11925 results for "cancer rna-seq"

in 17.39 milliseconds.

• RNA-seq analysis of metastatic prostate cancer solid tumor biopsies

  The prevalence and features of treatment-emergent small-cell neuroendocrine prostate cancer (t-SCNC) are not well characterized in the era of modern androgen receptor (AR)–targeting therapy. We sought to characterize the clinical and genomic features of t-SCNC in a multi-institutional prospective study. Patients with progressive, metastatic castration-resistant prostate cancer (mCRPC) underwent metastatic tumor biopsy and were followed for survival. t-SCNC is present in nearly one fifth of patients with mCRPC and is associated with shortened survival.

  Study EGAS00001006369

• Functional Enhancer Elements Drive Subclass-Selective Expression From Mouse to Human Neocortex

  A complete epigenomic map of human brain cell types will be necessary to fully understand their genetic regulation, and to create the next generation of non-species-restricted genetic tools for their functional characterization. Here we performed both bulk and single-nucleus ATAC-seq studies of fresh human neocortical samples excised during neurosurgery, in order to discover the functional genomic elements that discriminate cell types. This dataset contains 78 bulk layer-dissected ATAC-seq samples, and 3660 single-nucleus ATAC-seq samples from fresh acutely isolated human neurosurgical samples. Furthermore, from these data we identified and validated several enhancers for use in AAV context. We also provide validation single cell RNA-seq for 456 human acutely labeled neurosurgical neurons labeled by 3 unique enhancer-AAV vectors, and single cell RNA-seq for 1483 mouse neurons labeled in vivo by 11 unique enhancer-AAV vectors. Together these datasets provide high-resolution maps of single human neocortical cell types, as well as proof of the functional utility of the genomic elements discovered. As a whole these data will be important to furnish the next generation of cell type-specific functional tools and therapies in neuroscience.  

  Study phs002292

• Data access committee for RNA-seq as a tool for evaluating human embryo competence

  Dac EGAC00001001215

• RNA-Seq data for AEL paper

  Dataset EGAD00001003412

• A single-cell transcriptional gradient in human cutaneous memory T cells restricts Th17/Tc17 identity

  We identified a gradated transcriptional program of coordinately regulated inflammation-suppressive genes in psoriatic resident memory T cells. This dataset includes bulk RNA-seq for CRISPR-based deactivation of two core components of this inflammation-suppressive program, ZFP36L2 and ZFP36, in human PBMCs. It also includes scRNA-seq of cutaneous immune cells from psoriasis patients before and during therapeutic IL-23 blockade.

  Study EGAS00001006716

• Paired RNA-Seq of 32 samples of chemo-naïve and post-chemotherapy PDAC tumors

  Paired RNA-Seq of 32 samples of chemo-naïve and post-chemotherapy PDAC tumors (HIPO_015) to define the molecular and cellular impact of neoadjuvant chemotherapy. Transcriptome analysis combined with high resolution mapping of whole tissue sections identified GATA6 (Classical), KRT17 (Basal-like) and Cytochrome P450 3A (CYP3A) co-expressing cells that were preferentially enriched in post-CTX resected samples. The sequencing was done on HiSeq2000/HiSeq2500 using the Takara_SMARTer_Ultra_Low_Input_RNA_and_NEBNext_ChIP-Seq Kit.

  Dataset EGAD00001010884

• Comprehensive molecular and clinicopathological profiling of glioma

  Various molecular profiles are needed to classify malignant brain tumors, including gliomas, based on the latest classification criteria of the World Health Organization, and their poor prognosis necessitates new therapeutic targets. The Todai OncoPanel 2 RNA Panel (TOP2-RNA) is a custom-target RNA-sequencing (RNA-seq) using the junction capture method to maximize the sensitivity of detecting 455 fusion gene transcripts and analyze the expression profiles of 1,390 genes. This study aimed to classify gliomas and identify their molecular targets using TOP2-RNA. A total of 124 frozen samples of malignant gliomas were subjected to TOP2-RNA for classification based on their molecular profiles and the identification of molecular targets.

