7188 results for "({!join from=dataset_studies to=id v=$q1}) OR ("transcriptome" OR "RNA-seq" OR "rna sequencing" OR "rna-sequencing")"

in 135.04 milliseconds.

• BLUEPRINT release January 2015, RNA-Seq for erythroblast

  RNA-Seq data for 7 erythroblast sample(s). 29 run(s), 7 experiment(s), 7 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 EGAD00001001177

• BLUEPRINT release January 2015, RNA-Seq for central memory CD8-positive, alpha-beta T cell

  RNA-Seq data for 1 central memory CD8-positive, alpha-beta 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 EGAD00001001175

• BLUEPRINT release January 2015, RNA-Seq for CD38-negative naive B cell

  RNA-Seq data for 2 CD38-negative naive B cell sample(s). 2 run(s), 2 experiment(s), 2 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 EGAD00001001145

• BLUEPRINT release August 2014, RNA-Seq for erythroblast

  RNA-Seq data for 4 erythroblast sample(s). 22 run(s), 4 experiment(s), 4 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001000911

• BLUEPRINT release August 2015, RNA-Seq for CD38-negative naive B cell, on genome GRCh38

  RNA-Seq data for 2 CD38-negative naive B cell sample(s). 2 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001500

• BLUEPRINT release August 2015, RNA-Seq for regulatory T cell, on genome GRCh38

  RNA-Seq data for 1 regulatory T cell sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001546

• BLUEPRINT release January 2015, RNA-Seq for CD8-positive, alpha-beta T cell

  RNA-Seq data for 2 CD8-positive, alpha-beta T cell sample(s). 2 run(s), 2 experiment(s), 2 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 EGAD00001001137

• BLUEPRINT release August 2015, RNA-Seq for CD8-positive, alpha-beta thymocyte, on genome GRCh38

  RNA-Seq data for 1 CD8-positive, alpha-beta thymocyte sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001478

• BLUEPRINT release January 2015, RNA-Seq for endothelial cell of umbilical vein (resting)

  RNA-Seq data for 1 endothelial cell of umbilical vein (resting) 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 EGAD00001001142

• BLUEPRINT release January 2015, RNA-Seq for effector memory CD8-positive, alpha-beta T cell

  RNA-Seq data for 1 effector memory CD8-positive, alpha-beta 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 EGAD00001001153

• BLUEPRINT release August 2015, RNA-Seq for mature neutrophil, on genome GRCh38

  RNA-Seq data for 14 mature neutrophil sample(s). 14 run(s), 14 experiment(s), 14 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001474

• BLUEPRINT release August 2015, RNA-Seq for CD8-positive, alpha-beta T cell, on genome GRCh38

  RNA-Seq data for 2 CD8-positive, alpha-beta T cell sample(s). 2 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001488

• BLUEPRINT release August 2015, RNA-Seq for conventional dendritic cell, on genome GRCh38

  RNA-Seq data for 1 conventional dendritic cell sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001540

• BLUEPRINT release August 2015, RNA-Seq for macrophage, on genome GRCh38

  RNA-Seq data for 18 macrophage sample(s). 19 run(s), 18 experiment(s), 18 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001582

• BLUEPRINT release August 2015, RNA-Seq for alternatively activated macrophage, on genome GRCh38

  RNA-Seq data for 4 alternatively activated macrophage sample(s). 6 run(s), 4 experiment(s), 4 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001586

• BLUEPRINT release January 2015, RNA-Seq for cytotoxic CD56-dim natural killer cell

  RNA-Seq data for 3 cytotoxic CD56-dim natural killer cell sample(s). 3 run(s), 3 experiment(s), 3 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 EGAD00001001159

• BLUEPRINT September 2016, RNA-Seq Acute Lymphocytic Leukemia for precursor B cell from bone marrow, on Genome GRCh38

  RNA-Seq data for 8 sample(s) Acute Lymphocytic Leukemia for precursor B cell from bone marrow, on Genome GRCh38. 8 run(s), 8 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002953

• BLUEPRINT September 2016, RNA-Seq for monocyte T=0day from venous blood, on Genome GRCh38

  RNA-Seq data for 1 sample(s) for monocyte T=0day from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002955

• BLUEPRINT September 2016, RNA-Seq T-cell lymphoma for helper T cell from venous blood, on Genome GRCh38

  RNA-Seq data for 2 sample(s) T-cell lymphoma for helper T cell from venous blood, on Genome GRCh38. 2 run(s), 2 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002956

• BLUEPRINT September 2016, RNA-Seq for monocyte T=2day_RANK_M-CSF from venous blood, on Genome GRCh38

  RNA-Seq data for 1 sample(s) for monocyte T=2day_RANK_M-CSF from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002957

