11976 results for "cancer rna-seq"

in 40.78 milliseconds.

• Drug Perturbation of Primary Lymphoma Patient Samples and RNA Sequencing

  This submission contains 3'-end-based shallow-depth RNA sequencing data from 108 patients with chronic lymphocytic leukemia and 8 patients with lymphoma. Each primary patient sample was treated in vitro with DMSO as a control and with up to ten small-molecule drugs (ibrutinib, duvelisib, everolimus, trametinib, nutlin-3a, I-BET762, MK2206, selinexor, compound 26, and a combination of ibrutinib and compound 26). The samples were sequenced after 48 hours. The total data set consists of 1476 RNA sequencing samples from 6 batches (pilot, batch 1, batch 1 replicate, batch 2, batch 3, batch 4).

  Study EGAS50000001500

• bulk RNA sequencing, single cell RNA sequencing and nanopore sequencing of T-ALL patients with TCF7-SI1 fusion

  This dataset contains all sequencing data of the publication "Oncogenic cooperation between the TCF7-SPI1 fusion and NRAS(G12D) requires β-catenin activity to drive T-cell acute lymphoblastic leukemia." This is bulk RNA sequencing of 4 T-ALL patients (X09, XB37, XB41 and XB47) of which X09 has a TCF7-SPI1 fusion, single cell RNA sequencing of these 4 patients toghether with a PDX model of the X09 patient and two patients from another cohort (SJTALL030263 and SJTALL031201) which also have a TCF7-SPI1 fusion, and nanopore sequencing of all patients with the TCF7-SPI1 fusion. Moreover these patient samples with the fusion where treated with PKF 118-310, and bulk RNA sequencing was performed in triplicate to determine the differentially expressed genes.

  Dataset EGAD00001007010

• Whole blood RNA sequencing of individuals from Nepal

  This study utilized blood samples collected in Lalitpur, Nepal as part of the Strategic Typhoid Alliance across Africa and Asia (STRATAA) study. The dataset comprises whole blood RNAseq of 376 febrile individuals from Nepal. Blood was collected in PAXgene tubes and sent to Monash University (Melbourne, Australia) where RNA was extracted using the PAXgene Blood RNA kit before being sent to the Wellcome Sanger Institute (Hinxton, UK) for sequencing. Library prep used NEBNext Ultra II RNA custom kits on an Agilent Bravo WS automation platform with poly(A) pulldown. After PCR, plates were purified using Agencourt AMPure XP SPRI beads and libraries were quantified using Biotium Accuclear Ultra high sensitivity dsDNA Quantitative kits. Pooled libraries were normalised to 2.8 nM. Samples were globin depleted using KAPA RNA HyperPrep with RiboErase. Libraries were then subjected to 2x100bp paired-end sequencing on Illumina NovaSeq. Each library was sequenced to an average of 80 million reads. The STRATAA study was approved by the Nepal Health Research Council (NHRC, ref 283 306/2015) and OxTREC (Oxford Tropical Research Ethics Committee, ref 39-15). All participants provided informed consent for human genetic tests.

  Dataset EGAD00001011131

• MS meninges single nuclei RNA sequencing

  10X 3' (RNA) samples of isolated single nuclei from highly inflamed leptomeninges and adjacent grey matter from 3 MS patients used in the paper.

  Dataset EGAD50000001235

• Bulk RNA-sequencing data from 9 cHL cell lines

  The dataset contains raw data of 27 bulk RNA-sequencing data from 9 cHL cell lines. Paired-end fastq with polyA capture are available for each cell line.

  Dataset EGAD50000001271

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

  10xGenomics single-cell RNA sequencing of glioblastoma patient tumor

  Dataset EGAD00001006206

• Expression profiling of pediatric brain tumors Embryonal Tumor with Multilayered Rosettes (ETMR)

  RNA was prepared using the IlluminaTruSeq RNA sample preparation kit for poly-adenylated mRNA with an average of 97.64 million reads per sample respectively

  Dataset EGAD00001004803

• RNA data for EGAS00001004660

  RNA data for EGAS00001004660, "Aggressive PDACs show hypomethylation of repetitive elements and the execution of an intrinsic IFN program linked to a ductal cell-of-origin"

  Dataset EGAD00001006539

• RNA Sequencing of mCRC xenografts under cetuximab treatment.

  RNA sequencing on cetuximab treated, untreated and release samples of one metastatic colorectal xenograft. 3 cetuximab treated samples, 3 placebo and 3 release - paired fastq.

  Dataset EGAD00001005185

• Single-cell RNA sequencing of 43 BALF samples from CAPA and COVID-19 patients

  Single-cell RNA sequencing of 43 bronchoalveolar lavage fluid (BALF) samples from 15 CAPA and 22 COVID-19 mechanically ventilated patients.

