14970 results for "cancer studies using rna-seq"

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• COVID-19 Multiomics Atlas

  We provide a single-nuclei RNA-sequencing (snRNA-seq) dataset derived from four COVID-19 patients, generated using the 10x Chromium Next GEM Single Cell v3.1 kit. For our study, these were integrated with snRNA-seq data with 12 publicly available sc/snRNA-seq datasets, comprising organ donor lung samples (n=89) and COVID-19 lung tissue samples (n=51). Additionally, we provide a spatial transcriptomic dataset characterizing different histopathological stages of diffuse alveolar damage, across a cohort of 33 COVID-19 patients. This was generated using the Nanostring Whole Transcriptome Assay (WTA) with regions of interest (ROIs) sized 400 µm² each. This integrated multi-omics analysis of snRNA-seq, histology, and spatial transcriptomics data, is available for exploration and download via our web portal: https://covid19-multiomicatlas.cellgeni.sanger.ac.uk/.

  Dataset EGAD00001015404

• 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

• Transcriptional profiles of Kleefstra syndrome (EHMT1 and EHMT2) and healthy fibroblasts

  This dataset contains FASTQ files from RNA sequencing (RNA-seq) of fibroblasts derived from a healthy donor (control), a patient with Kleefstra syndrome (KSP), and a patient carrying a pathogenic variant in EHMT2 (P2). Ribosomal RNA was removed using an RNase H–based depletion method, and strand-specific libraries were prepared for paired-end sequencing on the MGI DNBSEQ PE100 platform.

  Dataset EGAD50000002343

• RNAseq of human fetal pancreas development

  The dataset comprises RNA-seq information of 4 subpopulations sorted from human fetal pancreas of 3 different donors. Low input libraries were generated using the Smart-seq2 protocol after Ampure XP cleanup of the total RNA extracted from the sorted cells. Libraries were multiplexed and sequenced paired-end over 2 lanes of HiSeq4000 each. Raw data was aligned to the human genome refernence GRCh37 using STAR v2.5.1b with GENCODE v19 as transcriptome reference, and unaligned reads were folded into the final uploaded bams.

  Dataset EGAD00001004210

• FFPE cohort with RNA-seq data of tumor samples

  This dataset contains RNA-seq raw data in fastq format from 14 tumor samples. The samples are from primary tumors or metastasis and represent various cancer entities. The samples are formalin-fixed paraffin-embedded (FFPE) treated. For target enrichment SureSelect XT Human All Exon V6 was used. The libraries were sequenced in paired-end mode (2 x 50 nt) on a NovaSeq6000 S2 flow cell.

  Dataset EGAD00001006781

• MOSAIC Window - Bladder dataset

  This dataset will include Spatial Transcriptomics, Single-Cell RNA-Seq, Bulk RNA-Seq, Clinical data, WES, and H&E data from 15 Muscle-invasive Bladder Cancer patients, treated with upfront cystectomy. Researchers from private or public institutions outside the MOSAIC Consortium will be able to apply to access this data and, pending approval, use the data for their research.

  Dataset EGAD50000000967

• MOSAIC Window Bladder Data

  This dataset will include Spatial Transcriptomics, Single-Cell RNA-Seq, Bulk RNA-Seq, Clinical data, WES, and H&E data from 15 Muscle-invasive Bladder Cancer patients, treated with upfront cystectomy. Researchers from private or public institutions outside the MOSAIC Consortium will be able to apply to access this data and, pending approval, use the data for their research.

  Dataset EGAD50000001251

• RNA-seq from PDAC samples

  Bam and fastq files from RNA-seq of PDAC samples described in Transcription phenotypes of pancreatic cancer are driven by genomic events events during tumour evolution

  Dataset EGAD00001005799

• PanCurX Translational Research Initiative - RNA-Seq mapped and unmapped reads

  Integration of Genomic and Transcriptional Features in Pancreatic Cancer Reveals Increased Cell Cycle Progression in Metastases - RNA-Seq mapped and unmapped reads

  Dataset EGAD00001004548

• Research of factors related to diagnosis, progression, prognosis and treatment of hepato-biliary-pancreatic malignancies

  Advanced cancers with metastasis and/or recurrence are usually resistant and refractory to treatment. In our studies, whole exome sequencing analysis, comprehensive epigenetic analysis and genome-wide expression analysis were performed using cancerous and non-cancerous tissues derived from multicentric cohort study of hepatocellular carcinoma (HCC). The aim of the studies is identification of the refractoriness-related deriver genes for application to novel molecular targeted therapy and preventive medicine. The studies are intended for refractory HCC. High frequency of the tumor recurrence even after curative resection is one of the major difficulties in the treatment of HCC. According to our previous studies, not the recurrence itself, but the recurrence pattern has critical effects on prognosis of the patient with HCC. Then, we analyzed the cancerous and non-cancerous tissues of primary HCC on the point of the recurrence patterns in accordance with or without Milan criteria. The materials were obtained from thirty three patients underwent curative hepatectomy for HCC at Department of Hepato-Biliary-Pancreatic Surgery, Tokyo Medical and Dental University Hospital. Written informed consent from these patients, as well as the institutional review board approved was obtained. The determination of the refractory HCC group (16 cases) was based on the point of the recurrence patterns in accordance with Milan criteria for the recurrent tumor (solitary <5cm, or up to 3 nodules <3 cm, without major vascular invasion or distant metastasis) that has been proposed as the useful criteria of the liver transplantation for HCC. The cellular DNA was extracted from the cancerous and non-cancerous tissues of primary HCC by the phenol-chloroform method. After SNP certification using Genome-Wide Human SNP Array 6.0 (Affymetrix), whole exome sequencing was performed at the Cancer Institute of JFCR, as the support infrastructure. Exome sequencing was performed using HiSeq 2000 (Illumina), and the obtained reads were mapped to the human reference genome (hg19) using BWA software. GATK software was used for local realignment base call recalibration. Single nucleotide variants (SNVs) and indels were analyzed by MuTect and SomaticIndelDetector, as well as visual confirmation by IGV software.

