3743 results for "RNA AND sequencing OR transcriptome"

in 17.20 milliseconds.

• LSC RNA-Sequencing

  To infer the proteomic Mito signature in the LSC subcompartiment, myeloid blasts for 10 patients from the discovery cohort were FACS-sorted into CD34-GPR56+NKG2DLigands- (CD34-), alias 61dc5fb798e2520001702c03 CD34+GPR56+NKG2DLigands- (CD34+), alias 61dc5fb798e2520001702c03 Detailed gating strategy will be described in Donato, Correia, Andresen and Trumpp et al., (manuscript in preparation)

  Dataset EGAD00001008488

• Genetic determinants of monocyte splicing are enriched for disease susceptibility loci including for COVID-19

  These data correspond to samples used in the following papers: 1. GWAS and meta-analysis identifies 49 genetic variants underlying critical Covid-19 2. Genetic determinants of monocyte splicing are enriched for disease susceptibility loci including for COVID-19. 3. Identification of Genetic Determinants of Transcriptional Response to Metformin in Primary Human Monocytes. They are the raw RNA sequencing files as used in all downstream analysis.

  Dataset EGAD00001010176

• RNAseq Iron-Treated iPSC-derived Microglia

  Iron accumulation in microglia has been observed in Alzheimer’s disease and other neurodegenerative disorders and is thought to contribute to disease progression through various mechanisms including neuroinflammation. To study the interaction between iron accumulation and inflammation, we treated human induced pluripotent stem cell-derived microglia (iPSC-MG) with an increasing concentration of iron, in combination with inflammatory stimuli such as interferon gamma and amyloid β, and performed RNA sequencing.

  Dataset EGAD00001008660

• Transcriptomic profiling of primary tumor and paired hepatic oligometastasis of PDAC

  The dataset was generated for studying metastatic mechanism of pancreatic ductal adenocarcinoma (PDAC). It is consisted of pair-end raw RNA sequencing reads of 33 fresh froze PDAC specimens, which includes 6 tumor-adjacent normal tissues (N), 13 primary tumors (PT), and 14 hepatic metastases (HM) from 14 PDAC patients (6 N-PT-HM trios, 7 PT-HM paires, and 1 HM).

  Dataset EGAD00001006598

• RNA-Seq in Patients with Primordial Dwarfism

  Transcriptome studies in patients with rare genetic diseases can potentially aid in the interpretation of likely causal genetic variation through identification of altered transcript abundance and/or structure. RNA-Seq is the most sensitive assay for both investigating transcript structure and abundance The primary aim of this pilot project is to investigate to what degree integrating exome-Seq and RNA-Seq data on the same individual can accelerate the identification of causal alleles for rare genetic diseases. There are two main strands to this: (i) identifying which variants discovered in exome-seq appear to be having a functional impact on transcripts, and (ii) identifying transcript outliers, especially among known causal genes, that may not necessarily have a causal variant identified from exome sequencing. The latter may identify the presence of causal variants that lie far from coding regions (e.g. the formation of cryptic splice sites deep within introns, or loss of long range regulatory elements), which can be confirmed with further targeted genetic assays. Just over 50% of all disease-causing variants recorded in the Human Gene Mutation Database (HGMD) affect transcript structure and abundance (e.g. nonsense SNVs, essential splice site SNVs, frameshifting indels, CNVs). This pilot project will study RNA from lymphoblastoid cell-lines from 12 patients with primordial dwarfism syndromes, for 10 of these samples we have previously generate exome data as part of our collaboration with the group of Prof Andrew Jackson. The two remaining samples are positive controls where the causal mutation is known, and is known to affect transcript structure and/or abundance. Primordial dwarfism is a prime candidate for these RNA-seq studies because all known causal mutations to date have key roles in DNA replication and thus, unsurprisingly, the products of the causal genes are typically ubiquitously expressed. Each RNA will be sequenced, with two technical replicates (independent RT-PCR and libraries) per sample, and each replicate run in 1/2 of a HiSeq lane using 100bp paired reads. Samples preparation was as follows :The cells were grown to confluency, then pellets frozen at -80. RNA samples were prepared using the Qiagen RNeasy kit, then nanodropped and analyzed using the bioanalyzer to determine concentration and purity. 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 EGAD00001000640

• Bulk Iso-Seq from brain tissue and exosomes isolated from brain tissue using long-read PacBio sequencing of poly-adenylated transcripts

  Human brain sEVs were isolated from postmortem human brain tissue. RNA was extracted from both the source brain tissue and sEVs and prepared for long-read sequencing. cDNA was sequenced on the PacBio Sequel II. The data provided have undergone processing using the tool ccs (v6.0.0) to generate circula consensus reads. For further processing, it is recommended to follow the guidelines at https://isoseq.how/, starting with using lima to remove cDNA primers.

