; 47,XYY. These individuals are largely a subset of the same cohort described above. In addition, we performed RNA-seq on in-vitro stimulated CD4+ T cells with the following sex chromosome constitutions: 45,X; 46,XX; 46,XY; 47,XXY.In the August 2024 update, we added RNA-seq datasets generated from the following: 1) LCLs derived from individuals with AZFa deletions of the Y chromosome, 2) DDX3X and DDX3Y knockdown (via CRISPRi) in XY fibroblasts, and 3) 5-ethyl uridine (5-EU) treatment in XY and XYYYY LCLs.

  Study phs002481

• PACA-CA RNASeq fastq files

  Fastq files for PACA-CA RNA Seq analysis, for DCC release 27

  Dataset EGAD00001003972

• scRNA primaries

  Single cell RNA-seq for primary samples

  Dataset EGAD00001006135

• Long-term organoid culture of a small intestinal neuroendocrine tumor

  organoid and tissue bam files from rna-seq experiment

  Dataset EGAD00001010175

• RNAseq data

  RNA-seq data from PAXgene extracted whole blood of patients enrolled in the COVACTA trial. This dataset includes raw FASTQ files.

  Dataset EGAD00001011168

• Medulloblastoma dataset

  This dataset contains a tumor + normal DNA sequence data and tumor RNA seq data for a medulloblastoma patient.

  Dataset EGAD50000000384

• DAC Ghent University - Department of Movement and Sports Sciences

  DAC of Ghent University for RNA-seq data of human skeletal muscle biopsies collected at the Department of Movement and Sports Sciences

  Dac EGAC50000000263

• RNAseq counts

  RNA-seq data from ILC samples. This dataset includes raw, unnormalized counts per gene, per sample.

  Dataset EGAD50000000826

• DAC - Department of Periodontology, University of Gothenburg, Sweden

  Data Access Committee to manage external requests. Project: RNA-seq data from soft tissue biopsies harvested from dental implant sites with peri-implantitis

  Dac EGAC50000000241

• Transcriptome sequencing of cancer cell lines

  This dataset contains RNA sequencing data for 675 cancer cell lines. RNA libraries were made with the TruSeq RNA Sample Preparation kit (Illumina) according to the manufacturer protocol. The libraries were sequenced on an Illumnia HiSeq 2000

  Dataset EGAD00001000725

• RNA-seq of iPSC-derived microglia treated with miRNA mimics and inhibitors

  Microglia were derived from iPSCs and treated with mimics and inhibitors of the miRNAs hsa-miR-150-5p, hsa-miR-193a-3p and hsa-miR-19b-3p. RNA-sequencing was then performed to examine the effects of up- and down-regulation of the respective miRNAs.

  Dataset EGAD00001006842

• Paired RNA-Seq data from 17 samples of different tumors

  Paired RNA sequencing data (21 runs/ 17 samples) of different tumors. The samples were prepared using the Illumina TruSeq stranded mRNA Kit. The sequencing was done on Illumina HiSeq 4000.

  Dataset EGAD00001009706

• DNA methylation database for gynecological cancer detection, classification and assay development

  DNA methylation changes are associated with cancer the best predictor of the presence of cancer. In order to detect and classify gynecological cancer, we performed MeD-seq to generate DNA methylation profiles of vulvar, cervical, endometrial, fallopian tube and ovarian cancers and their associated healthy tissues. DNA methylation profiles were used to find general cancer, regional cancer and specific cancer biomarkers that can be used for cancer detection, classification and treatment monitoring.

  Study EGAS50000000417

• 28 RNA-Seq from CAF-S1, CAF-S4 and EPCAM cells coming from Primary tumors and Lymph nodes of 5 patients)

  Dataset EGAD00001005744

• bulkRNA

  Bulk RNA-seq for cALL patient-derived PDX samples

  Dataset EGAD00001006133

• RNAseq RPKM

  RNA-seq data from ILC samples. This dataset includes counts normalized for sequencing depth and gene length.

  Dataset EGAD50000000828

• RNA sequencing of high hyperdiploid and ETV6/RUNX1-positive pediatric acute lymphoblastic leukemia

  RNA-sequencing data of pediatric B-cell precursor acute lymphoblastic leukemia, including 18 high hyperdiploid cases and 9 ETV6/RUNX1-positive cases. Sequencing libraries were constructed using the Human Ribo-Zero rRNA Removal Kit (Illumina, San Diego, CA) and sequenced on an Illumina NextSeq 500. RNA sequencing data were processed using the TCGA mRNA-seq pipeline (https://docs.gdc.cancer.gov/Data/Bioinformatics_Pipelines/Expression_mRNA_Pipeline/#mrna-analysis-pipeline).

  Dataset EGAD00001004176