• BLUEPRINT September 2016, RNA-Seq for monocyte T=1day_M-CSF_S100A9_4hr_RANL from venous blood, on Genome GRCh38

  RNA-Seq data for 1 sample(s) for monocyte T=1day_M-CSF_S100A9_4hr_RANL from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002959

• BLUEPRINT September 2016, RNA-Seq for monocyte T=6day_S100A9_RANKL_M-CSF from venous blood, on Genome GRCh38

  RNA-Seq data for 1 sample(s) for monocyte T=6day_S100A9_RANKL_M-CSF from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002960

• BLUEPRINT September 2016, RNA-Seq for monocyte T=10day_S100A9_RANKL_M-CSF from venous blood, on Genome GRCh38

  RNA-Seq data for 1 sample(s) for monocyte T=10day_S100A9_RANKL_M-CSF from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002961

• BLUEPRINT September 2016, RNA-Seq Acute Myeloid Leukemia for blast cell from bone marrow, on Genome GRCh38

  RNA-Seq data for 1 sample(s) Acute Myeloid Leukemia for blast cell from bone marrow, on Genome GRCh38. 1 run(s), 1 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002962

• BLUEPRINT September 2016, RNA-Seq Acute Lymphocytic Leukemia for precursor B cell from venous blood, on Genome GRCh38

  RNA-Seq data for 6 sample(s) Acute Lymphocytic Leukemia for precursor B cell from venous blood, on Genome GRCh38. 6 run(s), 6 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002963

• BLUEPRINT September 2016, RNA-Seq for monocyte T=1day_4hr_RANK from venous blood, on Genome GRCh38

  RNA-Seq data for 1 sample(s) for monocyte T=1day_4hr_RANK from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002964

• BLUEPRINT September 2016, RNA-Seq for monocyte T=2day_S100A9_RANKL_M-CSF from venous blood, on Genome GRCh38

  RNA-Seq data for 1 sample(s) for monocyte T=2day_S100A9_RANKL_M-CSF from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002965

• BLUEPRINT September 2016, RNA-Seq for monocyte T=10day_RANK_M-CSF from venous blood, on Genome GRCh38

  RNA-Seq data for 1 sample(s) for monocyte T=10day_RANK_M-CSF from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002966

• BLUEPRINT September 2016, RNA-Seq for monocyte T=6day_RANK_M-CSF from venous blood, on Genome GRCh38

  RNA-Seq data for 1 sample(s) for monocyte T=6day_RANK_M-CSF from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002967

• BLUEPRINT September 2016, RNA-Seq Acute Myeloid Leukemia for myeloid cell from venous blood, on Genome GRCh38

  RNA-Seq data for 2 sample(s) Acute Myeloid Leukemia for myeloid cell from venous blood, on Genome GRCh38. 2 run(s), 2 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002968

• BLUEPRINT release August 2014, RNA-Seq for CD8-positive, alpha-beta T cell

  RNA-Seq data for 1 CD8-positive, alpha-beta T cell sample(s). 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001000912

• BLUEPRINT release January 2015, RNA-Seq for CD14-positive, CD16-negative classical monocyte

  RNA-Seq data for 8 CD14-positive, CD16-negative classical monocyte sample(s). 8 run(s), 8 experiment(s), 8 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 EGAD00001001148

• BLUEPRINT release January 2015, RNA-Seq for effector memory CD4-positive, alpha-beta T cell

  RNA-Seq data for 1 effector memory CD4-positive, alpha-beta 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 EGAD00001001163

• BLUEPRINT release January 2015, RNA-Seq for central memory CD4-positive, alpha-beta T cell

  RNA-Seq data for 1 central memory CD4-positive, alpha-beta 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 EGAD00001001172

• BLUEPRINT release August 2015, RNA-Seq for class switched memory B cell, on genome GRCh38

  RNA-Seq data for 1 class switched memory B cell sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001531

• BLUEPRINT release August 2015, RNA-Seq for memory B cell, on genome GRCh38

  RNA-Seq data for 1 memory B cell sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001542

• Delineating pediatric brain tumor progression using single-nuclei sequencing

  raw fastq files from the single-nuclei RNA-seq experiments generated from 42 paediatric CNS tumour samples by the 10X Genomics technology.

  Dataset EGAD50000001831

• Single-cell RNA-seq from tumor-on-chip (TOC)

  8 Fastq files of single-cell RNAseq data from tumor-on-chip (TOC) after 42h of TNBC and CAF mono- or co-culture

  Dataset EGAD50000001296

• Esophageal Adenocarcinoma Organoid scRNAseq data

  This is 10X single cell RNA-seq data of esophageal adenocarcinoma organoids.