  Dataset EGAD50000000043

• Bell_activation_timecourse

  We purified human naive and memory B cells from PBMCs. We stimulated them with IgM cross-linker providing BCR stimulation, multimeric CD40L that engages costimulatory receptor CD40 on the B cell, and cytokines IL-2 and IL-21. To comprehensively characterise activation dynamics of naive and memory B cells, we performed single-cell RNA sequencing (scRNA-seq) and B cell receptor sequencing (BCR-seq) in resting cells (day 0), before the first division (day 1), at the time of the first division (day 3) and following the full B cell differentiation (day 6)

  Dataset EGAD50000002115

• Comprehensive single cell study of lung adenocarcinoma from early to metastatic stages

  We performed single cell RNA sequencing (scRNA-seq) for 208,506 cells derived from 58 lung adenocarcinomas from 44 patients, which covers primary tumour, lymph node and brain metastases, and pleural effusion in addition to normal lung tissues and lymph nodes. The extensive single cell profiles depicted a complex cellular atlas and dynamics during lung adenocarcinoma progression which includes cancer, stromal, and immune cells in the surrounding tumor microenvironments.

  Dataset EGAD00001005054

• Sequencing data for oesophageal and related samples - Xiaodun Li et al (WGS, RNA)

  Data supporting: "Esophageal adenocarcinoma organoid cultures recapitulate human disease heterogeneity and provide a model for clonality studies and precision therapeutics." Li et al. WGS (BAM files) RNAseq (BAM files) Tumours, organoids, normals

  Dataset EGAD00001004007

• Dataset for Ewing_sarcoma_PNET-RNA

  Rare cancer sequencing data of 28 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008845

• Sequencing data for oesophageal and related samples - Izadi et al (WGS, RNA)

  Data supporting: "Genomic analysis of response to neoadjuvant chemotherapy in esophageal adenocarcinoma" Izadi et al. WGS for tumour and normal samples. RNAseq for tumour samples.

  Dataset EGAD00001007493

• Sequencing data for the manuscript "Resolving spatial subclonal genomic heterogeneity of loss of heterozygosity and extrachromosomal DNA in gliomas"

  Mapping the spatial organization of DNA-level somatic copy number changes in tumors can provide insight to understanding higher-level molecular and cellular processes that drive pathogenesis. We describe an integrated framework of spatial transcriptomics, tumor/normal DNA sequencing, and bulk RNA sequencing to identify shared and distinct characteristics of an initial cohort of eleven gliomas of varied pathology and a replication cohort of six high-grade glioblastomas.

  Dataset EGAD50000001394

• scRNAseq of ALS patients

  The data set contains information from 9 individuals (5 ALS + 4 controls) using single cell RNA sequencing in combination with TCR V(D)J sequencing to study the immune profile of the central nervous compartment (CSF). Sequencing was done using 10x Genomics platform (5’ scRNAseq & V(D)J Reagent Kits v1.1). 5P and TCR libraries were then pooled and for sequencing on the NovaSeq sequencer. Provided files are in .fastq.gz format and per individual four files are available (Read 1&2 and Lane 1&2).

  Dataset EGAD00001009623

• Newcastle COVID-19 Single-cell PBMC

  Single-cell multi-omic profiling of healthy controls, asymptomatic and hosptial-admitted COVID19 patients recruited from Newcastle University hospitals. These data also include healthy control volunteers treated with IV-LPS as inflammatory controls. Data represent RNA-seq, surface protein measurements (CITE-seq) of 192 antibody targets, along with VDJ-seq profiling of single T cell and B cell receptors.