  Study JGAS000671

• 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

• Single-cell RNA-seq of immune cells from Melanoma tumors (Li et al, 2018) - DAC

  Dac EGAC00001001089

• Healthy human B-lymphopoiesis RNA-Seq reference using FACS sorted bone marrow aspirates

  Study EGAS00001007305

• Characterization of a novel MEF2D-BCL9 fusion positive acute lymphoblastic leukemia cell line RNA-Seq

  Study EGAS00001006802

• Cystic Fibrosis Varsity Project Multi-omics data

  This Dataset contains RNA-Seq, H3K27Ac ChIP-Seq, and ATAC-Seq data for 13 cystic fibrosis (CF) patients and 8 healthy volunteers (HV).

  Dataset EGAD00001009062

• RNA sequencing of genetically modified human iPSCs modeling patients with autism spectrum disorders (ASD)

  We generated two genetically modified iPSC lines. In each line, a single promoter variant identified in a patient with autism spectrum disorder (ASD) was introduced by using the CRISPR/Cas9 system. These mutant lines were analyzed by RNA-seq together with control lines to assess the impact of the introduced variant.

  Study JGAS000651

• RNA-seq of iPSC-derived hepatocyte-like cells

  We performed RNA-seq on polyA-enriched mRNA isolated from the original liver biopsy tissue (Liver tissue), primary liver cells (PLC), hepatocyte-like cells (HLCs) differentiated from induced pluripotent stem cells (iPSCs), and iPSCs. RNA libraries were prepared using the Illumina TruSeq Stranded mRNA Sample Preparation protocol (ref. RS-122-2101, Illumina, San Diego CA, US) and sequenced using the Illumina HiSeq2500 platform following the manufacturer’s protocol. Samples were sequenced in paired-end mode to a length of 2x76 base pairs. Images from the instrument were processed using the manufacturer’s software to generate FASTQ sequence files.

  Dataset EGAD00001003770

• Genetic regulation of RNA splicing in human pancreatic islets

  Here we provide access to newly generated RNA-seq data for 101 human islet samples used to map genetic effects on gene expression and alternative splicing (eQTLs and sQTLs) in a total of 399 human islets. We also make publicly available genotyping array data for 128 human islets, including the fraction of 101 human islet samples with existing RNA-seq data.

  Dataset EGAD00001009102

• Detection and genomic analysis of BRAF fusions in Juvenile Pilocytic Astrocytoma through the combination and integration of multi-omic data

  Juvenile Pilocytic Astrocytoma (JPAs) are highly vascular tumors and show pervasive immune infiltration, which can lead to low tumor cell purity in clinical samples. In some instances, this results in gene fusions that are difficult to detect with conventional omics approaches including RNA-Seq. To this effect, we applied RNA-Seq as well as linked-read whole-genome sequencing and in situ Hi-C as new approaches to detect and characterize low-frequency gene fusions at the genomic, transcriptomic and spatial level. Overall, we demonstrate the power of integrating multi-omic datasets to identify low frequency fusions and characterize the JPA genome at high resolution.

  Study EGAS00001006388

• NICHE - RNA-seq of MMR proficient and MMR deficient early stage colon cancers

  The dataset includes 77 FASTQ files from single-end total RNA sequencing on Illumina HiSeq2500 for 39 patients.

  Dataset EGAD00001006042

• single-cell RNA sequencing of human lung epithelial cells

  Single-cell RNA seq data of epithelial cells ((EpCAM-enriched by FACS) isolated from cryopreserved human lung tissue (3 samples, 3 donors)

  Dataset EGAD00001010251

• RNA-seq of AD, MCI and control ONS cells

  Total RNA sequencing of cultured ONS cells derived from patients with Alzheimer's disease (AD), individuals with mild cognitive impairment (MCI) and cognitively healthy controls.