  Dataset EGAD00001007525

• 2_cortical-neurons_HD_vs_Ctrl_DMSO_Branaplam

  n=3 Ctrl and n=3 HD iPSC lines differentiated into cortical neurons were treated with DMSO or 10nM Branaplam for 72h and RNA-seq was performed.

  Dataset EGAD00001008808

• RNAseq following stent placement and removal in a porcine model 

  This dataset includes 2*76bp RNA-seq reads from 9 pigs sequenced using Illumina NextSeq500.

  Dataset EGAD00001009783

• Human Epidermis scRNA

  Single cell RNA-seq analysis of human skin.

  Dataset EGAD00001004367

• MOSAIC Window DLBCL Data

  This dataset will include Spatial Transcriptomics from the 10x Genomics Visium SD technology, Single-Cell RNA-Seq from the 10x Genomics Chromium Flex protocol, Bulk RNA-Seq (sequenced on Illumina), WES (sequenced on Illumina), H&E, and Clinical data from 10 DLBCL patients. For Visium and Chromium data we are sharing the outputs of respectively Space Ranger and Cell Ranger. For Bulk RNA-Seq we are including processed files such as counts.tsv, FPKM.tsv, fusion_genes.tsv, TPM count matrix.tsv, DESeq2 count matrix.tsv, multiqc_report. For WES, we are sharing the presence or absence of single nucleotide variants (SNVs), small insertions and deletions (indels), and copy number variants (CNVs).* Researchers from private or public institutions outside the MOSAIC Consortium will be able to apply to access this data and, pending approval, use the data for their research.

  Dataset EGAD50000001702

• MOSAIC Window Ovarian Data

  This dataset will include Spatial Transcriptomics from the 10x Genomics Visium SD technology, Single-Cell RNA-Seq from the 10x Genomics Chromium Flex protocol, Bulk RNA-Seq (sequenced on Illumina), WES (sequenced on Illumina), H&E, and Clinical data from 15 Ovarian patients. For Visium and Chromium data we are sharing the outputs of respectively Space Ranger and Cell Ranger. For Bulk RNA-Seq we are including processed files such as counts.tsv, FPKM.tsv, fusion_genes.tsv, TPM count matrix.tsv, DESeq2 count matrix.tsv, multiqc_report. For WES, we are sharing the presence or absence of single nucleotide variants (SNVs), small insertions and deletions (indels), and copy number variants (CNVs).* Researchers from private or public institutions outside the MOSAIC Consortium will be able to apply to access this data and, pending approval, use the data for their research.

  Dataset EGAD50000001704

• MOSAIC Window Mesothelioma Data

  This dataset will include Spatial Transcriptomics from the 10x Genomics Visium SD technology, Single-Cell RNA-Seq from the 10x Genomics Chromium Flex protocol, Bulk RNA-Seq (sequenced on Illumina), WES (sequenced on Illumina), H&E, and Clinical data from 10 Mesothelioma patients. For Visium and Chromium data we are sharing the outputs of respectively Space Ranger and Cell Ranger. For Bulk RNA-Seq we are including processed files such as counts.tsv, FPKM.tsv, fusion_genes.tsv, TPM count matrix.tsv, DESeq2 count matrix.tsv, multiqc_report. For WES, we are sharing the presence or absence of single nucleotide variants (SNVs), small insertions and deletions (indels), and copy number variants (CNVs).* Researchers from private or public institutions outside the MOSAIC Consortium will be able to apply to access this data and, pending approval, use the data for their research.

  Dataset EGAD50000001706

• Single cell RNA-seq and ATAC-seq of human fetal forebrain tissue, weeks 8 to 11.

  Single cell RNA-seq from 6 and single nuclei ATAC-seq from 3 human fetal tissue samples. Samples from 8 to 11 weeks. Includes a 8.5 weeks samples with matching both ATAC-seq and RNA-seq runs. Data was sequenced using 10X Genomics chromium technology, for scRNA-seq samples belong to v2 and v3.