  Study JGAS000052

• Pancreatic Cancer Case Control Association Study

  Pancreatic cancer is the fourth leading cause of cancer death in the United States. This is in large part due to the rapidly fatal course of this disease, as the vast majority of patients die within months of diagnosis and the five-year survival rate is less than 5. We have brought together over 8000 participants from 9 studies of pancreatic cancer, to conduct a GWAS of pancreatic cancer. The studies were drawn from the Pancreatic Cancer Case-Control consortium and include case-control studies from the United States, Europe and Australia. Sites include: Johns Hopkins National Familial Pancreas Tumor Registry, Mayo Clinic Biospecimen Resource for Pancreas Research, Ontario Pancreas Cancer Study (OPCS), Yale University, MD Anderson Case Control Study, Queensland Pancreatic Cancer Study, University of California San Francisco Molecular Epidemiology of Pancreatic Cancer Study, International Agency of Cancer Research and Memorial Sloan Kettering Cancer Center.

  Study phs000648

• Single-Cell Atlas of Human Liver and Blood Immune Cells Across Fatty Liver Disease Stages

  The goal of the study was to investigate immunological correlates of human fatty liver disease progression. We generated a single-cell RNA-seq (scRNA-seq) atlas of immune cells from liver fine needle aspirates (FNAs) and paired peripheral blood mononuclear cells (PBMCs) from a full-spectrum Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD)/Metabolic Dysfunction-Associated Steatohepatitis (MASH) human cohort, using the 3' 10X Genomics platform. Using computational analyses to assess changes in cellular frequencies and function, we found heightened immunoregulatory programs with profibrotic potential alongside a shift from antigen-specific to natural killer cytotoxic functions in the liver with MASH progression. Available data include raw single-cell transcriptomic data (FASTQ files) for each sample type (PBMC, FNA) per patient alongside clinical and histological measurements of fatty liver disease.

  Study phs004044

• Breast Cancer Single-Cell RNA-Seq Dataset

  Single-cell RNA-Sequencing of 26 primary breast cancers from Wu et al. (2021) study. Data was generated using the Chromium controller (10X Genomics) and sequenced on the NextSeq 500 platform.

  Dataset EGAD00001007495

• Citeseq of human bone marrow

  CITE-seq dataset of human bone marrow from four healthy donors. Single-cell RNA sequencing was performed using the 10x Genomics 3’ v3 platform. Approximately 7,000–10,000 cells were loaded in each 10x channel, after which the single-cell libraries were prepared according to manufacturer’s instructions, except for the added CITE-seq steps. Demultiplexed FASTQ files are provided.

  Dataset EGAD50000001211

• Whole Transcriptome Sequencing Data of prDLBCL

  We used sequenced 30 prDLBCL samples using RNA-seq to evaluate possible fusion events and to get expression profiles.

  Dataset EGAD50000000592

• Profiling human first-trimester neurodevelopment using scATAC-seq and multiomics

  116 single cell ATAC runs and 23 single cell multiome (ATAC+RNA) runs on various brain regions during human first-trimester development.

  Dataset EGAD00001011300

• RNAseq of pre- and post-5AZA-treated head and neck cancer patients refractory to anti-PD-1 therapy

  RNA sequencing (RNA-seq) was performed on baseline (before low-dose 5-aza treatment) and on-treatment (low-dose 5-aza treatment for 5 or 10 days) tumor samples from eight participants with head and neck cancer who were refractory to anti-PD-1 therapy. RNA library preparations, sequencing reactions, and initial bioinformatics analyses were conducted at GENEWIZ, LLC. In total, 16 150-bp pair-end RNAseq data were generated.

  Dataset EGAD50000001010

• Pulldown_cytosine_deaminases

  We are looking at the causal factors behind hyper-mutator phenotypes found in previous Breast Cancer sequencing studies.

  Study EGAS00001000233

• Gene Expression of Small Cell Carcinoma of the Ovary-Hypercalcemic Type (SCCOHT)

  Small cell carcinoma of the ovary-hypercalcemic type (SCCOHT) is a rare and aggressive form of ovarian cancer afflicting young women at a median age of 24 years. SCCOHTs are characterized by loss of protein expression of SWI/SNF chromatin remodeling ATPases SMARCA4 and SMARCA2 through mutation and epigenetic silencing, respectively. This study aims to establish gene expression profiles of this cancer through RNA-Seq of fourteen pathologically confirmed cases of SCCOHT tumors.

  Study phs001528

• Common Variant GWAS, Genetics & Epidemiology of Colorectal Cancer Consortium (GECCO)

  Genetics &#38; Epidemiology of Colorectal Cancer Consortium (GECCO) is a collaborative effort which aims to accelerate the discovery of colorectal cancer-related variants by discovering, replicating and fine-mapping Genome Wide Association Study (GWAS) findings, conducting a meta-analysis of GWAS data, and investigating how genetic variants are modified by environmental risk factors. The coordinating center for this consortium is based at the Fred Hutchinson Cancer Research Center (Principal investigator: Ulrike Peters). The GECCO Consortium is utilized in the following dbGaP individual studies. To view genotypes, and derived variables collected in these individual studies, please click on the following individual studies below or in the "Sub-studies" box located on the right hand side of this top-level study page phs001078 GECCO Consortium. phs000965 VITAL phs001056 DALS phs001077 WHI Colorectal Cancer phs001092 PMH CCFR phs001094 PLCO phs001104 ASTERISK phs001113 DACHS phs001114 HPFS phs001128 PHS phs001129 NHS phs001170 Colo2and3 phs001171MEC Colorectal Cancer

