11925 results for "cancer rna-seq"

in 22.32 milliseconds.

• EM-seq datatset of primary human thymocyte subsets

  FASTQ-files of EM-seq experiments of 6 primary human thymocyte subsets, isolated by flow-cytometry (FACS) from neonatal thymus biopsies. All samples were sorted to be negative for the expression of the lineage surface markers CD11c, CD19, CD56, CD141 and CD303 and additionally had the following surface phenotypes: DN2 (CD4-CD8-CD7+CD1a-CD161-CD38+CD3-TCRab-); DN3 (CD4-CD8-CD7+CD1a+); ISP (CD4+CD8-CD3-TCRab-CD1a+); DPE (CD4+CD8+TCRab-CD69-); DPL (CD4+CD8+TCRab+CD69+); SP4 (CD4+CD8-). Samples were sorted from 1-2 pediatric patients undergoing heart surgery.

  Dataset EGAD50000001600

• mRNA-seq data from ALL patients with NUP214::ABL1 disease

  Dataset contains mRNA-sequencing data (fastq files) from 2 patients with NUP214::ABL1 disease (one T-ALL and one B-ALL patient). Patient samples (peripheral blood or bone marrow) were taken at diagnosis (B-ALL) or relapse (T-ALL). mRNA was extracted from lymphoblasts and underwent paired-end sequencing (75bp) using the Illumina NextSeq platform. Transcriptomic data was used for identification of gene fusions, SNVs and InDels. mRNA-seq data for an additional B-ALL patient with NUP214::ABL1 disease utilised in this study has already been published (EGAS00001006460).

  Dataset EGAD50000001395

• scRNA-seq data of Anti-Her2-CAR T cells treated with immunomodulatory metabolites

  Anti-Her2-CAR T cells produced from T cells derived from healthy human donors were treated with DMSO (control) or either of the immunomodulatory metabolites indole‐3‐carboxaldehyde (ICA), valeric acid (VA) and isovaleric acid (IVA) to assess effects on CAR T cell function. scRNA-seq libraries were generated on a 10X Chromium controller with On-Chip-Multiplexing. The individual samples in a library are distinguished during analysis on the single-cell level via the cell barcode class.

  Dataset EGAD50000002012

• Investigation of chromatin accessibility in clear cell renal cell carcinoma using ATAC-seq

  To identify regions of open and accessible chromatin in clear cell renal cell carcinoma (ccRCC), we performed ATAC-seq on the 786-O, A-498, UM-RC-2 ccRCC cell lines, as well as HK-2 normal renal epithelium cell line, cultured under normoxic (20% O2) and hypoxic (0.05% O2) conditions. Data are provided in raw fastq and processed narrowPeak fomats. Data were processed using the nf-core atacseq pipeline.

  Dataset EGAD50000001885

• BLUEPRINT release August 2016, ChIP-Seq for CD14-positive, CD16-negative classical monocyte, on genome GRCh38

  ChIP-Seq data for 10 CD14-positive, CD16-negative classical monocyte sample(s). 80 run(s), 76 experiment(s), 76 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002484

• BLUEPRINT release August 2016, ChIP-Seq for effector memory CD4-positive, alpha-beta T cell, on genome GRCh38

  ChIP-Seq data for 2 effector memory CD4-positive, alpha-beta T cell sample(s). 8 run(s), 7 experiment(s), 7 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002514

• BLUEPRINT release August 2016, ChIP-Seq for mature conventional dendritic cell - GM-CSF_IL4_T=6_days_R848_T=24hrs, on genome GRCh38

  ChIP-Seq data for 3 mature conventional dendritic cell - GM-CSF_IL4_T=6_days_R848_T=24hrs sample(s). 20 run(s), 19 experiment(s), 19 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002462

• BLUEPRINT release August 2016, ChIP-Seq for effector memory CD8-positive, alpha-beta T cell, terminally differentiated, on genome GRCh38

  ChIP-Seq data for 2 effector memory CD8-positive, alpha-beta T cell, terminally differentiated sample(s). 6 run(s), 6 experiment(s), 6 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002503

• BLUEPRINT release August 2016, ChIP-Seq for effector memory CD8-positive, alpha-beta T cell, on genome GRCh38

  ChIP-Seq data for 3 effector memory CD8-positive, alpha-beta T cell sample(s). 16 run(s), 15 experiment(s), 15 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002283

• BLUEPRINT release August 2016, ChIP-Seq for central memory CD4-positive, alpha-beta T cell, on genome GRCh38

  ChIP-Seq data for 3 central memory CD4-positive, alpha-beta T cell sample(s). 11 run(s), 9 experiment(s), 9 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002439