  Dataset EGAD00001007866

• MSC_busulfan_small_intestine_organoids

  This dataset represent the RNA-seq, which was done on untreated small intestinal organoids; small intestinal organoids treated with chemotherapeutic, busulfan; untreated small intestinal organoids co-cultured wth mesenchymak stromal/stem cells (MSCs; busulfan treated small intestinal organoids co-cultured with MSCs. The same set of samples was done for 3 different primary bone marrow MSC donors.

  Dataset EGAD00001011176

• RNA-seq data of Metabolic profiling of patient-derived organoids reveals nucleotide synthesis as a metabolic vulnerability in malignant rhabdoid tumors

  Patient-matched normal kidney organoid (103H) and MRT tumoroid (103T2) models were treated for 24h with either DMSO (ctrl), 400nM MTX, or 50nM BAY to investigate the direct effects of drug treatment on the expression of key metabolic enzymes in the nucleotide biosynthesis pathways.

  Dataset EGAD00001015391

• Reconstitution of Human Brain Cell Diversity in Organoids via Four Protocols [scRNAseq]

  Single-cell RNA-sequencing of brain organoids at day 120 grown in four distinct growth protocols designed to generate dorsal (D) and ventral (V) forebrain, midbrain (M) and striatum (S) tissue using eight different pluripotent stem cell lines. Per per cell line-protocol combination two organoids (biological replicates) were grown. For cell line 176 the experiment was conducted in two independent biological replicates (repititions E1 and E2).

  Study EGAS50000000662

• Immune control of functional memory CD8 T cells in normal-appearing vitiligo skin

  This study aimed to characterize immune cell states in nonlesional (NL) and perilesional (PL) skin of patients with vitiligo using single-cell RNA sequencing. Shared CD8⁺ T cell clusters were detected in both regions, with PL-derived cells enriched for immune activation pathways and NL skin showed stronger infiltration of regulatory T cells. These findings reveal functional T cell heterogeneity in vitiligo and highlight regulatory mechanisms that may limit depigmentation in NL skin.

  Study EGAS50000001317

• Bulk RNA-seq paired fastq files from i3Ns harbouring a SNCA A53T mutation, with or without RSL3 treatment

  FASTQ files from bulk RNA sequencing of a iPSC-derived rapid neuronal model (i3Ns) harbouring the SNCA A53T mutation in a WTC11 background as a model of synucleinopathy, with or without treatment of 300nM RSL3 for 6 hours. Libraries were prepared using the Watchmaker rRNA and globin depletion kit and sequenced on a NovaSeq X with an average depth of ~27 million paired-end reads with a fragment length of 100 base pairs, per sample. 19 samples are included in this dataset, each with two paired fastq files (R1 and R2). The dataset includes control neurons (WT: dcas9 parental line and C4 CRISPR control) and A53T clones (B7, H8 and L8) across two neuronal inductions (ind1 vs ind2), with or without treatment of RSL3 (UT vs. RSL3).

  Dataset EGAD50000002209

• 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

• RNA-sequencing from duodenal bipsies of Celiac disease patients

  Samples, in a form of PAXgene fixed and paraffin-embedded biopsies, were collected from the multi-site, double-blind, randomized, placebo-controlled trial, aimed at dose-finding and assessing the efficacy and tolerability of a 6-week treatment with ZED1227 capsules vs. placebo in subjects with well-controlled celiac disease undergoing gluten challenge. Total RNA was extracted from the PaxFPE biopsy specimens (n = 116) using additional cuttings from the samples on which histomorphometry was previously assessed. For the extraction, an RNeasy Kit (Qiagen, Hilden, Germany) was used according to the manufacturer’s instructions. Library preparation and next-generation sequencing (NGS) were performed by the Qiagen NGS Service. A total of 10 ng of purified RNA was converted into cDNA NGS libraries. Library preparation was quality controlled using capillary electrophoresis. Based on the quality of the inserts and the concentration measurements, the libraries were pooled in equimolar ratios and then sequenced on a NextSeq (Illumina Inc., San Diego, USA) sequencing instrument according to the manufacturer’s instructions, with 100 bp read length for read 1 and 27bp for read 2. The raw data were de-multiplexed, and FASTQ files for each sample were generated using bcl2fastq2 software (Illumina Inc., San Diego, USA).