  Dataset EGAD00001008653

• University of Pennsylvania CAR T Cell Responding and Non-responding Patients

  The adoptive transfer of autologous T cells genetically modified to express a CD19-specific, 4-1BB/CD3zeta-signaling chimeric antigen receptor (CAR; CTL019) has shown remarkable activity in patients with B acute lymphoblastic leukemia. Similar therapy can induce long-term remissions for relapsed/refractory chronic lymphocytic leukemia (CLL) patients, but in only a small subset of subjects. The determinants of response and resistance to CTL019 therapy of CLL are not fully understood. We employed next generation sequencing of RNA (RNA-seq) to identify predictive indicators of response to CTL019 treatment. We performed RNA-seq on leukapheresis and manufactured infusion product T cells from patients with heavily pre-treated and high-risk disease. To characterize potency, we also performed RNA-seq on the cellular infusion product after CAR-specific stimulation. Our findings indicate that durable remission in CLL is associated with gene expression signatures of early memory T cell differentiation (e.g., STAT3), while T cells from poorly- or non-responding patients exhibited elevated expression of key regulators of late memory as well as effector T cell differentiation, apoptosis, aerobic glycolysis, hypoxia and exhaustion. These gene expression signatures, along with additional immunological biomarkers, may be used to identify which patients are most likely to respond to cellular therapies and suggest manufacturing modifications that might potentiate the generation of maximally efficacious infusion products. In a follow-up study, we report multiplex CRISPR-Cas9 gene editing on T cells in humans to test the hypothesis that disrupting genes encoding the endogenous T cell receptor (TCR), TCRα (TRAC) and TCRβ (TRBC), as well as PD-1 (PDCD1) would enhance the efficacy of autologous T cells engineered to express a transgenic NY-ESO TCR. We used single cell RNA-seq to comprehensively characterize the transcriptomic phenotype of this T cell product and its evolution over time in a patient with sarcoma. Notably, this patient's transferred T cells that persisted in vivo demonstrated increases in expression of genes associated with a central memory state (IL7R, TCF7). These findings may guide future trials involving administration of genetically redirected, genome -edited T cells.In this follow-up study, we investigated whether CRISPR-Cas9-mediated disruption of PDCD1 and/or CTLA-4 could restore CART dysfunction in healthy donors and/or CLL patients. We show that depletion of CTLA-4 rescues the function of T cells from leukemia patients that previously failed CART cell treatment. We performed single-cell RNA sequencing and characterized the transcriptomic landscape of CTLA-4 KO CART19 cells that showed higher proliferation and anti-tumor efficacy by permitting unopposed CD28 signaling and maintenance of CAR expression on the T cell surface under stress-test conditions of chronic antigen exposure. Our findings reveal that selective disruption of CTLA-4 invigorates dysfunctional patient T cells, providing a strategy for increasing patient responses to CART cell therapy.

  Study phs001707

• Laser Capture Microscopy (LCM)-RNAseq for Topological Mapping of Synovial Pathology during Rheumatoid Arthritis

  Synovial tissue from the hip or knee was collected from rheumatoid arthritis (RA) and osteoarthritis (OA) patients at the time of joint replacement surgery. Samples were analyzed using laser capture microdissection (LCM) followed by RNA-seq to evaluate the transcriptome in distinct synovial compartments. Results indicated that synovial compartments have both shared and distinct transcriptional signatures that correspond to key pathways relevant to RA pathogenesis.

  Study phs003587

• FusionSeq: a modular framework for finding gene fusions by analyzing Paired-End RNA-Sequencing data

  We have developed FusionSeq to identify fusion transcripts from paired-end RNA-sequencing. FusionSeq includes filters to remove spurious candidate fusions with artifacts such as misalignments or random pairing of transcript fragments and it ranks candidates according to several statistics. It also has a module to identify exact sequences at breakpoint junctions. FusionSeq detected known and novel fusions in a specially sequenced calibration data set, including 8 cancers with and without known rearrangements.

  Study phs000311

• Identification of Novel Therapeutic Targets for Calcific Aortic Valve Stenosis Using Integrative Genomics

  In order to identify novel therapeutic targets for calcific aortic valve stenosis, we have generated a large transcriptomic dataset from RNA sequencing of human aortic valve tissues from 500 individuals undergoing aortic valve replacement or heart transplant at the Institut universitaire de cardiologie et de pneumologie de Québec – Université Laval (QUEBEC-CAVS-RNA). This dataset represents a unique resource to understand the molecular mechanisms underlying aortic valve diseases.

  Study phs003541

• RNA sequencing of serial samples from patients enrolled in the NA-PHER2 trial

  Improved outcomes in HER2+ breast cancer have resulted from chemotherapy and anti-HER2 therapies. However, HER2+ER+ cancers exhibit lower response rates. The NA-PHER2 trial investigated chemo-free preoperative HER2 and CDK4/6 blockade with or without endocrine therapy in HER2+ER+ breast cancer. Through RNA sequencing and tumour infiltrating lymphocytes (TIL) assessment in serial biopsies we identified predictive biomarkers of pCR, Day 14 Ki67 response, and unveiled treatment-induced molecular changes.

  Study EGAS50000000248

• Single-cell RNA-sequencing and cellular indexing of transcriptomes and epitopes of peripheral blood mononuclear cells and peritoneal fluid from patients with achalasia

  The data published here contains cellular indexing of transcriptomes and epitopes (CITE-seq) and single-cell RNA- sequencing (scRNAseq) data on patients with achalasia. Paired PBMC and PF were subjected to 3' scRNAseq and CITE-seq, respectively. All single-cell data was generated using the 10X Genomics (Chromium Single Cell 3’ Reagent) and sequenced in a paired-ended fashion on the NovaSeq6000.

