12304 results for "cancer rna-seq"

in 35.07 milliseconds.

• WES and RNA-seq of pre-invasive lung adenocarcinoma

  The prevalence of lung adenocarcinoma (LUAD) has increased sharply in East Asia. Early diagnosis leads to better survival rates, but this requires an improved understanding of the molecular changes during early tumorigenesis, particularly in non-smokers. We performed whole exome-sequencing and RNA-sequencing of samples from 94 East Asian patients with precancerous lesions (25 with atypical adenomatous hyperplasia [AAH]; 69 with adenocarcinoma in situ [AIS]) and 73 patients with early invasive lesions (minimally invasive adenocarcinoma [MIA]). This datasets contains the sequencing raw data (FASTQ format).

  Dataset EGAD50000000637

• PBL whole exome and transcriptome data

  Plasmablastic lymphoma (PBL) represents a clinically heterogeneous subtype of aggressive B-cell non-Hodgkin lymphoma. Although targeted sequencing studies and a single center whole exome sequencing (WES) study in HIV+ patients recently revealed several genes, associated with PBL pathogenesis, the global mutational landscape and transcriptional profile of PBL remain elusive. To inform on disease-associated mutational drivers, mutational patterns and perturbed pathways in HIV+ and HIV- PBL we performed WES and RNA-sequencing (RNA-seq) of 34 PBL tumors.

  Dataset EGAD00001006795

• RNA and ChIP Sequencing datasets from the study Kalirin-RAC controls nucleokinetic migration in ADRN-type neuroblastoma

  This dataset contains the RNA and ChIP Sequencing data from the study Kalirin-RAC controls nucleokinetic migration in ADRN-type neuroblastoma. The data is organized in 7 experiments which are divided by both sequencing technology or the application of siRNA or drug interventions (or lack thereof) on neuroblastoma cell lines. The experiment names and the file names have been chosen in each respective experiment to guide future users of the data to replicate the analyses in the manuscript.

  Dataset EGAD00001006964

• atrial appendage miRNA-seq in non-, paroxysmal and persistent atrial fibrillation

  64 left atrial appendages from patients without atrial fibrillation (AF) undergoing cardiac surgery, patients with paroxysmal AF and with persistent AF (~20 per group). Trizol RNA isolation, size selection, single end miRNA sequencing on 4 lanes of illumina NextSeq 500. Provided are FastQ files, one per lane per sample. Additional data (e.g. clinical characteristics, RIN values etc.) can be provided upon request. The same RNA samples (62) were used for transcriptome sequencing. Results from transcriptome sequencing are stored in the EGA database and are managed by the same DAC.

  Dataset EGAD00001007694

• Whole genome, RNA-seq and single-cell Multiome profile of multiple myeloma

  We analyzed multiple myeloma samples from two patients included in the observational prospective cohort MYRACLE before talquetamab treatment and after relapse. Five other myelomas from the same cohort were included for comparison. Normal plasma cells were also retrieved. All samples were analyzed by whole genome sequencing and single-nucleus Multiome, except one that could only be analyzed by bulk RNA sequencing.

  Dataset EGAD00001010057

• RNA sequencing of Non-Small Cell Lung Cancer and adjacent normal tissue (ICON)

  RNA sequencing was performed on 108 NSCLC tumor samples and their paired adjacent normal tissues (n=21) to identify associations with clinical and immune characteristics.

  Dataset EGAD50000000361

• De novo metastatic prostate cancer cohort

  Fastq files from RNA sequencing of normal and tumor samples from 16 patients from the de novo metastatic prostate cancer cohort.