  Dataset EGAD00001009395

• Natural variation of circulating RNAs in human serum

  Non-coding RNA (ncRNA) molecules have fundamental roles in cells and many are also stable in body fluids as extracellular RNAs. In these studies, we used RNA sequencing (RNA-seq) to investigate the profile of small non-coding RNA (sncRNA) in human serum. We analyzed more than 10 billion Illumina reads from more than 500 serum samples, included in the Norwegian population-based Janus Serum Bank (JSB). Our results suggest that many circulating RNAs in serum can be potential biomarkers and they are associated with different traits including age, sex, smoking, body size etc.

  Study EGAS00001002814

• Cystic fibrosis multi-omics study

  Cystic fibrosis (CF) is a genetic disorder affecting approximately 1 in 2,500 people in the UK. Here, we generated a number of high-throughput sequence data sets for monocytes and neutrophils from CF patients and matched healthy volunteers (HV); including ChIP-Seq (H3K27Ac), chromatin accessibility (ATAC-Seq), and transcript/gene expression (RNA-Seq) data. Analysis of gene expression and epigenetic profiles demonstrates a robust innate immune gene expression profile that distinguishes CF and HV during periods of disease exacerbation. Upregulation of pathways responsible for the production of proinflammatory cytokines is described.

  Study EGAS00001006421

• 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

• RNA-seq

  The RNA was extracted using the AS1390 PROMEGA kit according to the manufacturer’s instructions. The samples underwent sequencing using a Novaseq 6000 machine, equipped with an SP 200 cycles v1.5 cartridge. The sequencing process varied slightly across batches based on the input RNA and the library preparation kits used.

  Dataset EGAD50000002023

• RNA-sequencing

  Raw reads from RNA-sequencing of monocyte-derived macrophages from three individuals with heterozygous TET2 loss (Ly9, Ly11, Ly14) and two wild-type controls (Ly8 and an unrelated control). Libraries were prepared using ScriptSeq RNA-Seq Library Preparation Kit and Illumina sequenced with paired-end 75bp reads.

  Dataset EGAD00001004784

• Targeted RNA Expression Profiling via scTAMARA-seq

  This dataset comprises targeted single-cell RNA expression profiles derived from the same CD34+ bone marrow sample (patient X.1) used for scTAMARA_DNA. 120 RNA targets were selected using LASSO regression to capture key transcripts predictive of cell state within the hematopoietic compartment.

  Dataset EGAD00001015495

• Human pancreatic beta cell RNA-seq

  Dataset EGAD00001000393

• Characterization of a novel MEF2D-BCL9 fusion positive acute lymphoblastic leukemia cell line RNA-Seq derived

  Study EGAS00001006803

• Childhood Cancer Data Initiative (CCDI): Pediatric In Vivo Testing Program –Sarcoma, Kidney, and Liver Cancers

  The goal was to complete whole exome sequencing (WES) and RNA sequencing (RNA-Seq) on patient derived xenograft samples. Cancer in children is rare with approximately 15,700 new cases diagnosed annually in children 21 years or younger in the U.S. Through use of multimodality therapy (surgery, radiation therapy, and aggressive chemotherapy), 70% of patients will be 'cured' of their disease, and 5-year Event-Free Survival (EFS) exceeds 80%. Consequently, the number of patients that can be enrolled in phase I/II clinical trials is small, and most patients will have been extensively treated, hence drug/radiation resistant. Thus, preclinical studies that accurately translate into effective clinical therapy are an essential component of pediatric drug development. Our group has contributed to studies in the Pediatric Preclinical Testing Program (PPTP) and Pediatric Preclinical Testing Consortium (PPTC) that have led to clinical studies through Children's Oncology Group (COG). Of importance, we have developed and characterized over 330 Patient Derived Xenografts (PDX), developed from tumors both at diagnosis and relapse, that can be used to facilitate pediatric drug development as directed by FDA under the Research to Accelerate Cures and Equity for Children Act (RACE for Children Act).