  Study EGAS50000000174

• Single nuclei RNA sequencing on Primary and Maladaptive FSGS patient samples

  We used single-nucleus RNA-sequencing to identify differentially expressed transcriptional signatures in kidney biopsies of well-phenotyped primary vs. maladaptive FSGS patients. We included cryopreserved kidney biopsy cores from adult patients with newly diagnosed primary FSGS (n = 9, all nephrotic), maladaptive FSGS (n = 9, not nephrotic), proteinuric controls (PLA2R-positive membranous nephropathy, n = 3), and healthy controls (n = 4). We identified 120,751 high-quality nuclei, including 2,471 podocytes and 1,574 parietal epithelial cells (PECs).

  Study EGAS50000001070

• 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

• RNA sequencing data of in vitro differentiated megakaryocyte cells transduced with E527K and WT SRC

  For RNA sequencing (RNAseq), CD34+ hematopoietic stem cells (HSC) were isolated from healthy controls before transduction with WT-SRC and E527K-SRC lentiviral vectors in triplicate and differentiation to MK. RNA was extracted from the complete cell population as the aim was to detect differences in genes regulating MK maturation and differentiation. A total of six WT-SRC and six E527K-SRC RNA samples were used for RNAseq to identify differentially expressed genes.

  Study EGAS00001005808

• RNA sequencing in primary human macrophages overexpressing ETS2

  We investigated an intergenic haplotype on chr21q22, linked to five different inflammatory diseases, and discovered a mechanism that orchestrates macrophage responses during chronic inflammation. We delineated how the risk haplotype increases expression of the causal gene, ETS2, and demonstrated that ETS2 is necessary for inflammatory macrophage effector functions. To establish whether ETS2 is sufficient to drive inflammatory responses, we overexpressed ETS2 in a dose-dependent manner and performed RNA-sequencing to characterise the transcriptional effects.

  Study EGAS00001007554

• Prognostic whole-genome and transcriptome signatures in colorectal cancers

  This dataset consists of RNA-seq CRAM raw-data files of 1063 primary colorectal cancer and 120 adjacent normal tissue samples. The expression profiles for these samples can be found at the ArrayExpress with accession number E-MTAB-12862.

  Dataset EGAD50000000169

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

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

  Dataset EGAD00001004076

• 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

• scRNA-seq of patient-derived PDAC organoids

  We derived PDAC organoids from primary tumors of 18 patients, together with two matched samples from liver metastases. By single-cell RNA sequencing, we show that PDAC organoids consist of ductal cells with patient-specific expression of several gene groups, including genes which encode cell surface proteins. We report ‘classical’ and ‘basal-like’ cells coexisting within single primary tumors or metastases, with greater intratumor subtype heterogeneity linked to higher tumor grade. Single-cell transcriptome analysis of PDAC organoids and primary PDAC identified distinct tumor cell states shared across patients, including a cycling progenitor cell state and a differentiated secretory state. We show that these cell states are connected by a differentiation hierarchy, with ‘classical’ subtype cells concentrated at the endpoint of this hierarchy.

  Study EGAS00001004661

• Performance assessment of total RNA sequencing of human biofluids and extracellular vesicles

  Dac EGAC00001001591

• Single-cell RNA-sequencing reveals that glioblastoma recapitulates a normal neurodevetlopmental hierarchy

  Dac EGAC00001001625

• RNA sequencing of control OM cells exposed to traffic-related air pollutants

  Study EGAS00001007528

• RNA Sequencing of paediatric patients with B lymphoblastic leukemia

  Study EGAS00001003726

• Merkel Cell Carcinoma Tissue and Data Repository

  Merkel cell carcinoma (MCC) is a rare, aggressive neuroendocrine skin cancer with increasing incidence in the United States. In this study we performed the first whole genome sequencing of three Merkel cell carcinomas with their matched normal tissues for somatic variant calling. From these data we describe the likely mechanism of Merkel cell polyomavirus integration and focal host genomic amplifications in two tumors and the dominance of UV-mediated mutagenesis in a virus-negative tumor. We also performed poly-A RNA sequencing on a total of six Merkel cell carcinomas to address expression differences between virus-positive and virus-negative MCC.

  Study phs002189

• Systematic Analysis of Transcription Program Regulation by Transcription Factor EB (TFEB)

  In order to evaluate the effects of TFEB, a master regulator of autophagy and lysosomal biogenesis, CRISPR-Cas9 TFEB knock out cell lines were generated and reconstituted with wild-type TFEB (TFEB-WT), a vector control (TFEB-KO) or TFEB engineered to remain localized to the cytosol (TFEB-cyto) or to the nucleus (TFEB-nuc). RNA sequencing was performed on engineered cell lines at steady-state or following exogenous stimulation with autophagy inducer (Torin1 or Salmonella bacterial infection). Comparative analyses were performed to identify TFEB-dependent transcriptional response to subcellular localization at steady-state or to exogenous stimuli.