  Dataset EGAD00001011342

• RNA sequencing of 20 intra/extra hepatic bileduct organiods

  This dataset contains RNA sequencing data for 20 intra/extra hepatic bileduct organiods. Data is in BAM format and was processed by STAR.

  Dataset EGAD00001005225

• RNA-sequencing (Illumina HiSeq 4000) of tumor-stage mycosis fungoides

  This dataset contains RNA-sequencing data of tumors from 8 patients with mycosis fungoides. The data was generated using the Illumina HiSeq 4000 platform.

  Dataset EGAD00001003983

• Hospital for Sick Children Infant Glioma RNA Sequencing

  Whole transcriptome (n=4) and targetted RNA sequencing (n=15) .bam files of infantile glioma samples reported on at the Hospital for Sick Children

  Dataset EGAD00001005092

• RNA-Sequencing data of Human Acute Myleloid Leukemia Stem Cells

  RNA-Sequencing of 27 functionally validated LSC and blast fractions from 9 AML patients. Three healthy hematopoietic stem and progenitor cells from age-matched controls.

  Dataset EGAD00001006112

• RNA sequencing data of pretreatment tumor biopsies of patients treated in the OpACIN-neo trial

  The dataset includes RNA sequencing on pre-treatment tumor biopsies of lymph node metastases (n=65)

  Dataset EGAD00001006731

• METABRIC

  The elucidation of breast cancer subgroups and their molecular drivers requires integrated views of the genome and transcriptome from representative numbers of patients. We present an integrated analysis of copy number and gene expression in a discovery and validation set of 997 and 995 primary breast tumours, respectively, with long-term clinical follow-up. Inherited variants (CNVs, SNPs) and acquired somatic copy number aberrations (CNAs) were associated with expression in 40% of genes, although the landscape was dominated by cis and trans-acting CNAs. By delineating expression outlier genes driven in cis by CNAs, we identified putative cancer genes, including deletions in PPP2R2A, MTAP, and MAP2K4. Unsupervised analysis of paired DNA/RNA profiles revealed novel subgroups with distinct clinical outcomes, which reproduced in the validation cohort. These include a high-risk, ER-positive 11q13/14 cis-acting subgroup and a favourable prognosis subgroup devoid of CNAs. Trans-acting aberration 0152hotspots were found to modulate subgroup-specific gene networks, including a TCR deletion-mediated adaptive immune response in the 0152CNA-devoid sub-group and a Basal-specific chromosome 5 deletion-driven mitotic network. Our results provide a novel molecular stratification of the breast cancer population, derived from the impact of somatic copy number aberrations on the transcriptome.

  Study EGAS00000000083

• DIGEST: Dietary Influences on Glucuronidation, a Cross-Sectional Study of Diet and Metabolism

  Plasma samples derived from a study population of control participants (DIGEST: Dietary Influences on Glucuronidation, a Cross-Sectional Study of Diet and Metabolism) were used to profile miRNA circulating in plasma. RNA was isolated from plasma samples using the Qiagen miRNeasy kit. Libraries were prepared using Illumina TruSeq Small RNA Library Prep Kit. Libraries were sequenced on a HiSeq. Data from this sequencing project will be available through dbGaP.

  Study phs003223

• Multi-omics characterization of KMT2A-rearranged infant acute lymphoblastic leukemia

  KMT2A gene rearranged (KMT2A-r) infant acute lymphoblastic leukemia (ALL) is the most refractory subgroup of childhood leukemia, whose molecular heterogeneity remains largely unknown. To better understand the molecular pathogenesis of KMT2A-r infant ALL, we comprehensively analyzed the RNA sequencing, methylation array, whole exome sequencing, single-cell RNA sequencing data of diagnostic samples of KMT2A-r infant ALL. We also performed ChIP sequencing of infant ALL-derived cell lines.

  Study JGAS000385

• Effect of inflammation on human hematopoietic stem cells in a xenograft model

  Transcriptional heterogeneity in cord blood HSCs was investigated by 10X single-cell Multiome (RNA+ATAC). To investigate the effect of inflammatory stress on human HSC, 10X single-cell Multiome profiling of cells from xenografted mice recovered from repeated inflammatory challenge was performed. To investigate transmission of inflammatory stress-related molecular programs from HSC to their progeny, 10X single-cell RNA sequencing was performed on committed progenitor and myeloid cells from the same mice.