  Study phs003160

• Histone and transcriptome profiling of glioblastoma initiating cells

  ChIP-seq and RNA-seq of glioblastoma initiating cells and their differentiated counterparts with and without inhibition/knockdown of KDMs.

  Dataset EGAD00001005124

• CBB post-mortem hippocampal short-RNA-seq

  Short RNA sequencing of post-mortem human hippocampi from the Calgary Brain Bank. The dataset includes patients with Alzheimer's disease (AD) and healthy control individuals (Ctrl).

  Dataset EGAD00001006886

• RNA-seq cohort of non-tumorous breast tissue from BRCA1/2 carriers

  Non-tumorous breast tissues from BRCA1 or BRCA2 carriers were subject to RNA sequencing. The total number of samples is 130.

  Dataset EGAD00001006746

• Exome and RNA seq data for female patient

  Exome and RNA sequencing data for EGAS00001003776 - one female patient with neurofibroma/schwannoma hybrid nerve sheath tumor (N/S HNST)

  Dataset EGAD00001005249

• Single cell sequencing data for chronic myeloid leukemia cell lines

  This dataset contains RNA sequencing information for Chronic Myeloid Leukemia. In total 2 single-end RNA-seq tumor cell line samples are present.

  Dataset EGAD00001009736

• Exploration of coding and non-coding variants in cancer using GenomePaint.

  GenomePaint (https://proteinpaint.stjude.org/genomepaint) is a dynamic visualization platform for whole-genome, whole-exome, transcriptome, and epigenomic data, featuring a novel design that captures the inter-relatedness between DNA variations and RNA expression. Regulatory non-coding variants can be inspected and discovered along with coding variants, and their functional impact further explored by examining 3D genome and/or ChIP-seq data generated from cancer cell lines. Further, GenomePaint correlates mutation and expression patterns with patient outcomes, and can display external data such as adult cancer datasets and user-provided custom tracks. We used GenomePaint to analyze multi-omics data from 3,652 pediatric cancers representing 16 histotypes, and demonstrate the visualization features through examples, including two that led to new insights into oncogenic mechanisms in pediatric cancer. The first is the discovery of a new class of pathogenic recurrent variants that cause aberrant splicing, disrupting the RING domain of CREBBP, a driver gene frequently mutated in relapsed pediatric leukemia. The second is the cis-activation of the MYC oncogene in a subset of B-lineage acute lymphoblastic leukemia (B-ALL) via duplication of the NOTCH1-MYC enhancer (N-ME), previously discovered only in T-lineage ALL. The regulatory impact of N-ME enhancer amplification was initially confirmed by allelic imbalance in published gene expression and ChIP-seq data and verified by additional Capture-C and fluorescence in situ hybridization data generated by follow-up experiments. These examples demonstrate the power of GenomePaint in enabling not only data visualization but also integrative genomic analysis that can lead to novel biological insight for follow-up experimental validation.

  Study EGAS00001004669

• Single cell RNA-seq and ATAC-seq of CD4+ T cells from blood and tumor of NSCLC patients

  This dataset contains fastq files for paired blood-tumor scRNA-seq samples from 5 NSCLC patients and paired blood-tumor scATAC-seq samples from 2 NSCLC patients, both sequenced with NovaSeq or Illumina HiSeq - Rapid Run.

  Dataset EGAD50000000424

• Epigenome of sorted human muscle stem cell

  This dataset contain RNA-seq, ChIP-seq, WGBS and ATAC-seq of 1 human muscle stem cell sample. NCAM+ITGB1+ CD31−CD45−CD34− were used as the sorting strategy for the sample. H3K27ac, H3K27me3, H3K4me1, H3K4me3, H3K36me3 and H3K9me3 are the targets of ChIP-seq.

  Dataset EGAD00001008686

• An atlas of transcribed enhancers across helper T cell diversity for decoding human diseases

  At 5' ends of RNAs, there is a unique "cap signature" derived from a 7-methylguanosine cap. By leveraging this signature, we developed ReapTEC (read-level pre-filtering and transcribed enhancer call), a method for simultaneously profiling gene expression and enhancer activities using 5'-end single-cell RNA sequencing (5' scRNA-seq). We applied ReapTEC and single-nucleus ATAC-seq to a total of ~1 million single human CD4+ T cells.