  Study phs002099

• RNA seq on 19 samples of Radiation-Induced Meningiomas

  Purpose: Majority of pediatric cancers require the irradiation of the central nervous system (CNS), and as more patients survive into adulthood from improved oncological therapy the sequelae of brain radiation are increasing in prevalence. Radiation-induced meningiomas (RIMs), one such secondary effect, demonstrate a clinically more aggressive behaviour than sporadic meningiomas (SMs). We aimed to describe the genomic mutational landscape of RIMs.Methods: We analyzed a principal cohort of 18 RIMs, with 31 RIMs overall, from patients who received childhood radiation therapy and 30 SMs, as a comparator population. We performed a multiplatform integrative genomic analysis; including methylation, whole exome and RNA sequencing. Results: RIMs exhibited a five-fold increase in copy number alterations, commonly the loss of chromosome 1p (17/18 RIMs) and 22q (17/18 RIMs), which was significantly more than observed in sporadic meningiomas. Furthermore, RNA sequencing data revealed an NF2 gene fusion event in 35.3% of RIMs. In all 6 cases, there was a complete NF2 exon spliced into a complete exon of a reciprocal gene, suggesting that the breakpoints of genomic rearrangement are intronic. All tumours with the NF2 fusion also possessed monosomy of chromosome 22q, rendering the cells with homozygous disruption of NF2. Clinically, RIMs with the NF2 fusion exhibited ill-defined borders and a tendency to develop in anatomic frontal location. Also, targeted sequencing panel confirmed that RIMs had fewer nonsynonymous NF2 mutations (6.5% vs. 30% in SM) and absence of mutations in TRAF7, SMO, KLF4, PIK3CA and AKT1, genes traditionally involved in SMs.Conclusion: Our study demonstrates that RIMs have distinct genomic drivers of oncogenesis as compared to SMs, specifically NF2 inactivation through fusion event. Radiation therapy possibly triggers genomic structural rearrangements through error-prone repair of double-stranded DNA breaks.

  Study EGAS00001002318

• Longitudinal 3'RNA-Seq data from MEMORI trial

  80 bam files generated from 3'RNAseq of tumour biopsies from oesophageal adenocarcinoma. Samples were collected within the clinical MEMORI trial.

  Dataset EGAD50000000357

• cHCC-ICC RNAseq

  The RNA-seq data of 97 tumor samples from 77 cHCC-ICC cases, data of two other HCC tumor samples were also included.

  Dataset EGAD00001005182

• RCC transcriptomic data

  RNA-seq data. 287 Japanese RCC cases.

  Dataset EGAD00001010003

• Whole exome and transcriptome sequencing of gastric cancer patients

  Whole exome and RNA-seq of matched normal gastric mucosa (n=34) and gastric cancer tissues (n=34) from gastric cancer patients (n=34)

  Dataset EGAD00001004164

• Performance assessment of Total RNA sequencing of human biofluids and extracellular vesicles

  Study EGAS00001004428

• Whole Exome and RNA sequencing of synchronous female bilateral breast cancers

  Study EGAS00001006910

• RNA sequencing of chondrosarcoma

  To profile chondrosarcoma patients.

  Study EGAS00001004585

• RNAseq of preneoplasia lung adenocarcinoma

  RNA sequencing of 168 pulmonary samples including lung preneoplasia atypical adenomatous hyperplasia (AAH, N=38), adenocarcinoma in situ (AIS, N=22), minimally invasive adenocarcinoma (MIA, N=19) and invasive lung adenocarcinoma (ADC, N=38) and adjacent lung tissues (Normal, N=62).

  Study EGAS50000000271

• Characterization of a Metastatic Cervical Cancer Patient and HPV18 Integration Using Next Generation Sequencing

  In this study, we used shallow whole genome, exome, and RNA sequencing to genomically and transcriptomically characterize a cervical squamous carcinoma lesion metastatic to the lung and to detect and analyze HPV infection in the same sample.

  Study phs000628

• Understanding the Progression of Metastatic Colorectal Cancer

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

  Study phs001722

• Single cell RNA sequencing of co-culture of human organoids with polarized pro-inflammatory (M1) or anti-inflammatory (M2) macrophages

  In order to know if the mechanisms we identified in mice – demonstrating that macrophages are able to orchestrate the intestinal regenerative process – are conserved in humans we develop a co-culture system with human intestinal organoids and human polarized macrophages. We co-culture human organoids with pro-inflammatory or anti-inflammatory macrophages for 48h. On day 3 cells were collected to perform single cell RNA sequencing.