  Study EGAS50000001624

• Somatic L1 retrotransposition in normal colorectal epthelium

  Throughout an individual’s lifetime, genomic alterations accumulate in somatic cells. However, the mutational landscape induced by retrotransposition of long interspersed nuclear element-1 (L1), a widespread mobile element in the human genome, is poorly understood in normal cells. Here, we explored the whole-genome sequences of 406 normal colorectal clones, 12 MUTYH-associated adenomatous clones, and 19 matched colorectal cancer tissues. In addition, we analyzed promoter DNA methylation status of retrotransposition-competent L1 (in 139 clones) and read-through RNA expression profiles (in 116 clones) to investigate the epigenetic regulation of L1 activity.

  Dataset EGAD00001010183

• Board considering access to van Hijfte snRNA-seq GBM dataset

  Dac EGAC00001003044

• Human LV H3K27ac ChIP-seq Data Access Commitee

  Dac EGAC00001001169

• Bulk ATAC-Seq on sorted cord blood hematopoietic populations

  Study EGAS00001004742

• 5 scRNA-seq with TCR Enrichment of Tumour-Involved Lymph Nodes, Malignant Seromas and Patient-Derived Xenografts from 18 T-Cell Lymphoma Patients

  This raw data contains 5' scRNA-seq with TCR enrichment data from 18 individual patients analysing cells taken from tumour-involved lymph nodes (LN), malignant seromas and patient-derived xenografts (PDX) including systemic/nodal ALK+ ALCL (n=3 PDX), BIA-ALCL (n=2 seromas), PTCL-NOS (n=5 nodal tumours), nodal T follicular helper lymphoma - angioimmunoblastic type (nTFHL-AI) (n=1), nTFHL, not otherwise specified (nTFHL, NOS, n=1), TLBL (n=5) and 1 case of Sezary Syndrome (SS, cutaneous tumour). Droplet-based 5’ scRNA-seq with TCR enrichment (10x Chromium platform) was performed for all live cells, or the viable CD45+CD3- and CD45+CD3+ fractions following cell sorting by flow cytometry.

  Dataset EGAD00001015703

• 16SV4 ribosomal RNA gene sequencing data

  16SV4 ribosomal RNA gene sequencing data of GI samples and associated mixed community cultures collected from pediatric patients at risk for IBD.

  Dataset EGAD50000000485

• RNA sequencing of pediatric BCP ALL

  RNA sequencing data of 33 B-cell precursor (BCP) acute lymphoblastic leukemia (ALL) cases were constructed on an Illumina nextseq 2000 Sequencing System.

  Dataset EGAD50000001125

• Multi-omics characterisation of immune cells in Long Covid

  We generated 10X Multiomics (paired RNA+ATAC) for Long Covid patients with up to 14 months follow-up.

  Study EGAS50000000142

• Strand-specific RNA Sequencing of initial and recurrent gliomas

  Four RNA-sequencing datasets from two patients with initial low-grade glioma and copy number alteration at IDH1 upon recurrence. Data is provided as bam files.

  Dataset EGAD00001003764

• Poikiloderma syndrome RNAseq

  We will sequence the RNA of lymphoblast samples, transformed with EBV, which have poikiloderma syndrome with mutations in c16orf57. The aim of the experiment is to characterise RNA structural effects in this disease.

  Dataset EGAD00001000324

• RNA sequencing of AML with 3q26 rearrangements

  RNA sequencing of 44 AML cases with diverse 3q26 rearrangements. This dataset is complementary to EGAD00001000726 (which only contains t(3;3)/inv(3)) and to EGAD00001006123.

  Dataset EGAD00001015629

• Characterizing the tumor immune microenvironment of ependymomas using targeted gene expression profiles and RNA-sequencing the pros and cons

  RNA sequencing data of a collection of 6 pediatric ependymoma cases

  Dataset EGAD00001009301

• The Extracellular RNA Quality Control (exRNAQC) study (phase 2)

  mRNA capture sequencing and small RNA sequencing data (FASTQ files) of the exRNAQC study phase 2 (interaction study)

  Dataset EGAD00001009724

• Whole exome and RNA sequencing of 5 samples of patient-derived xenograft (PDX).

  Whole exome and RNA sequencing of 5 samples of patient-derived xenograft (PDX). Available files are raw sequencing fastq files.

  Dataset EGAD00001010102

• Strand-specific RNA sequencing of 16 pairs of primary and relapsed IDH-wt glioblastomas

  This dataset contains strand-specific RNA sequencing data from 16 primary/relapsed sample pairs of IDH-wt glioblastomas

  Dataset EGAD00001004564

• Human serum small non-coding RNA sequencing

  Human small non-coding RNA sequencing of serum from sons of PCOS mothers (n=9) and sons of control mothers (n=9), see publication for details.