  Study JGAS000689

• RNA-seq of tumor samples from clear cell renal cell carcinoma patients included in the Translational Program of the NIVOREN GETUG-AFU-26 trial

  Study on RNA-seq data from tumor tissue samples of primary tumors of advanced clear cell renal cell carcinoma patients enrolled in the NIVOREN GETUG-AFU-26 trial who consented to and participated in the translational program. The goal of this study was to assess previously published gene expression signatures and evaluate their association with the benefit and/or resistance to nivolumab, as well as their association with circulating soluble factors.

  Study EGAS50000001057

• Celiac disease-specific intestinal T cells analyzed with HLA-class II tetramers, RNA-seq and mass cytometry have a narrow, autoimmune-associated phenotype

  Celiac disease (CD) is an HLA-DQ2/8-associated autoimmune enteropathy driven by activation of gluten-specific CD4+ T lymphocytes upon gluten consumption. Much less is known about the phenotype and function of these cells or their correlation, if any, to disease-relevant cells in other autoimmune disorders. Here we use mass cytometry and RNA seq to show that gluten-specific blood and gut T cells occupy a small and phenotypically distinct T-cell subset.

  Study EGAS00001003017

• Blood RNA-seq from Mexican DMD patients and healthy controls

  These data are part of a study that aimed to assess the potential of blood RNA-seq to track non-invasively disease progression for DMD. In particular, here we focus on a study designed to compare gene expression in blood from DMD patients to that of healthy controls. These data are analysed in the following manuscript: Signorelli, M., Ebrahimpoor, M. et al. (accepted). Peripheral blood transcriptome profiling enables monitoring disease progression in dystrophic mice and patients. To appear in EMBO Molecular Medicine.

  Study EGAS00001004907

• Whole genome sequence and RNA-seq data from paired tumour and germline samples from mesothelioma patients.

  Malignant pleural mesothelioma (MPM) has a poor overall survival with few treatment options. Whole genome sequencing (WGS) combined with RNA sequencing (RNA-seq) analysis of the immune features of MPM offers the prospect of identifying changes that could inform future clinical trials. We analysed somatic mutation and RNA-seq data from 229 MPM samples, including 58 MPM samples that had undergone WGS from our own institutions, together with other published data. This combined analysis identified somatic driver genes, including newly identified candidate genes. Whole genome doubling was a frequent event that correlated with shorter survival. Mutational signature analysis revealed dominant signatures and showed that defects in homologous recombination repair were infrequent in our cohort. Within the tumour immune environment we identified high M2 macrophage infiltrate linked with MMP2, MMP14, TGFB1 and CCL2 expression, representing an immunosuppressive environment. A small subset of samples had a higher proportion of CD8 T cells and a high cytolytic score, suggesting a ‘hot’ immune environment which is independent of the somatic mutations. We propose that our findings on genomic changes and subtypes of immune microenvironments may influence therapeutic planning in the future.

  Study EGAS00001005196

• cfDNA in Hereditary And High-Risk Malignancies (CHARM)

  Our goal is to improve early cancer detection by developing a blood test to predict cancer development in carriers using circulating DNA. As carriers develop cancer, they may have pre-cancerous cells which release this DNA into the blood (cell-free DNA; cfDNA), which can be detected with novel genetic technologies. We propose to use three complementary cfDNA assays:shallow whole genome sequencing (sWGS), Liquid-Biopsy Sequencing (LB-Seq) and Cell-free Methylated DNA Immunoprecipitation and High-throughput Sequencing (cfMeDip-Seq) for early cancer detection.

  Study EGAS00001006539

• Single-cell RNA-seq data from metastatic ovarian cancer for quality control study

  Quality control is a crucial preliminary step in any single-cell RNAseq experiment, where hard thresholds are commonly used. In order to develop a methodology for a more precise cell filtering in the early steps of a scRNAseq data analysis, we collected tissue samples before chemotherapy from 4 patients.