  Study phs001078

• Cell Type-Specific and Disease-Associated eQTL in the Human Lung

  This study was conducted to investigate the genetic control of gene expression in a cell-type and context-specific manner in the human lung. We performed single-cell RNA-sequencing (scRNA-seq) of lung tissue from 66 Interstitial Lung Disease (ILD) cases and 48 unaffected donors. Employing a pseudo-bulk approach, we mapped expression quantitative trait loci (eQTL) across 38 cell types. The scRNA-seq data presented here include previously published (PMID 34262047) and unpublished samples. ILD tissue samples were obtained from lungs removed at the time of lung transplantation at either Vanderbilt University Medical Center (VUMC) or the Norton Thoracic Institute (NTI). Control tissue samples were obtained from lungs declined for organ donation either at the Donor Network of Arizona (DNA) or VUMC. The self-reported ethnicities of donors were 66.7% European, 9.6% African American, 17.5% not available (N/A), and 6.1% other. The smoking history includes 46.5% ever smoker, 29.8% never smoker, 23.7% N/A. For genotyping, flash-frozen tissue in DNA/RNA shield was homogenized via a bullet blender. Genomic DNA was extracted using Zymo Quick DNA/RNA microprep plus kit. Library preparation and low-pass Whole Genome Sequencing (WGS) were carried out at TGen or by Gencove Inc. At TGen, libraries were prepared using PCR-free Watchmaker kits (Watchmaker Genomics) with 200 ng input. Genomes were sequenced on NovaSeq at low coverage (typically 0.4&#8211;1x). The resulting sequence data were processed and imputed using Gencove's imputation platform.

  Study phs003521

• Targeted Long-Read Sequencing of the Ewing Sarcoma 6p25.1 Susceptibility Locus

  Ewing Sarcoma (EwS) is rare but the second most common cancer in children, adolescents and young adults. Recent studies suggest germline variation in or around GGAA microsatellites may interact with fusion oncoprotein binding causing changes in binding affinity and potentially impacting enhancer activity on nearby target genes. This study aims to better understand germline variation around EwS susceptibility regions by performing long-range haplotype sequencing of these regions using PacBio sequencing. Our analysis focused on characterizing variation in GGAA microsatellite length as well as germline variants in or around the microsatellite and their association with EwS risk.

  Study phs003159

• Breast Cancer FRT RNA seq

  We propose to definitively characterise the somatic genetics of ER+ve, HER2-ve breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Dataset EGAD00001000338

• High-throughput sequencing data for study of molecular drivers of resistance to castration in localised prostate cancer

  Aligned whole-genome sequencing and RNA-seq of localised prostate cancer for study 'Loss of SNAI2 in prostate cancer correlates with clinical response to androgen deprivation therapy'.

  Dataset EGAD00001006640

• 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

• Reference Profiles of ExRNAs in Normal Human Pregnancy

  In this study, we did a comprehensive exRNA profiling of plasma and serum specimens from healthy pregnant women, sampled at different gestational time points, and including subjects with diverse geographical and ethnic backgrounds. This study also contains samples from male and female healthy donors to provide a baseline. The aim of this study is to identify miRNAs that can predict the gestation age and to build a miRNA profile across gestation using small RNA-seq data.

  Study phs003182

• Characteristics and Inflammatory Markers in Children with Eosinophilic Esophagitis (EoE)

  The overall protocol for the samples used in this study collects medical information, blood, and biopsy samples from children with eosinophilic esophagitis (EoE) over time to understand clinical characteristics and disease pathogenesis. Our patient population has confirmed EoE and symptoms of esophageal dysfunction characteristic endoscopic findings of EoE. Fibroblasts isolated from esophageal tissue samples from 2 subjects with active EoE and 2 control subjects were evaluated using single cell RNA-sequencing (scRNA-seq).

  Study phs003869

• B Cell Lymphocytosis and Reprogramming due to a CARD11 Bi-Allelic Gain-of-Function Mutation

  This is a single-cell RNA sequencing (scRNA-seq) study using peripheral blood mononuclear cells (PBMC) from 2 healthy donors and 2 patients with B cell Expansion with NF-&#954;B and T cell Anergy (BENTA). Samples were not hashed or multiplexed. The 10X Genomics Platform was used for sequencing. Principal findings include transcriptome changes due to mono- or bi-allelic mutations in the gene CARD11. FASTA files will be available through dbGaP.

  Study phs004115

• Space Associated Stem Cell Hallmarks of Aging in Astronauts

  This study examined the effects of the stress of space, specifically low earth orbit, on hematopoietic stem and progenitor cells (HSPCs) that maintain lifelong hematopoiesis and immune responses. Enriched CD34+ HSPCs were derived from 7 astronauts before, during and after 10 and 21-day ISS missions on the International Space Station. The samples were used as input to whole transcriptome sequencing by bulk RNA-Seq performed at The Scripps Research Institute Next Generation Sequencing Core on Illumina NextSeq 2000 sequencer and single cell RNA-Seq performed at The Salk Institute for Biological Studies on Illumina NovaSeq X Plus sequencer. Subsequent expression, RNA editing, and retrotransposon analyses were performed to assess HSPC and immune subpopulation survival dynamics. Overall, these analyses revealed space-associated stem cell hallmarks of aging (SASHA), including spaceflight dependent alterations in HSPC survival and self-renewal, ADAR1, telomere maintenance, mobilization and cell cycle gene expression, combined with space-induced clonal hematopoietic mutations, APOBEC3C activation and retrotransposon deregulation to warrant countermeasure development to enable long-duration spaceflight. Post-spaceflight analysis revealed increased C-to-T and clonal hematopoiesis-associated mutations, repetitive element and base deaminase deregulation, decreased telomere maintenance gene expression, and decreased self-renewal capacity compared to ground controls. These results demonstrate the space-associated aging effects in HSPCs after month-long exposure to LEO, providing insights into utilizing the LEO environment to model space-accelerated aging and other age-related malignancies.