  Dataset EGAD00001010165

• RNA sequencing of paediatric glioblastoma in the ICGC PedBrain project

  RNA sequencing of paediatric glioblastoma in the ICGC PedBrain project

  Dataset EGAD00001001944

• ChIP seq samples

  Dataset contains 12 ChIP-Seq samples sequenced on the Illumina NextSeq500 sequencer. 3 samples are control samples (HcAct-Chip 1,HcAct-Chip 2,HcAct-Imput 2) 9 samples are case samples (HcAct2DG-Chip 1,HcAct2DG-Chip 2,HcAct2DG-Imput 1,JIAAct-Chip1,JIAAct-Chip2,JIAAct-Imput2,JIAAct2DG-Chip1,JIAAct2DG-Chip2,JIAAct2DG-Imput2)

  Dataset EGAD50000001188

• GATA1 scD&D-seq integrated with Multiome

  Ex vivo differentiation experiments were performed using human CD34+ hematopoietic stem and progenitor cells along the erythropoietic trajectory at multiple timepoints (differentiation days 0, 5, 8, 18, and 24). Simultaneous profiling of transcriptome, chromatin accessibility, and GATA1 binding were performed by integrating D&D-seq with 10X Multiome.

  Dataset EGAD50000002299

• Metadata and count matrix

  The dataset contains metadata for all cells before scRNA-seq quality control and for cells passing quality control. It also contains a count matrix with Salmon gene counts for all cells passing quality control, and reconstructed B-cell receptor sequences using the computational tool BraCeR. The scRNA-seq data was generated using the Smart-seq2 protocol and sequenced on Illumina NextSeq500.

  Dataset EGAD00001006435

• BLUEPRINT release August 2014, Bisulfite-Seq for macrophage

  Bisulfite-Seq data for 1 macrophage sample(s). 14 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_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001000923

• BLUEPRINT release January 2015, Bisulfite-Seq for erythroblast

  Bisulfite-Seq data for 2 erythroblast sample(s). 35 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_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001001133

• BLUEPRINT release August 2014, Bisulfite-Seq for erythroblast

  Bisulfite-Seq data for 1 erythroblast sample(s). 14 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_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001000909

• Whole genome sequencing of adult glioblastoma nuclei

  Three primary adult glioblastoma specimens were dissociated and nuclei were extracted. A portion of the nuclei was used for single-cell ATAC seq and the remainder were submitted for whole genome sequencing, to provide orthogonal validation of copy number variations in the samples compared to single-cell ATAC seq. Samples were sequenced on the Illumina NovaSeq 6000 in paired-end mode.

  Dataset EGAD00001007651

• Human tumor scMultiome

  We profile 10 high-grade gliomas patient brain tumor samples by single-cell multiome ATAC + gene expression, using the 10X Chromium technology. 3 sets of fastq are provided for each samples: R1 and R2 for gene expression, R1 and R2 for ATAC-seq as well as index1 and index2 for ATAC-seq.

  Dataset EGAD00001008349

• BLUEPRINT release January 2015, Bisulfite-Seq for macrophage

  Bisulfite-Seq data for 5 macrophage sample(s). 72 run(s), 5 experiment(s), 5 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_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001001192

• BLUEPRINT release August 2014, Bisulfite-Seq for inflammatory macrophage

  Bisulfite-Seq data for 3 inflammatory macrophage sample(s). 38 run(s), 3 experiment(s), 3 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_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001000914

• BLUEPRINT release January 2015, Bisulfite-Seq for inflammatory macrophage

  Bisulfite-Seq data for 3 inflammatory macrophage sample(s). 38 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_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001001139

• BLUEPRINT release August 2014, Bisulfite-Seq for Plasma cell

  Bisulfite-Seq data for 1 Plasma cell sample(s). 11 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_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001000927

• BLUEPRINT release January 2015, Bisulfite-Seq for plasma cell

  Bisulfite-Seq data for 1 plasma cell sample(s). 11 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_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001001160

• Rheumatoid Arthritis Finger Stick RNA Sequence Data

  This is a longitudinal study of 355 blood samples collected weekly from 5 patients with Rheumatoid Arthritis with varying disease activity over the course of one to five years. Blood samples were self collected from finger sticks and mailed from home. RNA was extracted, purified and sequenced.

  Study phs003179

• RNA-sequencing of 82 pleural mesothelioma samples

  The dataset contains RNA-sequencing data (bam files) for 82 pleural mesothelioma samples. All the samples were sequenced on an Illumina NovaSeq 600 sequencer in paired-end mode, generating 100 nt length reads, to obtain an average of 60 million clusters for RNA. Demultiplexing was performed using Illumina bcl2fastq2. Fastq quality was assessed using fastQC (v. 0.11.8) (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/) and low-quality reads were discarded. Sequence reads were aligned to Human reference genome (UCSC genome assembly GRCh38/hg38) using STAR (v. 2.7.0b).