  Dataset EGAD50000002381

• RNA sequencing

  We propose to definitively characterise the somatic genetics of 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 EGAD00001000285

• Characterization of High-Grade Serous Ovarian Cancer Subtypes via Single-Cell and Spatial-Transcriptomics Profiling

  We measured gene expression in single-cell RNA sequencing samples from patients with high-grade serous ovarian cancer (HGSOC), for a study on improving HGSOC subtype definition by taking into account varying cell type proportions within tumors. The initial dataset (added October, 2020) contains 3 samples (3 individuals). The next dataset (added November, 2022) contains 34 samples from 8 individuals. The samples in the second dataset were sequenced in five different ways: 1) rRNA depletion and bulk RNA sequencing of tumor chunks, 2) rRNA depletion and bulk RNA sequencing of dissociated cells, 3) poly-A capture and bulk RNA sequencing of dissociated cells, 4) poly-A capture and scRNA sequencing of dissociated cells, 5) barcoding and pooling cells and scRNA sequencing (2 pools of 4 samples each). The third dataset (added June, 2024) contains data from one spatially resolved transcriptomics experiment (4 samples, one per Visium capture area, describing one tumor from one individual) and scRNA sequencing on 5 samples (5 individuals).

  Study phs002262

• Characterizing Advanced Breast Cancer Heterogeneity and Treatment Resistance through Serial Biopsies and Comprehensive Analytics

  This dataset accompanies the manuscript "Characterizing Advanced Breast Cancer Heterogeneity and Treatment Resistance Through Serial Biopsies and Comprehensive Analytics". In this study we discuss the clinical implications and consequences of molecular heterogeneity in a metastatic breast cancer patient identified through serial biopsies, multi-omic analysis, and longitudinal patient monitoring, performed through the precision oncology program, Serial Measurements of Molecular and Architectural Responses to Therapy (SMMART). This case study describes a metastatic breast cancer patient with a highly heterogenous tumor that began as ER positive/HER2 negative on diagnosis, then was found to be ER negative/HER2 positive in a metastatic liver lesion (Study biopsy #1), and finally triple negative (TNBC) in another metastatic liver biopsy (Study biopsy #2). Multi-omic assays included clinical genomic panel sequencing, clinical immunohistochemistry, a clinical protein profiling assay (Intracellular Signaling Protein Profiling), RNA sequencing, and RPPA. Here we provide the expression data from RNAseq and RPPA data on Study biopsy #2 for the patient discussed in this case report. Note: The first liver biopsy did not yield sufficient material for RNAseq or RPPA.Raw RNA FASTQ files from Study biopsy #2 of the liver Gene expression (RNAseq) files from Study biopsy #2Protein expression (RPPA) files (level 2, 3, 4) for Study biopsy #2

  Study phs002321

• Synergy study: "Tissue resident CD8+ T cell clonal expansion in advanced triple negative breast cancer is associated with response to chemoimmunotherapy"

  Dataset of 10x Genomics 5'prime single-cell RNA sequencing of 40 tumor biopsy samples or triple negative breast cancer. Samples are taken before and after immuno checkpoint blockade treatment. Processed according the 10X genomics protocol, sequenced on Immumina NovaSeq6000. Raw sequencing reads are further processed with Cellranger 3.0 to get gene-expression matrices.

  Study EGAS50000000527

• Differential expression profile of gluten-specific T cells identified by single-cell RNA-seq

  Gluten-specific CD4+ T cells drive the pathogenesis of celiac disease and circulating gluten-specific T cells can be identified by staining with HLA-DQ:gluten tetramers. In this first single-cell RNA-seq study of tetramer-sorted T cells from untreated celiac disease patients blood, we found that gluten-specific T cells showed distinct transcriptomic profiles consistent with activated effector memory T cells that shared features with Th1 and follicular helper T cells. Compared to non-specific cells, gluten-specific T cells showed differential expression of several genes involved in T-cell receptor signaling, translational processes, apoptosis, fatty acid transport, and redox potentials. Many of the gluten-specific T cells studied shared T-cell receptor with each other, indicating that circulating gluten-specific T cells belong to a limited number of clones. Moreover, the transcriptional profiles of cells that shared the same clonal origin were transcriptionally more similar compared with between clonally unrelated gluten-specific cells.