  Dataset EGAD50000000491

• A Pilot Study of Rapid Autopsy and Procurement of Tissue in Thoracic Malignancy Cancer Patients to Investigate Tumor Heterogeneity

  Integrated proteo-genomics studies to characterize tumor heterogeneity of metastatic lung adenocarcinoma and thymic carcinoma are lacking. We carried out whole exome sequencing, RNA sequencing, copy number estimation and mass spectrometry-based proteomics of 40 tumors from five rapid/warm autopsy patients. We found highly variable mutational heterogeneity that was largely driven by APOBEC-mutagenesis with the expression of APOBEC3B (Gene ID: 9582) and APOBEC3A_B (Gene ID: 100913187) due to underlying APOBEC3 region germline variants as the likely mediating mechanism. APOBEC3A_B expression was associated with increased immune tumor microenvironment and CD274 (Gene ID: 29126) expression while smoking was associated with increased APOBEC-mutagenesis in TP53 (Gene ID: 7157) mutant tumors with high APOBEC3B expression. Heterogeneity at the level of the transcriptome and proteome occurred in association with copy number heterogeneity, not APOBEC-induced mutational heterogeneity. Arm and focal copy number alterations (CNAs) occurred as an evolutionarily late event in a subset of patients, with corresponding changes in the transcriptome and proteome, implicating CNAs as a driving force of heterogeneity in the evolution of metastatic disease.

  Study phs001432

• Capture-based Methods for Transcriptomic Profiling of FFPE material

  This dataset includes all FASTQ files for 11 samples where different capture-based methods for transcriptome profiling have been tested. Specifically, we have the 'traditional' RNA-seq experiment with fresh frozen (FF) material, and 3 different capture methods for the matching formalin-fixed paraffin-embedded samples: Agilent (AGI), IDT, and Twist Biosciences (TBS). In total, there are 43 samples with paired-end FASTQ files (1 sample did not have sufficient material to test all methods). Samples are identified by the R01-R11 IDs with a suffix that indicates the capture method used (or FF for fresh frozen).

  Dataset EGAD00001007655

• Genomics of Pediatric Renal Medullary Carcinomas

  Version 1We derived faithful cancer cell lines from patients with a diagnosis of renal medullary carcinomas (RMC). These models have been sequenced with whole genome, exome and transcriptome technologies along with the patient's primary germline and tumor samples. We took these faithful models and performed loss-of-function genetic perturbation screens (e.g. RNAi and CRISPR-Cas9) along with an orthogonal small molecule screen. We identified the ubiquitin-proteasome system as an important target in RMC as well as other SMARCB1 deficient cancers.Version 2We have collaborated with the Children's Oncology Group and the study AREN03B2 to study the cohort of patients with a central diagnosis of RMC. Here, we used 10x linked read sequencing along with RNA-sequencing to profile these matched tumor-normal pairs.

  Study phs001800

• Single cell transcriptome and TCR sequencing of EBNA1, ANO2 and CRYAB-reactive T cells in multiple sclerosis.

  Molecular mimicry between Epstein-Barr virus (EBV) and self antigens in the brain has been suggested as a mechanism for how adaptive immune responses to EBV may contribute to multiple sclerosis (MS) disease pathogenesis. Anoctamin-2 (ANO2) and ɑ-crystallin B (CRYAB) have been identified as having homologous peptide sequences with the EBV antigen EBNA1. To explore T cell cross-reactivity, we stimulated PBMC from four natalizumab-treated persons with MS with full-length bead-coupled antigens and sorted proliferating CD4+ T cells by flow cytometry after 8 days. Single cell RNA sequencing was performed on T cells reacting to EBV EBNA1, ANO2, CRYAB, albumin binding domain (ABD, irrelevant protein control) and anti-CD3.