  Dataset EGAD50000002131

• RNA sequencing of BCP-LBL and EM B-ALL patients samples

  In order to perform comprehensive transcriptomics and gene fusion analyses of a cohort of BCP-LBL and extramedullary (EM) manifestations of B-ALL patients, we performed RNA sequencing of 16 tissue samples from BCP-LBL and EM B-ALL patients. Because the material was available as FFPE, and had a relative low quality, we used a capture-based approach, where NGS libraries obtained from total RNA were captured in 4-plex, using a whole exome capture panel.

  Dataset EGAD50000002047

• Bulk RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the bulk RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015718

• Single-cell bam files and RNA sequencing of viral RNA stocks

  244 infected single-cell alveolar bam files, 48 empty well bam files, and 52 RNA sequencing of amplicons (4 SARS-CoV-2 variants with 12 batches and 4 viral variants pool samples). 244 alveolar single cells were captured over 12 experimental batches and experimental condition is written in metadata uploaded as "infected_cells_final_revision.csv". on github (https://github.com/twkim-0510/SARS-CoV-2_viral_competition). Each bam file name corresponds to the sample_name column of the metadata.

  Dataset EGAD00001009711

• Single-cell RNA-sequencing of rhabdomyosarcoma tumouroids (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell RNA sequencing of RMS tumouroids data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015708

• Bulk RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the bulk RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015714

• Data Access Commitee - Peripheral Blood Leukocytes 10x Genomics scRNA-seq

  Dac EGAC00001002550

• Peripheral clonal expansion of T cells (scTCR-seq)

  Study EGAS00001003994

• WGBS and oxBS-seq for APL

  Study EGAS00001005610

• Single Cell ATAC-Seq on human cord-blood derived HSPC.

  Study EGAS00001004740

• Single cell characterization of T-cell lymphoma: RNA (2025-07-31)

  Lymphomas are types of blood cancer derived from lymphocytes, and can be classified into two main categories, Hodgkin's lymphomas (HL) and non-Hodgkin lymphomas (NHL). T-cell lymphoma is a type of NHL that develops from T lymphocytes and accounts for 10-15% of total NHL cases. As a rare disease, T-cell lymphoma is functionally, pathologically, and clinically complex and heterogeneous. The 2016 revision of the WHO classification has listed 29 subtypes of mature T/NK-cell neoplasms, among which over 25 are T lymphocyte in origin. These subtypes of T-cell lymphomas have different biological behaviours and clinical prognosis. Clinically, T-cell lymphoma ranges from indolent (slow-growing) to aggressive (fast-growing and spreading) disease. According to the guideline booklet provided by the Lymphoma Research Foundation (https://lymphoma.org/aboutlymphoma/nhl/), indolent T-cell lymphoma subtypes include adult T-cell leukaemia/lymphoma (ATLL), cutaneous T-cell lymphoma (CTCL), and mycosis fungoides (MF), while the aggressive subtypes include anaplastic large cell lymphoma (ALCL), angioimmunoblastic T-cell lymphoma (AITL), peripheral T-cell lymphoma (PTCL), and T lymphoblastic lymphoma (TLBL). PTCL and ALCL represent the most common subtypes of aggressive T-cell lymphoma whereas TLBL is a rare and aggressive subtype mostly diagnosed in children. In this study, we will use single cell RNA sequencing and single cell multiomic methods three aggressive T-cell lymphoma subtypes (ALCL, PTCL and TLBL) and try to gain a deeper insight into the genotypic and phenotypic features of these T-cell lymphomas. . This dataset contains all the data available for this study on 2025-07-31.

  Dataset EGAD00001015669

• Organoid drug profiling identifies methotrexate as a therapy for SCCOHT, a rare pediatric cancer

  Small cell carcinoma of the ovary, hypercalcemic type (SCCOHT) is a rare and lethal tumor in adolescent and young adult patients. Currently, there is no standard-of-care treatment for these patients. Reliable models that represent this disease and can be used for translational research are scarce. To model SCCOHTs, we have established eight patient-derived tumoroid lines from tumor lesions of three patients with SCCOHT. The tumoroids recapitulate genomic and transcriptomic characteristics of the corresponding patient tumors and capture intrapatient tumor heterogeneity. Organoid drug profiling using a library of 153 clinical compounds identified methotrexate as an effective and selective drug against SCCOHTs with a clinically relevant IC50 of 35 nmol/L. RNA sequencing demonstrated that methotrexate induced TP53 pathway activation and apoptosis. These data underscore that organoid technology can support the design of therapeutic strategies for rare cancers.