  Study phs004267

• Encompassing view of spatial and single-cell RNA-seq renews the role of the microvasculature in human atherosclerosis

  Atherosclerosis is a pervasive contributor to ischemic heart disease and stroke. Despite the advance of lipid lowering-therapies and antihypertensive agents, the residual risk of an atherosclerotic event remains high and developing therapeutic strategies has proven challenging. This is due to the complexity of atherosclerosis with a spatial interplay of multiple cell types within the vascular wall. Here we generate an integrative high-resolution map of human atherosclerotic plaques combining single-cell RNA-seq from multiple studies and spatial transcriptomics data from 12 human specimens, with different stages of atherosclerosis. We show cell-type and atherosclerosis-specific expression changes and spatially constrained alterations in cell-cell communication. We highlight the possible recruitment of lymphocytes via ACKR1 endothelial cells of the vasa vasorum, the migration of vascular smooth muscle cells towards the lumen by transforming into fibromyocytes, and cell-cell communication in the plaque region, indicating an intricate cellular interplay within the adventitia and the subendothelial space in human atherosclerosis.

  Dataset EGAD50000000936

• RNA-seq of Toxoplasma gondii response in human macrophages

  Toxoplasmosis is a zoonotic disease caused by a ubiquitous protozoan parasite called Toxoplasma gondii, which can infect all mammal and bird species throughout the world. seroprevalence varies widely between countries. Studies have estimated that between 7-34% of people in the UK have been infected with T. gondii. The vast majority of these people will not have noticed any symptoms, however about 10% of people develop a mild to moderate self limiting flu-like illness. Following the acute active stage of the infection the parasite persists in the body in the form of cysts, particularly in heart and skeletal muscle and nervous system tissues, for many years, and usually for life. In immunocompetent persons these cysts do not pose a health risk. We will use RNA-seq to quantify the transcriptional response of macrophages to T gondii infection. 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/

  Dataset EGAD00001003241

• Single MII oocyte mRNA expression from women

  This dataset contains 14 paired-end FASTQ sequences from mRNA-Seq on single human M-II stage oocytes that were collected from ovarian tissue from unstimulated patients undergoing fertility preservation treatments due to cancer diagnoses, which did not influence ovarian function. Cumulus-oocyte-complexes were matured in vitro according Gruhn et al (Science 365: 1466-1469) and short term flash frozen prior to lysis, RNA extraction, full length cDNA preparation and amplification using the Ultra-low-input SMART-Seq2 v4 kit from Takara Clonetech. Further, these cDNA were used to prepare libraries for sequencing according the Nextera XT DNA library preparation kit from Illumina

  Dataset EGAD00001005971

• snRNAseq prostate cancer

  single-nucleus RNA seq characterization of human fresh frozen prostate cancer samples and non-malignant controls for the same patients. Biopsies were sectioned in 100 micron thick sections, adjacent to those used for spatial transcriptomics.

  Dataset EGAD50000001633

• Transcriptomic profiling of prostate cancer metastasis xenograft models

  RNA-seq profiling of 2 prostate cancer xenograft mouse models, each at the intact state (n=3), castrated state (n=4) and castrated + AR replacement (n=3).

  Dataset EGAD00001006551

• 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

• RNA-SEQ data from 13 CAF (Cancer Associated Fibroblast) samples sorted from fresh high-grade ovarian carcinoma

  Dataset EGAD00001003460

• Single-cell RNA-Seq analysis of thymic ILC1 progenitors and NK cell differentiation This analysis involved a multiplexed sequencing run to study thymic innate lymphoid cells (ILCs) and NK progenitors. The generated data requires a demultiplexing file to separate and identify the individual sample tags for downstream analysis.

  This dataset contains multiplexed single-cell RNA sequencing (scRNA-seq) data from human thymic tissue, focusing on ILC1 progenitors and NK cell differentiation. The data were generated using the BD Rhapsody system and sequenced on the Illumina NovaSeq S4 platform. A demultiplexing file is required to assign sample identities.

  Dataset EGAD50000001157

• T-ALL RNA-Seq raw data files

  Bone marrow or peripheral blood samples were collected of adult patients at first diagnosis of T-precursor acute lymphoblastic leukemia. RNA was isolated from mononuclear cells and subjected to mRNA library prep using Poly-A selection and sequencing on a NovaSeq 6000 system. Obtained gene expression profiles and gene fusion calls were used to allocate samples to molecular disease subtypes.

  Study EGAS50000000213

• Comparison between b2m KO and US2 expressing iPSC lines

  This dataset contains bulk RNA-seq transcriptomic profiles from a human induced pluripotent stem cell (hiPSC) line and three engineered derivatives: B2M knockout, EGFP overexpression, and US2 overexpression, alongside the parental line. Total RNA integrity was assessed using the Experion RNA StdSens 1K Analysis Kit on the Bio-Rad Experion Automated Electrophoresis System prior to library preparation and sequencing. Libraries were sequenced on an Illumina NovaSeq 6000 generating ~20 million reads per sample. Raw read quality was assessed with FastQC, reads were aligned to the human reference genome hg38 (Ensembl release 109) using STAR, and alignment/library QC metrics (e.g., orientation, composition, coverage) were evaluated with Picard.