  Study EGAS00001005517

• Single cell RNA sequencing reveals induced bifurcated differentiation after RUNX1::RUNX1T1 depletion in patient-derived leukemic blasts

  Study EGAS00001008050

• To profile the landscape of sebaceous tumours_RNAseq

  Sebaceous tumours are a rare cutaneous cancer with potential for aggressive behaviour. However, limited information is available on these cancers with few published cases. Here we wish to exome sequence these cancers to define the first genomic landscape for this malignancy. We will extract RNA from formalin-fixed, paraffin-embedded (FFPE) cores. Cores may be obtained from lesional and non-lesional tissues of primaries as well as matching metastases. The extracted RNA will be used for RNA sequencing.

  Dataset EGAD00001015368

• Childhood Cancer Data Initiative (CCDI): Molecular Characterization across Pediatric Brain Tumors and Other Solid and Hematologic Malignancies for Research, Diagnostic, and Precision Medicine

  This study contains tumor and germline WGS, RNA-Seq, Clinical Panel Sequencing, and other omics and molecular data for patients with pediatric brain tumors and other solid and hematologic malignancies. This data has been collected from multiple organizations including the multi-institute Children's Brain Tumor Network (CBTN), the Pacific Pediatric Neuro-Oncology Consortium (PNOC), and the Children's Hospital of Philadelphia Division for Genomic Diagnostics (CHOP DGD). In addition to being available pre-publication and without embargo via dbGaP and the NCI Cancer Research Data Commons, this data is made available via Cavatica, PedcBioPortal and the Kids First Data Resource Portal. Collectively, this availability strives to accelerate the research process and enable members of the scientific and patient communities to partner and make discoveries faster than ever before.In 2019, the CBTN launched the Pediatric Brain Tumor Atlas, which now comprises the largest collection of childhood brain tumor data in the world. This resource is helping accelerate not only brain tumor research, but is also empowering discovery for other rare childhood conditions. Brain tumors are the most common form of cancer in children aged 0-19 in the United States, and are the largest cause of cancer-related deaths. The estimated number of new cases in 2019 is nearly 3,800, and thus brain tumors are a rare disease. Despite their relative rarity, the years of potential life lost due to brain tumors in 2009 was estimated at 47,631 years for children and adolescents aged 0-19 in the United States; this is a disproportionate amount of life lost compared to adult cancers and represents an unrecognized societal threat. There is an urgent need to improve therapies for these children. This sequencing cohort defines the largest, clinically annotated pediatric brain tumor cohort study to date and seeks to define the intersection of germline and somatic underpinnings of pediatric brain tumors across a shared developmental context of cancer and structural birth defects.

  Study phs002517

• Triple Negative BC RNA Sequencing

  We propose to definitively characterise the somatic genetics of 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 EGAD00001001339

• bulk RNAseq analysis of tumor from 3 non-muscle-invasive bladder cancer patients

  We performed screenings of patient-specific neo-epitopes by tumor-infiltrating CD8+ T lymphocytes of 4 non-muscle invasive bladder cancer patients. After the tumor resection, these patients went on to receive BCG treatment as they had high-risk disease. In order to select the neo-epitopes, we performed bulk RNAseq of the bladder tumor to select the mutated genes that were expressed in the tumor (TPM >1). For patient UC2, 3 different tumors were resected at the same time and RNA from these 3 tumors were sent separately for RNAseq. For patient UC4, no RNA was available, so this patient is not included in this study.

  Study EGAS50000001383

• Cambridge Neoadjuvant Cancer of the Prostate (CANCAP03): A Window Study into the Effects of Olaparib ± Degarelix in Primary Prostate Cancer.