  Study EGAS00001005066

• Comparison of transcriptional response of induced pluripotent stem (iPS) cell-derived and monocyte-derived macrophages to bacterial lipopolysaccharide stimulation

  In the first part of this project, we will differentiate IPS cells from 5 human donors into macrophages, and extract RNA from unstimulated and LPS stimulated macrophages to perform RNA sequencing. We will also extract RNA before and after stimulation in blood- derived macrophages from 5 additional, unrelated healthy samples. In the second part of the project, RNA-seq data will be analysed to compare LPS response of these two macrophage populations. In summary, we will perform 75bp PE RNA-seq on 20 samples (10 pre and post stimulus), on the HiSeq 2500 platform. Samples will be multiplexed at 5 samples / lane, so we will require 4 flow cells in total.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 EGAD00001001106

• FASTQ files of the polyA+ (oligo-dT) RNA-Seq dataset from the POPS SGA (Small for Gestational Age) samples and their matched controls.

  FASTQ files of the polyA+ (oligo-dT) RNA-Seq dataset from the POPS SGA (Small for Gestational Age) samples and their matched controls. The POP study placental biopsies were collected within 30 minutes of birth and flash frozen in RNAlater (ThermoFisher). For each biopsy, total placental RNA was extracted from approximately 5 mg of tissue using the “mirVana miRNA Isolation Kit” (Ambion) followed by DNase treatment (“DNA-free DNA Removal Kit”, Ambion). RNA quality was assessed with the Agilent Bioanalyzer and all the samples with RIN values ≥ 7.0 were used in the downstream experiments. RNA-libraries were prepared from 1g of total placental RNA with the TruSeq Stranded mRNA Library Prep Kit (Illumina) which captures polyA-tailed transcripts by oligo-dT beads, then pooled and sequenced (single-end, 50bp) using a Single End V4 cluster kit and Illumina HiSeq2500

  Dataset EGAD00001006304

• Single-cell RNA-seq of immune cell subsets isolated from human tumors (Kaptein et al., 2024)

  Single-cell RNA-seq profiling of effector (KLRG1+ PD1-), transitional (KLRG1+ PD1-intermediate), dysfunctional (CD39+ PD1+) and memory (IL7Rα+) CD8 T cells isolated from 4 human tumors (1 melanoma, 1 renal carcinoma and 2 ovarian carcinoma). Respective cell populations were identified and isolated using FACS. FASTQ files contain gene expression data, feature barcode antibody capture or TCR data on individual CD8 T cell subsets across the 4 different samples.

  Dataset EGAD50000000376

• ICARUS-LUNG01-RNAseq

  Bulk RNA-seq was carried out on 20 pairs of frozen tumor biopsies. Differential gene expression (DGE) analyses was conducted, looking at the fold change of gene expression of matched on-T/BL samples in the overall population and, then, separately in responders and non-responders.

  Study EGAS50000000732

• RNA-seq of 2D cell culture and 3D muscle bundles generated by primary myoblast cell lines and the human iPSCs derived from mosaic FSHD patients, respectively.

  The dataset includes the RNA-seq on the 2D cell culture of primary myoblast cell lines derived from FSHD patients and healthy donors (n=3 in each condition) and on the 3D muscle bundles generated by the human iPSCs derived from healthy and FSHD-affected cells of mosaic FSHD patients (n=3 in each condition)

  Dataset EGAD50000000717

• BLUEPRINT release August 2016, RNA-Seq for Acute Promyelocytic Leukemia - MC2884, on genome GRCh38

  RNA-Seq data for 1 Acute Promyelocytic Leukemia - MC2884 sample(s). 1 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002352

• BLUEPRINT release January 2015, RNA-Seq for regulatory T cell

  RNA-Seq data for 1 regulatory T cell sample(s). 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001001174