  Dataset EGAD50000002321

• RNA sequencing data from patient derived colorectal cancer organoids

  This study aimed to develop NovumRNA, a bioinformatics pipeline designed to predict non-canonical tumor-specific antigens (ncTSAs) from human tumor RNA-sequencing data, potentially broadening the target pool for cancer neo-epitope-based immunotherapies. The pipeline was utilized to analyze RNA-seq data from ten patient-derived colorectal cancer (CRC) organoids, representing seven microsatellite stable (MSS) and three microsatellite instable (MSI) tumors. The goal was to explore the ncTSA landscape in CRC, particularly in MSS cases, which typically exhibit low tumor mutational burden and limited response to current immunotherapies. The study identified comparable ncTSA burdens across MSI and MSS tumors, suggesting new avenues for immunotherapy targeting non-canonical antigens in CRC. NovumRNA is available at: https://github.com/ComputationalBiomedicineGroup/NovumRNA.

  Study EGAS50000000685

• 10xchromium 3' v3 sequencing from cerebellum, lung, and heart aligned to GRCh38 genome

  Each run contains single cell RNA-seq data from unbiased sampling of single cells from the indicated human tissue. Single cell suspensions were prepared using enzymatic dissociation followed by tituration. The samples were processed using the 10XChromium 3' v3 sequencing pipeline, sequenced on an Illumina NovaSeq 6000, and analyzed using the cellranger software and aligned to the human GRCh38 genome version 93.

  Dataset EGAD00001006110

• Peripheral clonal expansion of T cells (scRNA-seq)

  Single-cell RNA-seq of tumor-infiltrating lymphocytes from 14 cancer patients before treatment, taken from tumor, normal adjacent tissue, and peripheral blood. Dataset consists of paired-end FASTQ files, including replicate libraries and runs.