  Study: Cambridge Neoadjuvant Cancer of the Prostate (CANCAP03): A Window Study into the Effects of Olaparib ± Degarelix in Primary Prostate Cancer. EudraCT Number: 2014-004417-86 Clinicaltrials.gov Number: NCT02324998 Purpose: Investigate combined PARP and androgen inhibition in primary prostate cancer. Aim: To understand the biological mechanism(s) underlying clinical efficacy, especially in the absence of mutations in homologous recombination (HR) repair pathways. Dataset: Single-nuclear RNA sequencing data from post-treatment radical prostatectomy tissue cores for six patients, 3 from each of olaparib and olaparib and degarelix cohorts. Samples were processed for nuclear isolation and extraction, prior to single-nuclear RNA sequencing. 10x libraries were constructed using the 10x supplied protocol, briefly: individual nuclei were trapped into droplets with a single bead, and poly A transcripts were barcoded during reverse transcription. Complementary DNA was amplified, and libraries were prepared for sequencing on NovaSeq 6000 using S4 flow cell (100k reads per cell). FASTQ files were processed using CellRanger pipeline (10X Genomics). Outputs from the CellRanger pipeline were analysed using the Seurat package (v4.9.9.9049) in R (v4.2.0). Processed data is provided as a Seurat object.

  Study EGAS50000000880

• Finding structural variation from the human skin fibroblast at the single-cell level

  Somatic structural variants (SVs) are widespread in cancer, but their impact on disease evolution is understudied due to a lack of methods to directly characterize their molecular consequences. We present a computational method, scNOVA, that integrates haplotype-resolved SV discovery with nucleosome occupancy analysis using Strand-seq, to functionally characterize SVs in single cells.

  Study EGAS00001006498

• Fastq data for ChIP-Seq (H3K9me3) assays for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  Fastq data for ChIP-Seq (H3K9me3) assays assay for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001408

• Fastq data for ChIP-Seq (Input) assays for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  Fastq data for ChIP-Seq (Input) assays assay for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001409

• ABHD11 Autoimmunity Study DAC

  This DAC oversees controlled access to human RNA-seq data generated as part of the project “ABHD11 inhibition and T cell function in autoimmunity” at Swansea University. The DAC will evaluate and approve access requests based on scientific merit and alignment with participant consent. Data requests will be considered from academic researchers and healthcare professionals working on immunology or autoimmunity.

  Dac EGAC50000000750

• RNA dataset of ALK study

  Here we sequenced biopsies from a patient with ALK-positive NSCLC progressing on first-line lorlatinib. This dataset contains one mRNA-seq and one Total-RNAseq. This aims to investigate the impact of the K1150dup mutation on lorlatinib progression and to explore potential therapeutic strategies to overcome resistance.

  Dataset EGAD50000002553

• Single-cell/single-nucleus RNA-seq of diffuse hemispheric gliomas, H3G34-mutant.

  9 DHG-H3G34 patient samples were sequenced by paired-end scRNA-sequencing using the Smart-Seq2 protocol on a NextSeq 500 sequencer (Illumina). Illumina bcl2fastq 1.5 was used for demultiplexing. This dataset contains the resulting 9,408 fastq files of 4,704 single cells/nuclei sequenced.

  Dataset EGAD50000000760

• TPM for IMpower133 (GO30081)

  This dataset contains log2(TPM + 1) for 271 tumor samples profiled by RNA-seq for the entire transcriptome for samples originating from IMpower133 (GO30081).

  Dataset EGAD50000000196

• Paired-end RNA-seq analysis of the 3D evolution of glioma cell populations. Part 1.

  Dataset includes 160 double-stranded RNAseq libraries collected from 16 patients with adult diffuse glioma. The majority of these samples were spatially-mapped during sample collection, enabling the genomic information derived from them to be mapped in 3D space.

  Dataset EGAD00001005222

• EGAD00000000046

  RNA-SEQ data from 3 recurrent and 1 ovarian primary Granulosa Cell Tumour samples

  Dataset EGAD00000000046

• Single cell mRNA sequencing of primary GBM - SF 10592

  We collected fresh tissue from an untreated GBM (SF10592) directly from the operating room and subjected the biopsy to single-cell RNA-seq with the fluidigm C1 machine, resulting in sequencing libraries from 96 individual cells.

  Dataset EGAD00001003112

• Single cell mRNA sequencing of primary GBM - SF 10679

  We collected fresh tissue from an untreated GBM (SF10679) directly from the operating room and subjected the biopsy to single-cell RNA-seq with the fluidigm C1 machine, resulting in sequencing libraries from 96 individual cells.