  Dac EGAC50000000270

• Effects of KSP inhibitor filanesib in aggressive hepatoblastoma PDX cells

  Aim of this RNA sequencing dataset has been to asses effects caused by the KSP inhibitor filanesib in aggressive hepatoblastoma PDX cells. Two cell lines (HB-279 and HB-284) were utilised. DMSO-treated cells were used as controls.

  Study EGAS50000000899

• Comprehensive molecular and clinicopathological profiling of desmoid tumors

  Previous studies have not clearly identified a prognostic factor for desmoid tumors (DT). Whole-exome sequencing and/or RNA sequencing were performed in 64 cases of DT to investigate the molecular profiles in combination with the clinicopathological characteristics.

  Study JGAS000270

• Genome-wide integrative analysis of pediatric pancreatoblastoma

  Pancreatoblastoma is the most common pancreatic malignancy of young children, but its molecular pathogenesis remains poorly understood. To understand the molecular pathogenesis of pancreatoblastoma, we comprehensively analysed the whole exome sequencing, RNA sequencing, SNP array, and methylation array data of pancreatoblastoma.

  Study JGAS000088

• Single-cell profiling maps the spectrum of crosstalk between glioma cells and tumor associated macrophages

  Tumor associated macrophages (TAMs) are a heterogeneous glioma infiltrate, implicated in cancer progression. We performed single-cell RNA-sequencing, to survey TAM response-patterns in glioma.

  Study EGAS00001002185

• Integrated genetic and epigenetic analysis of myxofibrosarcoma

  Myxofibrosarcoma (MFS) is a common histological subtype of adult soft tissue sarcoma characterized by an infiltrative growth pattern and a high propensity for local recurrence. We underwent whole exome sequencing, RNA sequencing, and methylation analysis of MFS.

  Study EGAS00001002889

• Gene_epression_regulation_in_cytokine_induced_immune_cell_states

  We isolated T cells and monocotyes from healthy platelet donors and cultured them in resting and stimulated conditions with addition of a range of cytokines. We performed RNA sequencing to assess impact of different disease-relevant cytokines upon immune cell responses.

  Study EGAS00001003823

• HLF COPD Transcriptomics

  We generated transcriptomes of primary human lung fibroblasts (HLFs) isolated from distal parenchyma of ex-smoker controls and COPD patients, with both mild and severe disease. RNA sequencing analysis demonstrated dysregulation of genes involved in proliferation, DNA repair, and extracellular matrix organization.

  Study EGAS00001006602

• Peripheral blood RNA-sequencing in 4,732 participants of the INTERVAL cohort

  We performed bulk RNA-sequencing on peripheral blood collected from 4,732 blood donors recruited as part of the INTERVAL study. Using these data, we mapped gene expression and splicing quantitative trait loci (QTLs). Then, we integrated these data with protein, metabolite and lipid QTLs in the same individuals. The study aimed to identify the shared genetic etiology across transcriptional phenotypes, molecular traits and health outcomes in humans.

  Dataset EGAD00001008015

• 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 conditions, as well as in the presence of Th1, Th2, Th17 and iTreg cocktail. In addition, T cells were stimulated in the presence of IL-10, IL-21, IL-27, IFNb and TNFa. We performed bulk RNA sequencing to assess impact of different disease-relevant cytokines upon T cell response.

  Dataset EGAD00001005291

• Improved Sezary cell detection and novel insights into immunophenotypic and molecular heterogeneity in Sézary syndrome

  We performed a prospective investigation in Sézary syndrome by the application of a standardized multiparameter flow cytometry, FACS-cell sorting, and RNA-sequencing for an in-depth immunophenotypic and transcriptional profiling of Sézary cells.

  Study EGAS00001005229

• RNA sequencing data of 66 matched primary and recurrent high grade serous ovarian cancer