  Dataset EGAD00001005464

• HBCC Postmortem Psychiatric Molecular Studies

  This postmortem study examines molecular, genetic and epigenetic signatures in the brains of hundreds of subjects with or without mental disorders conducted by the DIRP NIMH Human Brain Collection Core (HBCC). The brain tissues are obtained under protocols approved by the CNS IRB (NCT00001260), with the permission of the next-of-kin (NOK) through the Offices of the Chief Medical Examiners (MEOs) in the District of Columbia, Northern Virginia and Central Virginia. Additional samples were obtained from the University of Maryland Brain and Tissue Bank (contracts NO1-HD-4-3368 and NO1-HD-4-3383) (http://www.medschool.umaryland.edu/btbank/ and the Stanley Medical Research Institute: http://www.stanleyresearch.org/brain-research/). Clinical characterization, neuropathological screening, toxicological analyses, and dissections of various brain regions were performed as previously described (Lipska et al. 2006; PMID: 16997002). All patients met DSM-IV criteria for a lifetime Axis I diagnosis of psychiatric disorders including schizophrenia or schizoaffective disorder, bipolar disorder and major depression. Controls had no history of psychiatric diagnoses or addictions. SNP array: Array-based genotyping was performed on most samples published in this collection. The number of SNPs assayed via Illumina chips varied between 650,000 and 5 Million. Cerebellar tissue was generally used for genotyping studies. # Diagnosis SNP Array 1 Anxiety Disorder 1 2 Autism Spectrum Disorder 13 3 Bipolar Disorder 114 4 Control 387 5 Eating Disorder (ED) 2 6 Major Depressive Disorder (MDD) 186 7 Obsessive Compulsive Disorder (OCD) 5 8 Post-Traumatic Stress Disorder (PTSD) 0 9 Schizophrenia 220 10 Other 7 11 Tic Disorder 3 12 Undetermined 1 13 Williams Syndrome 2 Table: Numbers of samples in each diagnostic category. DNA extraction: 45-80 mg of cerebellar tissue was pulverized for DNA extractions. The QIAamp DNA mini Kit (Qiagen) method was employed for tissue DNA extraction. The tissue was initially lysed using Tissue Lyser (Qiagen) and extractions were accomplished according to manufacturer's protocol. The DNA was captured in 500uL elution buffer. The concentrations were measured using Thermo Scientific's NanoDrop 1000/NanoDrop ONE. The mean yield was 128.85 uG (+/- 79.48), the mean ratio of 260/280 was 1.87 (+/- 0.105), and the mean ratio of 260/230 was 2.48 (+/-1.75). Genotyping methods: Three types of Illumina Beadarray chips were used: HumanHap650Y, Human1M-Duo, and HumanOmni5M-Quad (San Diego, California). The genotyping was done according to the manufacturer's protocol (Illumina Proprietary, Catalog # WG-901-5003, Part # 15025910 Rev.A, June 2011). Approximately, 400ng DNA was used and each DNA sample was QC tested for 260/280 ratio by nanodrop and DNA band intactness on 2% agarose gel. Briefly, the samples were whole-genome amplified, fragmented, precipitated and resuspended in appropriate hybridization buffer. Denatured samples were hybridized on prepared Bead Array Chips. After hybridization, the Bead Chip oligonucleotides were extended by a single fluorescent labeled base, which was detected by fluorescence imaging with an Illumina Bead Array Reader, iScan. Normalized bead intensity data obtained for each sample were loaded into the Illumina Genome Studio (Illumina, v.2.0.3) with cluster position files provided by Illumina, and fluorescence intensities were converted into SNP genotypes. Microarray: We generated RNA expression data using array technology for psychiatric subjects compared to non-psychiatric subjects as controls. We used tissues from three different brain regions i.e. hippocampus, dorsolateral prefrontal cortex (DLPFC), and dura mater for a large cohort of individuals (total number 552 subjects for hippocampus, 800 for DLPFC and 146 for dura). Total RNA was extracted from ~100 mg of tissue using the RNeasy kit (Qiagen) according to the manufacturer's protocol. RNA quality and quantity were examined using the Bioanalyzer (Agilent, Inc) and NanoDrop (Thermo Scientific, Inc), respectively. Samples with RNA integrity number (RIN) # Diagnosis DLPFC Hippo Dura 1 Anxiety Disorder 1 0 0 2 Autism Spectrum Disorder 14 6 0 3 Bipolar Disorder 90 49 0 4 Control 336 270 75 5 Eating Disorder (ED) 2 1 0 6 Major Depressive Disorder (MDD) 144 87 0 7 Obsessive Compulsive Disorder (OCD) 5 3 0 8 Post-Traumatic Stress Disorder (PTSD) 6 0 0 9 Schizophrenia 192 125 71 10 Other 5 6 0 11 Tic Disorder 3 3 0 12 Undetermined 1 1 0 13 Williams Syndrome 2 1 0 Table: Numbers of samples in each diagnostic category. RNA-Seq of Dorso-lateral prefrontal cortex: All brains were collected and the dorsolateral prefrontal cortical (DLPFC) samples dissected at the HBCC, DIRP, NIMH. Dorsolateral prefrontal cortex (DLPFC) specimens were dissected from right or left hemisphere of frozen coronal slabs. The study was funded by the DIRP, NIMH under contract (#HHSN 271201400099C) with Icahn School of Medicine at Mount Sinai,1106402 One Gustave L. Levy Place, Box 3500, New York NY 10029-6574. RNA extraction, library preparation and sequencing were performed under contract at Icahn School of Medicine. The Common Mind Consortium (CMC) provided project management support. RNA isolation: Total RNA from 468 HBCC samples was isolated from approximately 100 mg homogenized tissue from each sample by TRIzol/chloroform extraction and purification with the Qiagen RNeasy kit (Cat#74106) according to manufacturer's protocol. Samples were processed in randomized batches of 12. The order of extraction for schizophrenia, bipolar, and MDD disorders and control samples was assigned randomly with respect to diagnosis and all other sample characteristics. The mean total RNA yield was 24.2 ug (+/- 9.0). The RNA Integrity Number (RIN) was determined by 4200 Agilent TapeStation System. Samples with RIN DLPFC RNA-Seq quantified expression data are provided for 364 samples. Data were generated, QC'd, processed and quantified as follows: RNA library preparation and sequencing: All samples submitted to the New York Genome Center for RNAseq were prepared for sequencing in randomized batches of 94. The sequencing libraries were prepared using the KAPA Stranded RNAseq Kit with RiboErase (KAPA Biosystems). rRNA was depleted from 1ug of RNA using the KAPA RiboErase protocol that is integrated into the KAPA Stranded RNAseq Kit. The insert size and DNA concentration of the sequencing library was determined on Fragment Analyzer Automated CE System (Advanced Analytical) and Quant-iT PicoGreen (ThermoFisher) respectively. Schizophrenia Bipolar Control 89 65 210 Table: Numbers of samples in each diagnostic category. RNA-Seq of subgenual anterior cingulate cortex (sgACC): All the 200 post-mortem brain samples (61 controls; 39 bipolar disorder; 46 schizophrenia; 54 major depressive disorder) were collected by the HBCC, DIRP, NIMH. RNA Extraction and Quality Assessment: Tissue from sgACC was pulverized and stored at -80&#176;C. Total RNA was extracted from 50-80 mg of the tissue using QIAGEN RNeasy Lipid Tissue Mini Kit (QIAGEN, Cat. # 74804) with DNase treatment (QIAGEN, Cat. # 79254). The RNA Integrity Number (RIN) for each sample was assessed with high-resolution capillary electrophoresis on the Agilent Bioanalyzer 2100 (Agilent Technologies, Palo Alto, California). The concentration of RNA and their 260/280 ratio (2.1+/- 0.032 SD) were determined with NanoDrop (Thermo Scientific). RNA