  Dataset EGAD00001003113

• Single cell mRNA sequencing of primary GBM - SF 10281

  We collected fresh tissue from an untreated GBM (SF10281) directly from the operating room and subjected the biopsy to single-cell RNA-seq with the fluidigm C1 machine, resulting in sequencing libraries from 96 individual cells.

  Dataset EGAD00001003114

• Single-Nuclei RNA-seq of healthy (post-mortem) and temporal lobe epilepsy (biopsy) subjects.

  To identify dysfunctional neuronal subtypes underlying seizure activity in the human brain, we have performed single-nucleus transcriptomics analysis of >110,000 neuronal transcriptomes derived from temporal cortex samples of multiple temporal lobe epilepsy and non-epileptic subjects.

  Dataset EGAD00001006575

• Microinjection of hIPSC-derived intestinal organoids with Salmonella Typhimurium

  To generate an RNA-Seq dataset for organoids apically stimulated with Salmonella Typhimurium.These data are 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 EGAD00001001363

• Islet RFX6 Study Manuscript Data

  This submission includes raw FASTQ files (for bulk RNA-seq and 10X joint snATAC+snRNA multiome profiling experiments), sample phenotype files, and genotypes for the data included in the manuscript.

  Dataset EGAD00001008777

• 17 scRNAseq samples

  17 samples were processed for single cell RNA sequencing (SORT-seq)

  Dataset EGAD00001007523

• RNA-seq dataset

  RNAseq FASTq files from 728 bulk pre-treatment tumors from IMvigor010.

  Dataset EGAD00001007575

• Gene expression in human monocyte differentiation

  This dataset consists of RNA-seq data from human monocytes, monocyte-derived dendritic cells or monocyte-derived macrophages as well as monocyte-derived cells that were subjected to siRNA treatment targeting CTCF or RAD21. In total, it includes 63 samples.

  Dataset EGAD00001007956

• Low T cell diversity is associated with poor outcome in bladder cancer - Single cell RNAseq and TCRseq data

  T cells are crucial effector cells in the endogenous defense against cancer, yet the clinical impact of their quantity, diversity, and dynamics remains underexplored. In this study we performed single cell RNAseq paired with single cell TCR-seq on tumor and blood samples from 4 patients (n samples = 8). The goal was to investigate T cell subtypes of expanded and non-expanded T cell clones in blood and in tumors.

  Study EGAS50000000938

• Single-cell RNA sequencing on 12346 single T cells from 14 non-small cell lung cancer (NSCLC) patients

  Deep single-cell RNA sequencing data for 12346 T cells from tumour, adjacent normal tissue and peripheral blood of treatment-naïve NSCLC patients

  Dataset EGAD00001003999

• CD8+ Tumor-Infiltrating Lymphocyte Abundance is a Positive Prognostic Indicator in Nasopharyngeal Cancer

  This retrospective tissue study explores the prognostic significance of tumour-infiltrating lymphocyte (TIL) populations in NPC, using a combination of RNA sequencing and immunohistochemistry.

  Study EGAS00001006396

• Human CD4 Memory T Cell Activation Time Course

  We performed a high-resolution time course RNA-seq experiment on CD4+ memory T cells during activation with anti-CD3/CD28 beads. We performed this in 24 adult individuals of European ancestry with no autoimmune diseases. We used 1 million cells as starting material, per time point (up to 8 time points per individual from 0 to 72 hours). We identified widespread dynamic allele-specific expression (dynASE) across the genome, i.e. ASE that changes with time after activation, which reflects cell state-dependent genetic regulatory effects. DynASE events were enriched in risk loci for multiple autoimmune diseases. This highlights the importance of studying multiple cellular states in order to elucidate the mechanisms of autoimmune disease. It also provides a successful framework to do it in other cellular systems relevant for other traits. We also showed an unprecedented amount of regulatory variation for HLA genes. HLA-DQB1 has 3 distinct regulatory haplotypes with expression profiles that could come from 3 different genes. We performed ATAC-seq in replicate for CD4+ memory T cells stimulated for 72 hours from another healthy individual. These data, together with genetic fine-mapping, CRISPR editing, EMSA and luciferase assays, helped us find a SNP in the promoter of HLA-DQB1 that causes at least part of the large cell state-dependent change in expression, at the RNA and protein levels.