  Study EGAS50000001531

• Bulk RNA sequencing of day 2 and day 7 biopsies from the tuberculin skin test in people with latent tuberculosis, and of day 2 biopsies from saline controls

  We used the tuberculin skin test (TST) as human challenge model to study the temporal evolution of the immune response to Mycobacterium tuberculosis (Mtb) antigens in vivo. Study participants comprised healthy HIV seronegative adults, 18-60 years of age. Latent tuberculosis (TB) infection was defined as immune memory for Mtb-specific antigens identified by positive peripheral blood IFNg release assays, but no clinical or radiological evidence of active TB. Two units tuberculin each were injected intradermally into the contralateral forearms of participants. After 2 days (n=216) or 7 days (n=158), 3 mm skin punch biopsies were taken from the injection sites and processed for whole genome transcriptional profiling by bulk RNA sequencing. The time points reflect maximum clinical inflammation (day 2) and maximum T cell infiltration (day 7) of the TST. TST samples were compared to skin biopsies taken two days after control injection of saline in a separate group of individuals (n=33), comprising healthy volunteers as well as patients with active or latent TB, ranging from 18-75 years of age. This dataset includes 407 samples from 256 individuals (n=33 saline, n=223 with Day 2 and/or Day 7 TST). Skin biopsies were collected into RNAlater (Qiagen) for RNA extraction. Total RNA was obtained with the Precellys Evolution homogenizer (Bertin Instruments) and Qiagen RNeasy mini kit. RNA was subjected to DNase treatment to remove contaminating genomic DNA using a TURBO DNA-free kit (Ambion, Life Technologies). The KAPA mRNA HyperPrep Kit (Roche Diagnostics) was used to construct stranded mRNA-Seq libraries from up to 500 ng intact total RNA. Paired-end sequencing was performed on the Illumina Nextseq using the Nextseq 500/550 High Output 75 cycle kit (Illumina). Runs were demultiplexed using bcl2fastq by Illumina.

  Dataset EGAD50000001208

• single cell RNA-seq of peripheral blood from analysis in infants with MLL-rearranged Acute Lymphoblastic Leukemia

  This dataset contains two experiments. 1) Single cell RNA-seq of peripheral blood diagnostic samples from patients with MLL-rearranged infant ALL that underwent relapse or not (samples ending in R relapsed, samples ending in N did not), sequenced with SORT-seq (see cell systems, 2016, doi:10.1016/j.cels.2016.09.002). For some of the patients, multiple indipendent plates were produced (each plate is a sample). Barcode-well correspondence can be found here: https://bitbucket.org/princessmaximacenter/sharq/src/master/data/celseq2_bc384-v4.csv . 2) Single cell RNA-seq of peripheral blood diagnostic samples from patients with MLL-rearranged infant ALL that underwent relapse or not (samples ending in R relapsed, samples ending in N did not), sequenced with10x Genomics Version 2.

  Dataset EGAD00001007752

• Discovery of Non-ETS Gene Fusions in Human Prostate Cancer using Next Generation RNA Sequencing

  Half of prostate cancers harbor gene fusions between TMPRSS2 and members of the ETS transcription factor family. To date little is known about the presence of non-ETS fusion events in prostate cancer. We employed next-generation transcriptome sequencing (RNA-Seq) in order to explore the whole transcriptome of 25 human prostate cancer samples for the presence of chimeric fusion transcripts. We generated more than 1 billion sequence reads and used a novel computational approach (FusionSeq) in order to identify novel gene fusion candidates with high confidence. In total, we discovered and characterized seven new cancer-specific gene fusions, two involving the ETS genes ETV1 and ERG, and five involving non-ETS genes such as CDKN1A (p21), CD9 and IKBKB (IKK-beta), genes known to exhibit key biological roles in cellular homeostasis or assumed to be critical in tumorigenesis of other tumor entities, as well as the oncogene PIGU and the tumor suppressor gene RSRC2. The novel gene fusions are found to be of low frequency but interestingly, the non-ETS fusions were all present in prostate cancer harboring the TMPRSS2-ERG gene fusion. Future work will focus on determining if the ETS rearrangements in prostate cancer are associated or directly predispose to a rearrangement prone phenotype.