  Study EGAS00001007911

• Single-cell and spatial transcriptomic profiling of hormone-naïve localised prostate cancer

  Localised prostate cancers (PCa) are heterogeneous and multifocal, with diverse outcomes. Current prognostic methods are epithelium-centric, overlooking the complex cellular landscape within the tumour microenvironment (TME), which remains incompletely characterised. We performed a comprehensive analysis of cancerous and adjacent-benign cores from 24 patients with hormone therapy-naïve localised PCa using single-cell RNA-sequencing. By integrating copy number variation and transcriptional signatures, we classified epithelial cells across a malignant spectrum, revealing widespread molecular perturbation. We found an expansion of Club cell phenotypes, suggestive of Luminal dedifferentiation. We also performed a detailed annotation of stromal phenotypes, focusing on fibroblasts, and identified a novel peri-neural fibroblast population. Spatial transcriptomics elucidated the precise anatomical distribution of CAFs within the PCa TME. This study provides a valuable foundation for advancing our understanding of PCa pathobiology and developing a comprehensive cellular model of the disease.

  Study EGAS00001008332

• A capture methyl-seq protocol with improved efficiency and cost-effectiveness using pre-pooling and enzymatic conversion

  The opportunities for sequencing-based methylome analysis of clinical samples are increasing. To reduce its cost and the amount of genomic DNA required for library preparation, we aimed to establish a capture methyl-seq protocol, which adopts pre-pooling of multiple libraries before hybridization capture and TET2/APOBEC-mediated conversion of unmethylated cytosine to thymine. We compared a publicly available dataset generated by the standard Agilent protocol of SureSelect XT Human Methyl-Seq Kit and our dataset obtained by our modified protocol, EMCap, that adopted sample pre-pooling and enzymatic conversion. We confirmed that the quality of DNA methylation data was comparable between the two datasets. As our protocol, EMCap, is more cost-effective and reduces the amount of input genomic DNA, it would serve as a better choice for clinical methylome sequencing.

  Study JGAS000605

• Transcriptome - Uveal Melanomas

  Total RNA sequencing on 9 uveal melanomas. Libraries were prepared using the TruSeq Stranded Total RNA Library Prep Gold (Illumina, 20020599). Paired-end libraries (2 x 100 bp) were sequenced on a NovaSeq 6000 instrument (Illumina).

  Dataset EGAD50000000763

• Single cell RNA-sequencing of glioblastoma tumours

  Single cell RNA-sequencing of fresh glioblastoma tumor biopsies with 10x Genomics 3' expression (v2 chemistry). Aligned to GRCh38 reference genome using CellRanger.

  Dataset EGAD00001006803

• Sequencing data for oesophageal and related samples - Ganguli et al (RNA)

  Data supporting: "TBC" Ganguli et al (RNA for 394 samples)

  Dataset EGAD00001011190

• Epigenomic atlas of organoid development

  To investigfate the epigenomic basis of fate decisions in the central nerveous system, we recorded a epigenomic timecourse of human brain organoid development using Cut&Tag with paired scRNA-seq. We further performed perturbation experiment inhibiting EED and profiled the response with scRNA-seq and Cut&Tag. Finally, we profiled a sample of the developing human brain using multiome sequencing and Cut&Tag. In our study, we uncover epigenomic switches during brain region diversification and show that epigenetic activation precedes gene expression during neurogenesis in organoids and in primary tissue. Lastly, we show that transcriptional repression by H3K27me3 is required to stabilize neuroectoderm induction from pluripotency.