• BLUEPRINT release August 2015, ChIP-Seq for CD3-positive, CD4-positive, CD8-positive, double positive thymocyte, on genome GRCh38

  ChIP-Seq data for 1 CD3-positive, CD4-positive, CD8-positive, double positive thymocyte sample(s). 3 run(s), 3 experiment(s), 3 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_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001503

• BLUEPRINT release August 2016, ChIP-Seq for CD34-negative, CD41-positive, CD42-positive megakaryocyte cell, on genome GRCh38

  ChIP-Seq data for 3 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 19 run(s), 18 experiment(s), 18 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002362

• BLUEPRINT release August 2016, ChIP-Seq for cytotoxic CD56-dim natural killer cell, on genome GRCh38

  ChIP-Seq data for 6 cytotoxic CD56-dim natural killer cell sample(s). 34 run(s), 34 experiment(s), 34 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002463

• BLUEPRINT release August 2015, ChIP-Seq for mature neutrophil - G-CSF/Dex. Treatment (16-20 hrs), on genome GRCh38

  ChIP-Seq data for 3 mature neutrophil - G-CSF/Dex. Treatment (16-20 hrs) sample(s). 18 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_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001527

• BLUEPRINT release August 2016, ChIP-Seq for mature neutrophil - G-CSF/Dex. Treatment (16-20 hrs), on genome GRCh38

  ChIP-Seq data for 3 mature neutrophil - G-CSF/Dex. Treatment (16-20 hrs) sample(s). 23 run(s), 23 experiment(s), 23 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002470

• BLUEPRINT release August 2016, ChIP-Seq for central memory CD8-positive, alpha-beta T cell, on genome GRCh38

  ChIP-Seq data for 3 central memory CD8-positive, alpha-beta T cell sample(s). 4 run(s), 4 experiment(s), 4 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002450

• BLUEPRINT release August 2016, ChIP-Seq for Germinal Center B-Cell-Like Diffuse Large B-Cell Lymphoma, on genome GRCh38

  ChIP-Seq data for 3 Germinal Center B-Cell-Like Diffuse Large B-Cell Lymphoma sample(s). 10 run(s), 10 experiment(s), 10 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002506

• BLUEPRINT release August 2016, ChIP-Seq for CD3-negative, CD4-positive, CD8-positive, double positive thymocyte, on genome GRCh38

  ChIP-Seq data for 2 CD3-negative, CD4-positive, CD8-positive, double positive thymocyte sample(s). 7 run(s), 5 experiment(s), 5 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002369

• BLUEPRINT release August 2016, ChIP-Seq for mesenchymal stem cell of the bone marrow, on genome GRCh38

  ChIP-Seq data for 2 mesenchymal stem cell of the bone marrow sample(s). 16 run(s), 14 experiment(s), 14 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002381

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

  ChIP-Seq data for 1 effector memory CD8-positive, alpha-beta T cell, terminally differentiated sample(s). 4 run(s), 4 experiment(s), 4 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_chipseq_analysis_ebi_20140811

  Dataset EGAD00001001195

• BLUEPRINT release August 2015, ChIP-Seq for CD4-positive, alpha-beta T cell, on genome GRCh38

  ChIP-Seq data for 7 CD4-positive, alpha-beta T cell sample(s). 39 run(s), 39 experiment(s), 39 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_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001505

• BLUEPRINT release August 2016, ChIP-Seq for CD3-positive, CD4-positive, CD8-positive, double positive thymocyte, on genome GRCh38

  ChIP-Seq data for 3 CD3-positive, CD4-positive, CD8-positive, double positive thymocyte sample(s). 11 run(s), 11 experiment(s), 11 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002445

• BLUEPRINT release August 2015, ChIP-Seq for central memory CD4-positive, alpha-beta T cell, on genome GRCh38

  ChIP-Seq data for 1 central memory CD4-positive, alpha-beta T cell sample(s). 9 run(s), 7 experiment(s), 7 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_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001499

• BLUEPRINT release August 2015, ChIP-Seq for effector memory CD8-positive, alpha-beta T cell, terminally differentiated, on genome GRCh38

  ChIP-Seq data for 1 effector memory CD8-positive, alpha-beta T cell, terminally differentiated sample(s). 4 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_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001577

• BLUEPRINT release August 2015, ChIP-Seq for CD34-negative, CD41-positive, CD42-positive megakaryocyte cell, on genome GRCh38

  ChIP-Seq data for 1 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 7 run(s), 6 experiment(s), 6 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_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001557

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

  ChIP-Seq data for 5 CD8-positive, alpha-beta T cell sample(s). 26 run(s), 26 experiment(s), 26 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_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001513