sequencing: Stranded RNA-Seq libraries were constructed after rRNA depletion using Ribo-Zero GOLD (Illumina). RNA sequencing was performed at National Institute of Health Intramural Sequencing Center (NISC). Schizophrenia Bipolar Control MDD 46 39 61 54 Table: Numbers of samples in each diagnostic category. Whole Genome Sequencing: All brains were collected and dissected at the HBCC, DIRP, NIMH. This study generates whole genome sequencing data using sequencing of DNA in the dorsolateral prefrontal cortex (DLPFC), anterior cingulate cortex (ACC) or cerebellum of 443 individuals with schizophrenia, bipolar disorder and major depressive disorder and non-psychiatric controls. The study was funded by the DIRP, NIMH under contract (#HHSN 271201400099C) with Icahn School of Medicine at Mount Sinai,1106402 One Gustave L. Levy Place, Box 3500, New York NY 10029-6574. DNA extraction, library preparation and sequencing were performed under contract at Icahn School of Medicine. The Common Mind Consortium (CMC) provided project management support. All specimens were dissected from right or left hemisphere of frozen coronal slabs. DNA Library Preparation and Sequencing: All samples submitted to the New York Genome Center for WGS were prepared for sequencing in randomized batches of 95. The sequencing libraries were prepared using the Illumina PCR-free DNA sample preparation Kit. The insert size and DNA concentration of the sequencing library was determined on Fragment Analyzer Automated CE System (Advanced Analytical) and Quant-iT PicoGreen (ThermoFisher) respectively. A quantitative PCR assay (KAPA), with primers specific to the adapter sequence, was used to determine the yield and efficiency of the adaptor ligation process. Performed on the Illumina HiSeqX with 30X coverage. Schizophrenia Bipolar Control 115 78 230 Table: Numbers of samples in each diagnostic category. ChIP-Seq: All brains were collected and the dorsolateral prefrontal cortical (DLPFC) samples dissected at the HBCC, DIRP, NIMH. This study generates epigenetic data using sequencing of DNA after chromatin immunoprecipitation (ChIP-Seq) for marks H3K4me3 and H3K27ac in the dorsolateral prefrontal cortex (DLPFC). Dorsolateral prefrontal cortex (DLPFC) specimens were dissected from right or left hemisphere of frozen coronal slabs. The study was funded by the DIRP, NIMH under contract (#HHSN 271201400099C) with Icahn School of Medicine at Mount Sinai,1106402 One Gustave L. Levy Place, Box 3500, New York NY 10029,6574. Chromatin precipitation, library preparation and sequencing were performed under contract at Icahn School of Medicine. The Common Mind Consortium (CMC) provided project management support. Chromatin immunoprecipitation (ChIP) assays for histone marks H3K4me3 and H3K27ac were carried out using Native ChIP. Micrococcal Nuclease (MNase) (Sigma, N3755) treatment was used to digest chromatin into mononucleosomes. The following antibodies were used for chromatin pull-down: anti-H3K4me3 (Cell Signaling, Cat# 9751BC, lot 7) and anti-H3K27ac (Active Motif, Cat# 39133, Lot # 31814008). Histone modification-enriched genomic DNA fragments were recovered using Protein A/G magnetic beads (Thermo Scientific, 88803-88938 or Millipore 16-663), and then washed, eluted, and treated with RNAse A and proteinase K. Final ChIP DNA products were isolated using phenol-chloroform extraction followed by ethanol precipitation. The efficiency of each ChIP assay was validated using Qubit concentration measurement and qPCR for positive (GRIN2B, DARPP32) and negative (HBB) control genomic regions. Only ChIP assays that passed quality control were further processed for library preparation and sequencing; this included ChIP DNA that was not detectable on Qubit but showed a good signal and expected enrichment patterns in qPCR. HISTONE_MARK H3K27ac H3K4me3 Input Bipolar 56 4 7 Control 158 11 24 Schizophrenia 79 11 12 Table: Numbers of individuals in each assay grouped by histone mark or input.Long-Read Whole-Genome Sequencing (WGS) Cohort Description: Brain specimens were obtained from the Human Brain Collection Core (HBCC), part of the NIH NeuroBioBank. Samples were collected under protocols approved by the NIH CNS Institutional Review Board (IRB) (NCT03092687), with informed consent from next-of-kin (NOK). Collection was coordinated through the Offices of the Chief Medical Examiners (MEOs) in Washington, D.C., Northern Virginia, and Central Virginia. Clinical metadata and documentation are publicly available via the NIMH Data Archive (NDA) (Collection #3151) https://nda.nih.gov/edit_collection.html?id=3151 Eligibility Criteria No clinical diagnosis of major neuropsychiatric or neurodegenerative diseaseNo diagnosis of cognitive impairment during life All individuals were confirmed to be neurologically normal at time of deathDemographics Initial cohort size: 155 individuals Ancestry: All individuals self-identified as African or African-admixed Mean age at death: 44.2 years (range: 18&#8211;85 years) Sex distribution: 36.4% femaleSample Processing: Frozen frontal cortex tissue was dissected and processed according to the public protocol: https://www.protocols.io/view/processing-human-frontal-cortex-brain-tissue-for-p-kxygxzmmov8j/v2. High-molecular-weight DNA was extracted and libraries were prepared using the Oxford Nanopore Technologies (ONT) LSK-114 kit. Sequencing was performed using ONT PromethION flow cells (R10.4.1 chemistry) Data Processing and Quality Control: Basecalling: Conducted using Guppy v6.38 Read Alignment: Reads were aligned to the GRCh38 reference genome using minimap2 Sample Identity Verification: Sample identity was validated by comparing ONT-derived SNP calls with matched short-read WGS genotypes to ensure concordance and prevent sample swaps Variant Calling and Phasing: Reads were base-called with Guppy v6.38. Reads were aligned to GRCh38 using minimap2. We verified sample identity by cross-checking ONT SNV calls with the existing short-read WGS genotypes, confirming no sample switches. The napu pipeline (https://github.com/nanoporegenomics/napu_wf) produced; haplotype-resolved assemblies, joint small-variant (SNV/indel) calls, and multi-caller structural-variant sets, all reported on GRCh38 and phased where possible. Raw signal data were basecalled to obtain 5-methyl-cytosine (5mC) status; methylation tags were added to the phased BAM files. Genome-wide methylation summaries are provided in BED format.Dataset Filtering and Exclusions: All 155 samples underwent sequencing and SNP-based ancestry inference 8 samples were excluded due to ancestry inconsistent with African or African-admixed background 1 sample was excluded due to insufficient sequencing quality Final Sample Set: 146 high-quality samples from individuals of African or African-admixed ancestry were retained for downstream analyses See PMID: 39764002 for further analysis detailsDiagnosis#SamplesControl155Table: Diagnostic Summary.Note: The data derived from HBCC resources were removed from dbGAP and are now available in the NIMH Data Archive (NDA). They include genotypes, short read whole genome sequencing (WGS), epigenetics (DNA methylation, ChIP-seq for histones), RNA expression (qPCR, microarray, RNA-seq, single nucleus RNA-seq) of various brain regions in cases with schizophrenia, bipolar disorder, major depression, substance use disorders and normative controls. Please access our NDA collection (https://nda.nih.gov/edit_collection.html?id=3151) for further detail.