  Study phs000310

• Genomic profiling of subcutaneous patient derived xenograft models of solid childhood cancer

  The pediatric cancer cohort in this study included 70 PDX models from 65 different individuals. This cohort included a total of 16 different pediatric solid tumor subtypes, including fourteen Wilms tumors, thirteen hepatoblastomas, thirteen osteosarcomas, ten germ cell tumors, four neuroblastomas, three clear cell sarcomas, two adrenal cortical carcinomas, two leydig cell tumors, two medulloblastomas, one embryonal rhabdomyosarcoma (ERMS), one Ewing sarcoma, one pleomorphic sarcoma, one adenocarcinoma, one glioblastoma, one mesothelioma and one ovarian tumor. Notably, we have five samples with multiple PDX models from same patient, including two cases with duplicates (564 and 564-Dup, 1796 and 1796-Dup), one case with two different metastasis (560-SM, 560-LM), one case with two blocks from same tumor (1939 and 1939-Dup), and one case with different primary tumor from same patient (2264 and 1932). We have a total of 353 sequencing data, including 82 RNA sequencing data (RNA-seq), 138 whole-exome sequencing (WES) and 135 low-pass whole-genome sequencing (WGS). For RNA-seq data, we have 61 PDXs and 21 PTs; for WES, we have 67 PDXs, 30 PTs and 40 matched normal germlines; for WGS, we have 64 PDXs, 30 PTs and 40 matched normal germlines. Of which, 19 PT-PDX paired RNA-seq, 28 paired PT-PDX paired WES and WGS were included.

  Dataset EGAD00001009863

• SCANDARE HNSCC 3' Tag RNA-seq

  SCANDARE (NCT03017573) is a multicentric biobanking study, enrolling adult patients with newly diagnosed head and neck squamous cell carcinoma (HNSCC), triple negative breast cancer (TNBC), ovarian and cervical cancer. Tumor tissue and blood samples are collected at several time points during patient's journey, including at diagnosis, post-neoadjuvant chemotherapy in case of neoadjuvant treatment, at surgery, at recurrence and at disease progression following treatment initiated at recurrence. Since its launch in 2017 at Institut Curie, SCANDARE has enabled the longitudinal collection and preservation of samples for in-depth analyses. Here, we describe molecular alterations in 264 FFPE samples at baseline from 90 HNSCC patients using 3'-tag RNA-seq technology, with FASTQ files deposited in the dataset.

  Dataset EGAD50000001655

• Integrative understanding of human immune system by functional genomics and development of intervention strategies for the prevention of autoimmune diseases

  arious peripheral blood immune cell subsets from 5 rheumatoid (RA) donors were collected ("CD16p_Mono", "CL_Mono???, "DN_B", "Fr_II_eTreg???, "mDC???, "Mem_CD4" , "Naive_B" , "Naive_CD4" , ???Neu", "NK" , "pDC" , "Plasmablast", ???SM_B", "Tfh", "Th1", "Th17", "Th2" , "USM_B"). The patients were analyzed again longitudinally after abatacept treatment. RNA-seq was performed with each immune cell subset samples. After gene expression quantification samples were filtered.

  Study JGAS000602

• Integrative understanding of human immune system by functional genomics and development of intervention strategies for the prevention of autoimmune diseases

  Various peripheral blood immune cell subsets from 39 healthy volunteers and 50 rheumatoid (RA) donors were collected ("CD16p_Mono", "CL_Mono???, "DN_B", "Fr_II_eTreg???, "mDC???, "Mem_CD4" , "Naive_B" , "Naive_CD4" , ???Neu", "NK" , "pDC" , "Plasmablast", ???SM_B", "Tfh", "Th1", "Th17", "Th2" , "USM_B"). 15 RA patients were analyzed longitudinally. RNA-seq was performed with each immune cell subset samples. After gene expression quantification samples were filtered.

  Study JGAS000598

• Bulk-tissue paired-end RNA-sequencing of anterior cingulate cortex samples derived from Lewy body disease patients

  Profiling of 24 human anterior cingulate cortex samples by bulk-tissue RNA-sequencing. Samples were derived from 5 non-neurological control individuals and 19 individuals with Lewy body disease (Parkinson’s disease = 7 individuals; Parkinson’s disease with dementia = 6 individuals; dementia with Lewy bodies = 6 individuals). Paired-end FASTQ files for each of the human samples are provided and are denoted by the suffixes R1 (read 1) and R3 (read 2). Fastp (v 0.20.0), a fast all-in-one FASTQ pre-processor, was used for adapter trimming, read filtering and base correction. Fastp default settings were used for quality filtering and base correction. Further details on parameters used are available here: https://github.com/RHReynolds/RNAseqProcessing/blob/master/QC/prealignmentQC_fastp_PEadapters.R.