  Dac EGAC00001000741

• Targeted RNA sequencing of breast cancer GWAS loci

  Dataset EGAD00001004498

• Angiosarcoma RNA sequencing

  Extension of angiosarcoma whole genome sequencing study

  Dataset EGAD00001000738

• Studying Glioblastoma in a Human Organoid Tumor Transplantation Model

  This study comprises two complementary investigations that leverage innovative human model systems and cutting-edge molecular profiling to dissect glioblastoma (GBM) heterogeneity and tumor-microenvironment interactions. The first study uses a novel Human Organoid Tumor Transplantation (HOTT) model, in which freshly dissociated GBM tumor cells from five patients were transplanted into human embryonic stem cell-derived cortical organoids. This system enables the interrogation of tumor and microenvironment interactions in a human-specific, developmentally relevant context. Using single-cell RNA sequencing (scRNA-seq) and single-nucleus RNA-seq (snRNA-seq), the authors profiled over 216,000 cells, analyzing tumor heterogeneity across multiple media conditions. Ligand-receptor analysis (CellChat), immunofluorescence, and RNAScope were used to validate findings. The study revealed that the HOTT model faithfully recapitulates primary GBM cell types and microenvironmental components, and uncovered a novel bidirectional signaling axis mediated by PTPRZ1 that influences both tumor migration and cell fate in a context-dependent manner. PTPRZ1 is identified to be important for intercellular communication between tumor and microenvironmental cells, while PDGFRB, NOTCH3, HOPX, FAM107A, CLDN5, RGS5, FOXC1, SOX18 are key markers of the neurovascular progenitor that we identify to be a multipotent, restricted progenitor in GBM. Related datasets include the inclusion of immune cells in the HOTT system, termed “iHOTT”. The second study focuses on identifying and characterizing a rare but functionally potent neurovascular progenitor (NVP) population within GBM tumors. By generating a meta-atlas from seven publicly available GBM scRNA-seq datasets, the authors identified a unique tumor-derived cell population co-expressing neural progenitor and vascular markers. This population was validated in situ and in vivo through immunostaining and lineage tracing via DNA barcoding in the HOTT system. Functional knockdown of NVPs in a murine GBM model resulted in reduced cycling cells, altered tumor composition, and increased survival. Clonal analysis showed NVPs have dual potency to give rise to both neuronal and vascular-like tumor cells, contributing significantly to tumor cell diversity. Molecular technologies used across the studies include: Single-cell and single-nucleus RNA sequencing DNA barcoding and clonal lineage tracing (CellTag) Population information: Tumor samples were obtained directly from multiple GBM patients (all IDH1 wild-type, adult), including core and peripheral tumor regions. Human cortical organoids derived from human embryonic stem cells (hESCs) served as the microenvironment in the HOTT model. Principal findings include: HOTT recapitulates the heterogeneity and cell type fidelity of GBM, while enabling the study of tumor–microenvironment signaling. PTPRZ1 has opposing roles in tumor and microenvironment, influencing GBM cell migration and fate via non-catalytic mechanisms. A novel GBM neurovascular progenitor population (NVP) was identified, validated, and shown to contribute clonally to distinct tumor cell types. Elimination of NVPs in vivo reduces tumor aggressiveness and improves survival. Data to be available through dbGaP: Raw and processed single-cell and single-nucleus RNA-seq data (HOTT model and NVP studies) CellTag barcode-labeled scRNA-seq clonal lineage data Associated metadata including patient of origin, experimental condition, and sample annotations.

  Study phs003936

• Dataset for Stromal-induced epithelial-mesenchymal transition induces drug resistance in acute lymphoblastic leukemia

  RNA-seq was performed to compare gene expression profiles between 11 patient adherent ALL samples and nonadherent ALL samples.

  Dataset EGAD00001009056

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

  This study includes treatment-naïve fresh tissue sample from 4 HGSOC patients.

  Dataset EGAD00001006984

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

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

  Dataset EGAD00001005137

• Leiomyosarcoma Cancer Transcriptome Sequencing

  RNA-Seq data (fastq raw read sequences) for French ICGC leiomyosarcoma cancer sequencing project, 78 samples representing 67 donors. Sequencing was performed on Illumina HiSeq. The libraries were then sequenced with a 2 x 75bp paired-end protocol to a minimum mean reads of 50 million.

  Dataset EGAD00001003192

• Single cell RNA sequencing of 33 primary colorectal cancer

  Study EGAS00001003779

• Transcriptome Sequencing PPGL (2)

  RNA-Seq data (n=81) library preparation was performed as previously reported by Calsina et al 2023 using QuantSeq 3' mRNA-Seq Library Prep Kit FWD for Illumina (Lexogen, 015). The prepared libraries were subsequently sequenced on NovaSeq™ system (Illumina). To combine the new CNIO samples (n=81) with the CNIO+TCGA dataset generated in Calsina et al., 2023, RNA data were processed using ComBat-seq as described in that same article.

  Study EGAS50000000013

• ResolveCRPS study - RNA-fragment sequencing from snap-frozen skin biopsies

  Complex Regional Pain Syndrome (CRPS) is a disabling pain disorder with unclear cutaneous molecular mechanisms. To identify gene-expression signatures linked to pain intensity and disease progression, we profiled the local transcriptome of CRPS-affected skin. 42 patients agreed to skin biopsies from the CRPS-affected area, which underwent low-input total RNA-seq. Full experimental and bioinformatics protocols are provided in the associated publication and its supplementary material.

  Study EGAS50000001061