  Study EGAS50000000155

• DAC for TCR-seq analysis of human intestinal Trm cells

  Dac EGAC00001001219

• scBCR-seq data from human donors

  Dataset EGAD00001005057

• RNA-seq analysis of transcriptome variation with human ESC subclones

  Many studies over the past 10 years, culminating in the recent report of the International Stem Cell Initiative (ISCI, 2011) have shown that hPSC acquire genetic and epigenetic changes during their time in culture. Many of the genetic changes are non-random and recurrent, probably because they provide a selective growth advantage to the undifferentiated cells. Some are shared by embryonal carcinoma cells, the malignant counterparts of ES cells. The origins of these growth advantages are poorly understood, but may come from altered cell cycle dynamics, resistance to apoptosis or altered patterns of differentiation. Less is known about the nature and consequences of epigenetic changes, but it is likely that these similarly affect hPSC behaviour; e.g., enhanced expression of DLK1, an imprinted gene, is associated with altered hPSC growth (Enver et al 2005). Inevitably, these genetic and epigenetic changes will impact on our ability to use hPSC for regenerative medicine, either because malignant transformation of the undifferentiated cells or their differentiated derivatives to be used for transplantation compromises safety, or because they impede the function of those differentiated derivatives, or because they affect the efficiency with which the undifferentiated cells can be expanded and differentiated into desired cell types. Focusing initially upon the existing clinical grade hESC lines, later moving to iPSC, we will Consolidate and extend knowledge of the rate, type and functional impact of the genetic variations that occur during hPSC culture. We will use whole genome and exome sequencing as well as SNP arrays, together with clonal analysis and other cytogenetics techniques. Common changes will be compared with those found in the normal human population, at low frequency in the original cell population or observed during iPSC generation in the HIPSCI project currently based at the WTSI. These studies will provide a better understanding of the range of genetic changes that occur in hPSC beyond the CNVs already identified. In conjunction with cancer genome resources and expertise at WTSI, bioinformatic analyses of these hPSC data will allow us to assess potential impact on hPSC behaviour pertinent to applications in regenerative medicine, notably the likelihood that specific changes arising in undifferentiated PSC cultures may be associated with potential malignant transformation of differentiated progeny 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 EGAD00001004266

• Dataset for WGS and RNA melanoma samples

  This dataset contains WGS and RNA sequencing data for 4 melanoma samples. Sequencing was performed on Illumina Novaseq 6000 and Illumina HiSeq X. The sequencing was always paired.

  Dataset EGAD50000000093

• Transcriptome - Uveal Melanomas MPI

  Total RNA sequencing on 4 uveal melanoma samples. Libraries were prepared using the TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero Gold. Paired-end libraries (2 x 75 bp) were sequenced on HiSeq 4000 instrument (Illumina).

  Dataset EGAD50000001138

• B cell single cell sequencing (RNA + VDJ) - Autoproliferation

  10X 3' (RNA) and 10X 5' (VDJ) samples of B cells (non-proliferating/hi and autoproliferating/Dim) for healthy donor and Multiple sclerosis patients used in the paper.

  Dataset EGAD50000001237

• Hematological toxicity following CAR-T cells injection dataset

  This dataset containes 44 paired of bulk RNA sequencing and 42 parired of single cell RNA sequencing issued from bone marrow aspirations obtained from patients treated with CAR-T (CD3+, CAR T+, CD34+ sorted populations).

  Dataset EGAD50000001142

• bulk RNAseq from metastatic uveal melanoma tumour biopsies

  Tumour biopsies were obtained from uveal melanoma patients (n = 35) pre and 16 days post treatment with tebentafusp. Biopsies, which were either snap frozen or put in RNA later, were analysed by bulk RNA sequencing (50 million reads per sample) using the Illumina NovaSeq system.

  Dac EGAC50000000519

• Integrated Multiomics Uncovers Distinct Macrophage Alterations in Human Metabolic dysfunction-Associated Steatohepatitis Progression

  We report single-nuclei RNA sequencing data from human livers in metabolic dysfunction-associated steatotic liver disease (MASLD) patients.

  Study EGAS50000000768

• Vascularized human retinal organoids

  Single cell RNA sequencing of human retinal organoids that have been vascularized. Assesses the impact of vascularization on cell types and their gene expression.

  Study EGAS50000000828

• Single-nucleus transcriptome sequencing of the human motor cortex

  Single-nucleus RNA-sequencing of the human motor cortex in patients with ALS, C9ORF72-ALS-FTD, ALS-FTD and unaffected controls.

  Study EGAS50000001562

• Single nuclei RNA-sequencing of glioblastoma tumors

  Single nuclei RNA-sequencing of snap frozen glioblastoma tumor tissue with 10x Genomics 3' expression (v2 chemistry). Aligned to GRCh38 reference genome with intron using CellRanger.

  Dataset EGAD00001006802

• RNA sequencing of adult T-cell leukemia/lymphoma

  RNA sequencing of 57 tumor samples of adult T-cell leukemia/lymphoma as well as 3 samples of HTLV-1 carrier and 3 samples of healthy volunteers.

  Dataset EGAD00001001411

• Osteosarcoma capture-based RNA sequencing

  This dataset includes 23 specimens from osteosarcoma patients (primary, relapsed, metastatic). It contains bam files from RNA sequencing using a library in which coding regions of cDNA are captured and short-read, paired-end sequencing.

  Dataset EGAD00001008434

• Single cell RNA-sequencing of glioblastoma stem cell lines

  Single cell RNA-sequencing of glioblastoma stem cell (GSC) lines with 10x Genomics 3' expression (v2 chemistry). Aligned to GRCh38 reference genome using CellRanger.