  Dataset EGAD00001007698

• Single-cell RNA sequencing of SarBC-01 treated with Dexamethasone vs DMSO, with or without Matrigel.

  This dataset contains raw FASTQ files from single cell RNA sequencing of SarBC-01 cells treated with Dexamethasone vs DMSO, with or without Matrigel, processed with MULTI-seq. Cells from 4 different culture conditions (+Mat/Dex, +Mat/DMSO, -Mat/Dex, -Mat/DMSO) were harvested, processed for multiplexing using the MULTI-seq protocol and loaded in a Chromium Single Cell 3ʹ GEM Library and Gel Bead Kit v3 (10x Genomics). Gene expression (cDNA) and MULTI-seq libraries were prepared according to the manufacturers’ protocol of Chromium Next GEM Single Cell 3’ reagents Kits v3.1 (Dual Index). Finally, cDNA and MULTI-seq libraries were analyzed using an Agilent Bioanalyzer (DNA High Sensitivity kit) and sequenced on a NovaSeq6000 (S2 flow cell) platform. MULTISEQ BARCODES: TTAGCCAG => Matrigel/DMSO CCACAATG => Matrigel/Dexamethasone GCACACGC => noMatrigel/DMSO AGAGAGAG => noMatrigel/Dexamethasone

  Dataset EGAD00001011155

• Single-cell RNA sequencing data of peripheral blood mononuclear cells obtained from 30 ATL patients, 11 HTLV-1-infected asymptomatic carriers, and 4 healthy donors.

  Single-cell RNA sequencing (scRNA-seq) data of peripheral blood mononuclear cells (PBMCs) obtained from 30 ATL patients (34 samples including 4 sequential ones), 11 HTLV-1-infected asymptomatic carriers, and 4 healthy donors.

  Dataset EGAD00001007015

• RNA-sequencing of meningiomas for integrative molecular classification.

  RNA-sequencing of meningiomas for integrative molecular classification.

  Dataset EGAD00001007494

• Evaluating potential drug candidates for the treament of Henamgiopericytoma on patient derived cell line models

  Solitary fibrous tumor/Hemangiopericytoma (SFT/HPC) is a rare subtype of soft tissue sarcoma associated with NAB2-STAT6 gene fusions. This study established and characterized a novel SFT/HPC patient-derived cell line called SFT-S1. Potential drug candidates that could be repurposed for the treatment of SFT/HPC were screened. Screening was performed through RNA-Seq

  Dataset EGAD50000000039

• 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

• scRNA-seq data set for 13 AML patients

  This dataset includes single cell (sc)RNA-seq of N=13 AML patients. 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 human genome. All scRNA-seq data were generated using the Chromium Next GEM Single Cell 5' Reagent Kits v2 (Dual Index) from 10X Genomics.

  Dataset EGAD50000001346

• miRNAseq of paired FL and tFL samples

  This dataset contains miRNA-seq of paired FL and tFL samples (n=10 pairs) sequenced by Illumina NextSeq500. Libraries used in this miRNA-seq dataset were prepared with NEBNext Multiplex Small RNA Library Prep Set for Illumina (NEB,Catalog number: E7560S). RNAs used for library preparation were isolated from FFPE tissues using High Pure miRNA Isolation Kit (Roche,Catalog number: 05080576001). Data are uploaded as FASTQ format.

  Dataset EGAD50000001385

• RNA-seq TPMs quantification for baseline tumor samples originating from IMpower150, and relevant clinical metadata

  This dataset includes full tumor transcriptomes from 558 advanced NSCLC tumors. These data originate from pre-treatment samples from a clinical trial for first-line non-small cell lung cancer (IMpower150). The patients in this trial were treated with the PD-L1 inhibitor atezolizumab +bevacizumab + chemotherapy or bevacizumab + chemotherapy or atezolizumab + chemotherapy.

  Dataset EGAD50000001814

• This dataset includes FASTQ for single-nucleus RNA-seq of normal controls, and multiple system atrophy (MSA) or Parkinson's disease (PD) patients.