  Study phs002259

• Development of Computational Approaches for Cell Hashing in scRNA-Seq

  As a test of cell overloading after cell hashing, a sample of peripheral blood mononuclear cells (PBMC) from a single subject was separated into naive T cells, memory T cells, and non-T cell PBMC populations using fluorescence activated cell sorting (FACS). Each population was separated into two technical replicates, then stained with BioLegend TotalSeq-A antibodies. All 6 samples were pooled, then loaded into 6 wells of a 10X Genomics Chromium 3' RNA-seq v3 chip at increasing cell counts: 16,000 (k), 24k, 32k, 48k, 64, and 80k cells per well. We also included a single sample that was not hashed or pooled, as well as a single sample that was stained with hashing antibodies, but not pooled in two separate wells.

  Study phs002695

• The transition from quiescent to activated states in human hematopoietic stem cells is governed by dynamic 3D genome reorganization

  To elucidate the epigenetic changes which occur when human long-term hematopoietic stem cells (LT-HSC) become activated we performed Bulk ATAC-Seq on 13 sorted bulk hematopoietic populations from cord bloodas well as single-cell ATAC-Seq upon CD34+CD38-CD45RA- cells enriched for HSC as well as CD34+/CD38+ progenitor cells both from cord blood. These studies revealed gains of chromatin accessibility around CTCF binding sites during HSPC activation, as such we additionally performed Low-C to directly profile the 3D conformation of human cord-blood derived LT-HSC and Short-term hematopoietic stem cells (ST-HSC), as well as Hi-C , ATAC-Seq and CTCF ChIP-Seq upon the OCIAML-2 cell line in which CTCF sites gained during LT-HSC activation are enriched. Finally we transduced human cord-blood LT-HSC with an shCTCF vector; in-vitro cultured LT-HSC cells harbouring shCTCF were used to perform RNA-Seq, and scATAC-Seq was performed on CD34+/CD38- human CB cells transduced with shCTCF, four weeks post xeno-transplantation into mice. Collectively these studies have helped us demonstrate the role of 3D chromatin conformation changes during human LT-HSC activation.

  Dataset EGAD00001006447

• Genome-Wide Characterization of Pancreatic Adenocarcinoma Patients Using Next Generation Sequencing

  In this study, we whole genome sequenced tumor/normal pairs from three pancreatic adenocarcinoma patients to separately characterize each patient with respect to somatic alterations. For 2 patients for whom tumor RNA was available, we also performed RNA sequencing to evaluate gene expression changes. While additional sequencing is needed to improve our understanding of the disease, the information acquired from this study contributes to our knowledge base on pancreatic cancer and helps to establish a foundation for identifying and developing more efficacious treatments for patients.

  Study phs000550

• RNA-seq of longitudinal human blood and nose swab samples from a controlled human infection experiment with SARS-CoV-2 virus

  Controlled human infection experiments enable longitudinal profiling of immune responses to a pathogen. 36 healthy volunteers aged 18-29 years, with no evidence of previous infection or vaccination, were inoculated with SARS-CoV-2 virus and quarantined for 14 days. Blood samples for RNA sequencing were collected into PAXgene tubes before virus challenge, 6 hours after challenge, daily thereafter for 14 days and on day 28. Mid-turbinate nose swabs for RNA sequencing were collected before virus challenge, and on days 1, 3, 5, 7, 10 and 14 after challenge, preserved in RNAprotect.

  Study EGAS50000000667

• Glioblastoma stem cell lines RNA-seq (Guilhamon et al.)