  Dataset EGAD00001006804

• Clear cell sarcoma dataset

  This deposit consists of DNA and RNA sequencing data from 67 CCS samples. 55 samples had tumor DNA sequencing data. 6 had matched normal sequencing data. 34 samples had tumor RNA sequencing data.

  Dataset EGAD00001008611

• Paired RNA sequencing of 30 samples RRMM (multiple myeloma)

  Paired RNA sequencing of 30 samples RRMM using Illumina TruSeq stranded mRNA kit and either HiSeq2000 or HiSeq X Ten for sequencing.

  Dataset EGAD00001009680

• RNA sequencing upon depletion of RAF kinases vs. MAPK inhibition in KRAS mutant cells

  RNA Sequencing upon shRNA mediated depletion of RAF kinases or treatment with Cobimetinib (GDC-0973, 250nM, 6hrs) or with pan RAFi (AZ-628, 10uM, 6hrs)

  Dataset EGAD00001008384

• RNA data of neuroblastoma patients

  94 sample with multi-omics analysis of ALT-positive neuroblastoma tumors, rna sequencing

  Dataset EGAD00001006587

• Single-cell RNA-sequencing of nivolumab-treated glioblastoma

  Single-cell RNA-sequencing of 8 patients, from primary and relapse tumour (total of 16 samples). Patients were treated with nivolumab prior to relapse surgery.

  Dataset EGAD00001010843

• Bulk RNA-sequencing of nivolumab-treated glioblastoma

  Bulk RNA-sequencing of 30 relapse tumour samples. 20 patients were treated with nivolumab prior to relapse surgery, while 10 patients are control patients.

  Dataset EGAD00001010844

• Identification of Long Non-coding RNA Biomarker of Human Lupus Nephritis Disease Activity - Dataset

  Total RNA paired-end sequencing was performed on whole blood samples from 74 Lupus nephritis (LN) patients and 20 healthy controls using Illumina NovaSeq 6000.

  Dataset EGAD00001010932

• Single-cell RNA sequencing of RCC patients

  Single-cell RNA sequencing was performed on viable frozen tumor dissociated cells from three RCC patients. The raw data is available as fastq files.

  Dataset EGAD00001011045

• BLUEPRINT release August 2014, Bisulfite-Seq for hematopoietic multipotent progenitor cell

  Bisulfite-Seq data for 1 hematopoietic multipotent progenitor cell sample(s). 8 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_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001000917

• Single-cell characterization of human GBM reveals regional differences in tumor-infiltrating leukocyte activation

  Raw sequencing files from scRNA-seq dataset used in Schmassmann et al. 2023. Single-cell characterization of human GBM reveals regional differences in tumor-infiltrating leukocyte activation. Elife 12 (https://elifesciences.org/articles/92678) Dataset content: 14 samples from 5 donors File type: paired-end fastq files Technology: Illumina sequencing Experimentation used: scRNA-seq using the 10X technology

  Dataset EGAD50000000434

• Single-cell CITE-seq and TCR-seq data from AIM⁺ HIV-1-specific T cells

  Single-cell sequencing data from 2 HIV-1 post-intervention controllers and 2 non-controllers reported in Fisher, Garcia, Frattari, Naasz, et al. Longitudinal samples were collected before antiretroviral therapy inititation, during suppressive therapy, and after analytical treatment interruption.

  Dataset EGAD50000002247

• Whole genome DNA sequencing for two long-lived humans.

  Two long-lived human samples were sequenced to a mean 20x coverage genome wide. Sequencing was done using the Illumina hi-seq platform, alignment to GRCh37/hg19 reference genome was done using the BWA alignment tool.

  Study EGAS00001000877

• BLUEPRINT release August 2016, Bisulfite-Seq for Mantle Cell Lymphoma, on genome GRCh38

  Bisulfite-Seq data for 5 Mantle Cell Lymphoma sample(s). 65 run(s), 5 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_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002505

• BLUEPRINT release August 2016, Bisulfite-Seq for thymocyte, on genome GRCh38

  Bisulfite-Seq data for 1 thymocyte sample(s). 14 run(s), 1 experiment(s), 2 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_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002440

• BLUEPRINT release January 2015, Bisulfite-Seq for alternatively activated macrophage

  Bisulfite-Seq data for 4 alternatively activated macrophage sample(s). 64 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_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001001143

• BLUEPRINT release January 2015, Bisulfite-Seq for mature neutrophil

  Bisulfite-Seq data for 6 mature neutrophil sample(s). 79 run(s), 6 experiment(s), 6 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_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001001201

• BLUEPRINT release August 2014, Bisulfite-Seq for mature neutrophil

  Bisulfite-Seq data for 6 mature neutrophil sample(s). 79 run(s), 6 experiment(s), 6 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_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001000935