  The dataset includes more than 130k nuclei isolated using 10x Genomics Chromium Next GEM Single Cell 3' Reagent Kits v3.1. In total, 30 samples are included from 10 controls, 8 MSA (including one sample that was omitted during QC), or 12 PD patients. Samples were sequenced on Illumina Novaseq 6000 or NextSeq 550 instruments.

  Dataset EGAD50000002041

• Assessment of cannabidiol and Δ9-tetrahydrocannabiol in mouse models of medulloblastoma

  These data were used in the following publication: Andradas, C.; Byrne, J.; Kuchibhotla, M.; Ancliffe, M.; Jones, A.C.; Carline, B.; Hii, H.; Truong, A.; Storer, L.C.D.; Ritzmann, T.A.; et al. Assessment of Cannabidiol and delta9-Tetrahydrocannabiol in Mouse Models of Medulloblastoma and Ependymoma. Cancers 2021, 13, 330. https://doi.org/10.3390/cancers13020330 There are 4 paired-end RNA-seq samples from paediatric brain cancer cell lines.

  Dataset EGAD00001006923

• Single-cell RNA sequencing of cytokine-induced T cell responses

  Cytokines affect T cell responses by polarising them to different phenotypes. We isolated T cells from healthy platelet donors and cultured them in resting and stimulated condition, as well as in the presence of Th2, iTreg and Th17 polarizing cocktail. To characterize the efficacy of cytokine induced porization and subpopulation specific response, we profiled single cell transcriptome five days following polarization using 10x platform (3' v2).

  Dataset EGAD00001005290

• Bulk RNASeq on CD8+CD69+CD103+ and CD8+CD69+CD103- T cells form breast cancer.

  CD8+CD69+CD103+ and CD8+CD69+CD103- T cells were flow sorted from 1 primary triple negative breast cancer, 1 primary HER2 amplified breast cancer, and 1 triple negative liver metastasis. Prior to flow sorting, fresh tumor samples were digested to produce single cell homogenates on the day of surgery. Following RNA extraction, RNASeq was performed using polyA selection.

  Dataset EGAD00001003964

• Characterization of Leukemic Stem Cells in DNMT3Amut and NPM1mut AMLs

  Using a novel sorting strategy, we performed ultra low input RNAseq from FACS-sorted populations from diagnostic DNMT3Amut and NPM1mut AML patients. Primary samples were retrospectively collected based on their mutational profile. Samples were thawed, stained and FACS sorted using combination of lineage markers, CD34, GPR56 and NKG2DLigands. RNA was extracted and library prepared from 13 samples.

  Dataset EGAD00001009293

• Stage-specific gene and transcript dynamics in human male germ cells

  To study global transcriptional dynamics during human spermatogenesis we sequenced total RNA of human testicular biopsies with 5 specific histological phenotypes: Sertoli cell-only (SCO, n=3), spermatogenic arrests at the spermatogonial (SPG, n=4), spermatocyte (SPC, n=3), and spermatid (SPD, n=3) level, as well as normal spermatogenesis (Normal, n=3).

  Dataset EGAD00001008652

• A brain precursor atlas reveals the acquisition of developmental-like states in adult cerebral tumours

  We generated a single-cell RNA-seq atlas capturing over 100,000 cells spanning all stages of the mouse cerebral development. By examining data from over 100 cerebral tumour samples, our study reveals that, despite the phenotypic/genotypic differences between the tumour types, they are all comprised of developmental sublineages that map most closely to embryonic or juvenile stages of development.

  Dataset EGAD00001008746

• RNA-Seq dataset for Malignant rhabdoid study

  Study describing the dynamics of chromatin organization within malignant rhabdoid tumors. This study describes how this chromatin organization changes upon SMARCB1 rescue within patient-derived organoid models from malignant rhabdoid tumors. Identification of a novel super-enhancer of MYC and identification of patient-specific enhancer utilization to activate MYC expression in these tumors.

  Dataset EGAD00001011819

• Breast Cancer - immune clusters - RNA-seq

  In this study we use expression data from breast cancer tumors to define immune clusters in breast cancer. Immune clusters have gradual levels of immune infiltration. In the intermediate immune infiltration cluster, we found a worse prognosis which is independent of known clinicopathological features. We also found the immune clusters associated with treatment response. Further using gene expression data and deconvolution algorithms to dissect the immune contexture of the clusters.

  Dataset EGAD00001004985