  RNA was extracted from GSCs using the Qiagen RNeasy Plus kit. RNA sample quality was measured by Qubit (Life Technologies) for concentration and by Agilent Bioanalyzer for RNA integrity. All samples had RIN above 9. Libraries were prepared using the TruSeq Stranded mRNA kit (Illumina). Two hundred nanograms from each sample were purified for polyA tail containing mRNA molecules using poly-T oligo attached magnetic beads, then fragmented post-purification. The cleaved RNA fragments were copied into first strand cDNA using reverse transcriptase and random primers. This is followed by second strand cDNA synthesis using RNase H and DNA Polymerase I. A single “A” base was added and adapter ligated followed by purification and enrichment with PCR to create cDNA libraries. Final cDNA libraries were verified by the Agilent Bioanalyzer for size and concentration quantified by qPCR. All libraries were pooled to a final concentration of 1.8nM, clustered and sequenced on the Illumina NextSeq500 as a pair-end 75 cycle sequencing run using v2 reagents to achieve a minimum of ~40 million reads per sample.

  Dataset EGAD00001006813

• Single-cell RNA sequencing of 6 follicular lymphoma tumors

  Follicular lymphoma (FL) is an indolent cancer of mature B-cells but carries increased risk of transformation to a more aggressive histology over time. We present here comprehensive profiling both tumor and immune compartments in 6 diagnostic FL biopsies by single-cell RNA sequencing. This confirmed results from 155 FL tumors characterized by mass cytometry (CyTOF) which revealed two distinct evolutionary trajectories with disparate risk of transformation and alternate biologies.

  Study EGAS00001005257

• Single-nuclei multiomic analysis of KOLF2.1J human induced pluripotent stem cells-derived differentiated dopaminergic neurons

  Datasets consists of 12 samples of nuclei from hIPSCs differentiated optimized protocols for generating dopaminergic neurons. 6 single nuclei (RNA-ATAC) samples of XMAS protocol with cells collected at days 0,11,16,28,42 and 56 after differentiation. 3 snRNA-seq samples from AMS protocol of cells collected at days 14,16 and 28 after differentiation and 3 snRNA-seq samples with AMS protocol until day 14 grafted and grafts processed after 5 months grafting.

  Dataset EGAD50000002054

• scRNA dataset for 15 samples

  This dataset includes single cell (sc)RNA-seq of N=3 patient-derived xenograft (PDX) samples profiled at baseline (no drug treatment) and N=12 samples from one PDX profiled during the course of treatment (N=1 sample each for 4 treatment arms x 3 timepoints). The dataset includes bam files that have been purged of reads mapping to cells where a majority of the reads from that cell mapped to the mouse genome. All scRNA-seq data were generated using the Chromium Next GEM Single Cell 5' Reagent Kits v2 (Dual Index) from 10X Genomics.

  Dataset EGAD50000001424

• Single-cell RNA sequencing dissects gene-environment interactions on gene expression and regulation in immune cells.

  This study aims to dissect gene-environment interactions on gene expression and regulation in immune cells using scRNA-seq data from 120 donors being stimulated with 3 pathogens, for 2 different timepoints. More specifically, we identified context- and cell-type-specific eQTLs and co-expression QTLs in PBMCs.

  Study EGAS00001005376

• T cell transcriptional gradient

  There are two datasets: 1. scRNA-seq of human cutaneous immune cells from psoriasis patients. These include pre- and post-Tildrakizumab treated patients and come in a BAM file format. 19006FL-25-01 19006FL-38-01 19006FL-32-01-03 19006FL-33-01 19006FL-28-01-05 19006FL-35-01-01 2. RNA-seq of ZFP36L2 CRISPIR deleted Human T cells are FASTQ files. 19006XR-30-05 19006XR-30-04 19006XR-30-02 19006XR-30-01 19006XR-26-05 19006XR-26-04 19006XR-26-02 19006XR-26-01 19006R-22-04 19006R-22-08 19006R-22-05 19006R-22-01

  Dataset EGAD00001009677