• BLUEPRINT release August 2015, ChIP-Seq for CD3-negative, CD4-positive, CD8-positive, double positive thymocyte, on genome GRCh38

  ChIP-Seq data for 1 CD3-negative, CD4-positive, CD8-positive, double positive thymocyte 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_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001570

• BLUEPRINT release August 2015, ChIP-Seq for mesenchymal stem cell of the bone marrow, on genome GRCh38

  ChIP-Seq data for 1 mesenchymal stem cell of the bone marrow sample(s). 9 run(s), 7 experiment(s), 7 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_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001578

• scRNA-seq raw data

  scRNA-seq data of B-lineage cells from the cerebrospinal fluid of 21 patients with multiple sclerosis. The data was generated with the Smart-seq2 protocol and sequenced on Illumina NextSeq500.

  Dataset EGAD00001008481

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

  ChIP-Seq data for 2 effector memory CD8-positive, alpha-beta T cell sample(s). 10 run(s), 10 experiment(s), 10 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_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001472

• BLUEPRINT release August 2015, ChIP-Seq for cytotoxic CD56-dim natural killer cell, on genome GRCh38

  ChIP-Seq data for 4 cytotoxic CD56-dim natural killer cell sample(s). 17 run(s), 17 experiment(s), 17 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_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001518

• BLUEPRINT release August 2015, ChIP-Seq for CD14-positive, CD16-negative classical monocyte, on genome GRCh38

  ChIP-Seq data for 9 CD14-positive, CD16-negative classical monocyte sample(s). 56 run(s), 53 experiment(s), 53 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_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001552

• BLUEPRINT release August 2016, ChIP-Seq for CD4-positive, alpha-beta T cell, on genome GRCh38

  ChIP-Seq data for 9 CD4-positive, alpha-beta T cell sample(s). 68 run(s), 63 experiment(s), 63 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002444

• BLUEPRINT release August 2016, ChIP-Seq for CD8-positive, alpha-beta T cell, on genome GRCh38

  ChIP-Seq data for 7 CD8-positive, alpha-beta T cell sample(s). 38 run(s), 38 experiment(s), 38 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002455

• Single Cell Genotypic and Phenotypic Analysis of Measurable Residual Disease in Acute Myeloid Leukemia

  Acute myeloid leukemia (AML) is a group of blood cancers with high mortality. Even though complete remission is often achieved, majority of the AML patients still relapse. Measurable residual disease (MRD), defined as the population of cancer cells which persists following chemotherapy, is responsible for AML relapse. Understanding the biology enabling MRD clones to resist therapy is necessary to guide the development of curative treatments more effectively. Discriminating residual leukemic clones, preleukemic clones, and normal precursors remains a challenge with current MRD tools. We developed a single cell MRD (scMRD) assay by combining flow cytometric enrichment of the targeted precursor/blast population with integrated single cell DNA sequencing (scDNA-seq) and immunophenotyping (Tapestri, Missionbio). The platform utilizes a custom amplicon panel covering 109 amplicons across 31 genes frequently mutated in AML and a panel of 42 oligo-conjugated antibodies against surface makers. We applied our scMRD assay to sequence 30 MRD samples (multiplexed into 6) from 29 AML patients to study the clonal architecture and protein correlation. In addition, 2 MRD samples were sequenced with scDNA+protein sequencing technology without enrichment or multiplexing. Five patients with AML at diagnosis were also sequenced with scDNA+protein sequencing technology without enrichment or multiplexing. In order to establish the sensitivity of our scMRD assay, we spiked AML cells into normal bone marrow cells. We sequenced 12 such spiked samples after multiplexing.

  Study phs003233

• Genetic and epigenetic characterization of adenoid cystic carcinoma

  Translocation events are frequent in cancer and may create chimeric fusions or regulatory rearrangements that drive oncogene overexpression. Although regulatory rearrangements are increasingly recognized in hematopoietic and even solid tumors, the underlying mechanisms remain obscure. Here we identify super-enhancer translocations that drive overexpression of the oncogenic transcription factor MYB as a unifying theme in adenoid cystic carcinoma (ACC). Whole genome sequencing data and chromatin state maps for 13 primary tumors and xenografts reveal distinct chromosomal rearrangements that juxtapose super-enhancer clusters to the MYB locus. Chromosome conformation capture confirms that the translocated enhancers physically interact with the MYB promoter. Remarkably, the MYB product itself binds to the translocated enhancers, thus creating a positive feedback loop that sustains its own expression. MYB also binds a large number of active enhancers that drive opposing regulatory programs in alternate cell lineages in ACC. MYB cooperates with the transcription factor TP63 in the myoepithelial component of the tumors, but promotes a Notch program in the luminal epithelial component. Bromodomain inhibitors, which disrupt enhancer function, slow tumor growth in ACC primagraft models in vivo, but are ineffective against high grade tumors that harbor activating mutations in the Notch pathway. Thus, our study identifies super-enhancer translocations as a unifying feature of ACC, and provides insight into the mechanism by which sustained MYB overexpression drives alternate cell fates in this disease.Processed ChIP-seq data is available on GEO under accession number GSE76465.