  Study phs000979

• Gene Expression and Epigenetic Analyses of Human Myocytes From Different Muscles

  The study contains expression and DNA methylation data of in vitro cultured myoblasts derived from biopsies of control, FSHD1 and FSHD2 patients from the tibialis anterior, quadricep, bicep and deltoid. Expression data is from bulk RNA-seq using the SmartSeq2 protocol for days 0 and 5 of in vitro differentiation of primary myocytes from the bicep and deltoid of FSHD1 patients. DNA methylation data was produced using the TruSeq Methyl Capture EPIC kit (Illumina) for days 0, 3 and 12 of in vitro differentiation of primary myocytes from the tibialis anterior and quadricep of healthy individuals and FSHD2 patients.

  Study phs002554

• BBMRI – BIOS – Freeze 2 – RNA-seq Counts

  Read counts determined using HTSeq-count for the BBMRI BIOS Freeze 2 RNAseq data

  Dataset EGAD00010001420

• 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

• Gabriella Miller Kids First Pediatric Research Program in Pediatric T-Cell Acute Lymphoblastic Leukemia

  The outcome for patients with relapsed T-ALL is dismal with 3-year event free survival of AALL0434 was a Children's Oncology Group-initiated phase 3 randomized clinical trial comparing Capizzi-style escalating methotrexate plus pegaspargase (CMTX) vs. high dose methotrexate (HDMTX), with/without six 5-day courses of nelarabine. Survival on this study was superior to any prior trial for de novo T-ALL, changing the standard of care. Yet, a substantial minority (~15%) of patients had relapsed or refractory (r/r) disease. Through the TARGET initiative, RNA sequencing (RNA-Seq), DNA copy number analysis, and whole-exome sequencing (WES) were performed on 264 T-ALL patients treated on AALL0434, demonstrating recurrent alterations could be grouped into 10 different potentially targetable functional pathways. This analysis was not powered to examine associations between genetic lesions with outcome, because too few patients with r/r disease were included. This project is dedicated to testing the hypothesis that comprehensive genomic profiling of the entire AALL0434 cohort will identify recurrent genetic alterations that can be segregated into biologically relevant deregulated pathways that can be combined with MRD to identify patients at risk for poor outcomes before they relapse and provide rationale for treatment with alternative therapies. In addition, a number of small recent studies demonstrated that many of the biologically relevant alterations in T-ALL occur in non-coding regions of the genome, but no large studies have performed whole genome sequencing (WGS) in T-ALL. This project also tests the hypothesis that WGS of a large cohort of patients with T-ALL will identify novel lesions in coding and non-coding regions that will be highly impactful in the understanding of T-ALL pathogenesis.These hypotheses are tested by performing comprehensive genomic profiling (WGS, WES, RNA-Seq, and copy number analysis) of the entire AALL0434 cohort with available samples with the following specific aims: (1) identify recurrent genetic alterations that predict poor outcome in T-ALL; (2) identify novel alterations, including non-coding alterations in T-ALL; and (3) identify germline genetic variants that predispose to T-ALL and to increased toxicity to chemotherapy.

  Study phs002276

• Spatial Transcriptomics on prostate cancer heterogeneity

  Intratumor heterogeneity is one of the biggest challenges in cancer treatment today. Here we investigate tissue-wide gene expression heterogeneity throughout a multifocal prostate cancer using the spatial transcriptomics (ST) technology. Utilizing a novel approach for deconvolution, we analyze the transcriptomes of nearly 6750 tissue regions and extract distinct expression profiles for the different tissue components, such as stroma, normal and PIN glands, immune cells and cancer. We distinguish healthy and diseased areas and thereby provide insight into gene expression changes during the progression of prostate cancer. Compared to pathologist annotations, we delineate the extent of cancer foci more accurately, interestingly without link to histological changes. We identify gene expression gradients in stroma adjacent to tumor regions that allow for re-stratification of the tumor microenvironment. The establishment of these profiles is the first step towards an unbiased view of prostate cancer and can serve as a dictionary for future studies.

  Study EGAS00001003001

• Single-cell RNA sequencing of control and Notch inhibitor treated HCC PDX model

  We generated single-cell RNA-seq data for anti-Notch2 (n=3), anti-JAG1 (n=1) and anti-gD (n=4) treated LIV78 tumors. NCR nude mice bearing similarly sized LIV78 tumors (volumes between 300-900mm3) were injected intravenously with 30mg/kg body weight of either anti-Notch2, anti-Jag1 or anti-gD control antibody 72hrs prior to tumor harvest and tumor cell isolation. Following the depletion of CD45+ and Ter119+ cells, the samples were processed for single-cell RNA-seq (scRNAseq) as described previously (Long et al., 2019) using the Chromium Single Cell 3’ Library and Gel bead kit v2, following the manufacturer’s manual. cDNAs and libraries were prepared following the manufacturer’s manual (10X Genomics). Libraries were profiled by Bioanalyzer High Sensitivity DNA kit (Agilent Technologies) and quantified using Kapa Library Quantification Kit (Kapa Biosystems, Wilmington, MA). Each library was sequenced in one lane of HiSeq 2500 (Illumina) following the manufacturer’s sequencing specification (10X Genomics) to produce the resulting FASTQ files.

  Dataset EGAD50000000738

• Phenotype information

  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 in-cluding 27 humanized (HIS) PDTX, 8 HIS non-PDTX and 21 non-HIS PDTX non-obese diabetic (NOD)-scid IL2Rgnull (NSG) mice were collected during humanization, xenografting, treatment, and sacrifice. The mice were treated with either rituximab, cyclophosphamide, doxorubicin, vincris-tine, and prednisone (R-CHOP), CD20-targeted human IFNα2-based AcTaferon combined with 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 using the SMARTer Stranded Total RNA-Seq Kit v3.

  Dataset EGAD50000000806