  Study EGAS00001001457

• scRNA-seq of glioblastoma cells alone or after co-culture with cerebral organoid cells

  Dataset EGAD00001005315

• ChIPseq data

  ChIPseq data for H3K4me1 and H3K9me3 in HT29; H3K4me1, H3K27me3, H3K9me3, H3K36me3 in LoVo.

  Dataset EGAD00001003258

• Dataset of PPB

  Whole exome sequencing and miRNA-seq data of PPB.

  Dataset EGAD00001000822

• ChIPseq data

  ChIPseq data for CLL patients

  Dataset EGAD00001008665

• Dataset for WGS and RNA samples of acute myeloid leukemia with MNX1 expression

  This dataset contains 10 samples of WGS, ATAC, 4C and RNAseq samples of patients with acute myeloid leukemia. The sequencing was performed on Illumina HiSeq 4000, 2000 and HiSeq X using Illumina TruSeq Nano DNA and Agilent Strand Specific RNA Kits. The sequencing was always paired.

  Dataset EGAD50000001098

• Single-cell RNA-sequencing of CSF cells and PBMCs from individuals with neurological disorders

  We undertook single-cell RNA sequencing to establish gene expression and lymphocyte receptor sequences of CSF and peripheral blood leukocytes derived from patients with a variety of inflammatory, infectious and non-inflammatory neurological disorders. The aim of the study was the investigation of functional changes of the cells involved in neuroinflammatory responses.

  Dataset EGAD50000001173

• Transcriptional and epigenetic profiling of bone marrow blood progenitors across age

  Bone marrow from donors without known malignancy was isolated and CD34-enriched, FACS-purified to further enrich for CD34+CD38- primitive cells, and then profiled by single-cell 10X genomics chromium Multiome (RNA+ATAC).

  Study EGAS50000001623

• Single-cell transcriptome sequencing

  Raw reads from single-cell RNA-sequencing of peripheral blood of five TET2 mutation carriers as well as three non-carrier family members. Single-cells were captured into 10x barcoded gel beads and RNA-sequencing library preparation was done using Chromium Single Cell 3' v2 chemistry (10x Genomics, Pleasanton, CA, USA). Sequencing was performed as recommended with 98bp length of read 2 using HiSeq4000 sequencer.

  Dataset EGAD00001004778

• Single-cell RNA sequencing generated from 11 glioma patient samples

  This dataset includes paired-end fastq files from 6 IDH-mutant, 5 IDH-wild-type glioma patient samples of unmatched initial and recurrent timepoints profiled using single-cell RNA sequencing.

  Dataset EGAD00001007772

• Transcript read counts derived from RNA sequencing data collected for NABUCCO cohort 1 (NCT03387761)

  Data from NABUCCO cohort 1 (NCT03387761). This dataset includes the Transcript read counts derived from the RNA sequencing data. The samples are pre-treatment (n=18) and post-treatment (n=18), and not all samples are paired. The data processing pipeline can be found on the Methods section from the Nature Medicine paper (https://doi.org/10.1038/s41591-020-1085-z)

  Dataset EGAD00001006854

• Transcriptome profiling of human lung fibroblasts in COPD

  Primary lung fibroblast were isolated from well-matched control donors (no COPD, n=3) and patients with COPD (GOLD stage I-IV, n=8). Total RNA of cultured human lung fibroblast were isolated at passage 3 and rRNA was depleted. 75 bp single-end reads were generated from RNA libraries on Illumina NextSeq 500.

  Dataset EGAD00001009405

• FASTQ files of the cell-free RNA from the maternal blood

  cell-free RNA from the maternal plasma obtained at round the 12, 20, 28 and 36 week gestational age from the cases of preeclampsia combined with fetal growth restriction (n=39) and their matched controls (n=156). All samples are from the Pregnancy Outcome Prediction (POP) study.

  Dataset EGAD00001015416

• RNA expression profiling of melanoma patient-derived xenograft

  Patient-derived xenografts (n=96) were derived from metastatic melanoma patients. RNA expression profiling will be preformed to study 1. HLA-typing and 2. the effect of the tumour microenvironment on tumour growth 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 EGAD00001002230

• 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