12214 results for "cancer rna-seq"

in 21.33 milliseconds.

• PhIP-seq of Japanese patients with SLE

  Bacteriophage Immunoprecipitation Sequencing (PhIP-Seq) datasets of three eHHV-6B-positive SLE patients (three technical replicates), six eHHV-6B-negative SLE patients (three technical replicates), and a negative control lacking sera or plasma (12 technical replicates; Illumina NextSeq) and sequencing data of HHV-6 peptide phage library (two technical replicates; Illumina NextSeq).

  Study EGAS00001007955

• Single-cell multi-omics and mtDNA genotyping of human peripheral blood cells

  This dataset comprises two mtscATAC-seq libraries (customized 10X ATAC-seq) generated from donor M80 and donor H05, and one DOGMA-seq library (customized 10X multiome) generated from donor H05, all derived from primary human peripheral blood mononuclear cells. Patient M80 is an 80-year-old male with mitochondrial encephalomyopathy, lactic acidosis, and stroke-like episodes (MELAS), while donor H05 is a healthy 5-year-old pediatric donor. The raw FASTQ files have been provided.

  Dataset EGAD50000001489

• BLUEPRINT September 2016, ChIP-Seq for class switched memory B cell from venous blood, on Genome GRCh38

  ChIP-Seq data for 1 sample(s) for class switched memory B cell from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001002951

• Blueprint: A human variation panel of genetic influences on epigenomes and transcriptomes in three immune cell types, (ChIP-Seq for mature neutrophil, on genome GRCh37)

  ChIP-Seq data for 182 mature neutrophil sample(s). 2847 run(s), 366 experiment(s), 355 analysis(s) on human genome GRCh37. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/blueprint_Epivar/protocols/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002670

• TARGET-seq+ single-cell transcriptome sequencing

  Single-cell whole transcriptome sequencing data for bone marrow samples from 9 cases with clonal hematopoiesis and 4 control samples. The TARGET-seq+ protocol was used to generate plate-based 3' transcriptome data. For details on cell sorting and the TARGET-seq+ protocol see the methods section of the manuscript. One FASTQ file is provided per cell. Cells are named with their plate and well IDs and the subject ID. Empty wells (no-cell controls) are named "blank". Corresponding genotyping files use the same naming without the "_transcriptome" suffix.

  Dataset EGAD00001011175

• 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

• CCA ChIP-seq data (63 CCA, 8 normal, 19 cell-line)

  Fastq files for H3K27ac ChIP-seq (with matched input-DNA control) for 63 CCAs, 8 normal bile duct tissues, 16 CCA cell-lines (including replicates), and 3 normal cholangiocyte cell-lines (including replicates). Library prep was performed with the NEBNext ChIP-seq library preparation kit. Each library (including matching input DNA) was sequenced to an average depth of 20 to 30 million raw reads on Illumina HiSeq4000 sequencer, with paired-end sequencing (except for 3 normal bile tissues done with single-end sequencing).

  Dataset EGAD00001012103

• 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 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

• 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

• Circulating Tumor DNA in Intermediate Risk Rhabdomyosarcoma

  In this study, we evaluated circulating tumor DNA (ctDNA) as a biomarker in the serum of 124 patients with newly diagnosed intermediate risk rhabdomyosarcoma (IR RMS) from the Children's Oncology Group (COG) biorepository. In addition to pre-treatment serum, we also analyzed matched tumor tissue and germline in a subset of patients. We profiled samples using ultra-low passage whole genome sequencing (ULP-WGS) and a new custom hybrid-capture sequencing assay, Rhabdo-Seq, to detect copy number alterations, rearrangements, and single nucleotide variants. We found that patients with detectable ctDNA at diagnosis had significantly worse outcomes than those without detectable levels of ctDNA. Our study demonstrates that baseline ctDNA detection is feasible and prognostic in IR RMS. The ULP-WGS and targeted next-generation sequencing (Rhabdo-Seq and TranSS-Seq) data are available in this study.  

  Study phs002866

• Maternal Plasma RNA Sequencing for Genomewide Transcriptomic Profiling and Identification of Pregnancy-Associated Transcripts

  Maternal Plasma RNA Sequencing for Genomewide Transcriptomic Profiling and Identification of Pregnancy-Associated Transcripts

  Dataset EGAD00001001609

• HipSci - Healthy Normals - RNA Sequencing - January 2016

  HipSci - Healthy Normals - RNA Sequencing - January 2016

  Dataset EGAD00001001933

• Single-nucleus RNA-sequencing of meningiomas

  Single-nucleus RNA-sequencing of meningiomas for integrative molecular classification

  Dataset EGAD00001007677

• RNA sequencing of Ewing and CIC-DUX4 sarcoma tumoroid models

  Tumoroid models from Ewing sarcoma and CIC-DUX4 sarcoma models were generated from patient tumor biopsies. Tumoroids were established in 3D matrigel domes and then propagated on a matrige layer. RNA sequencing was performed with established tumoroid models.

  Study EGAS50000000380

• DNA sequencing of sgRNAs in CRISPR-Cas9 screening and RNA sequencing of SF3B4-overexpressing liver organoids

  The dataset contains 18 samples. It includs 12 paired whole genome sequencing, and 2 matched short read and long read RNA sequencing of liver organoids, 2 paired RIP RNA sequencing samples. All the experiments were performed on Illumina platform with raw reads stored in fastq format or bam format.

  Dataset EGAD50000001625

• RNA fastq files and mutation annotation files

  This dataset contains the results of both RNA sequencing and DNA sequencing. For RNA sequencing, it includes data from 12 samples derived from 9 patients, provided as raw sequencing files in FASTQ format. For DNA sequencing, it contains mutation information obtained from targeted panel DNA sequencing, including data from 35 individuals in the mutation annotation file (MAF) format.

  Dataset EGAD50000001768

• RNA sequencing of BCP-LBL patients samples

  In order to perform comprehensive transcriptomics and gene fusion analyses of a cohort of BCP-LBL patients, we performed RNA sequencing of 49 tissue samples from BCP-LBL 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 EGAD50000000419

• RNA sequencing data of pediatric TCF3::PBX1 acute lymphoblastic leukemia (set 1)

  The dataset includes RNA sequencing FASTQ files from a diagnostic tumor sample of one TCF3::PBX1 ALL patient (ALLT-335). NEBNext Ultra Directional RNA Library Prep Kit (New England Biolabs) was used in library preparation, and Globin-Zero Gold rRNA Removal Kit (Illumina) was utilized for rRNA removal. The diagnostic tumor sample was sequenced using Illumina Novaseq 6000, and the target sequencing depth was 21 Gb.

  Dataset EGAD50000002577

• RNA sequencing data of pediatric BCR::ABL1 acute lymphoblastic leukemia (set 1)

  The dataset includes RNA sequencing FASTQ files from a diagnostic tumor sample of one BCR::ABL1 ALL patient (ALLT-343). NEBNext Ultra Directional RNA Library Prep Kit (New England Biolabs) was used in library preparation, and Globin-Zero Gold rRNA Removal Kit (Illumina) was utilized for rRNA removal. The diagnostic tumor sample was sequenced using Illumina Novaseq 6000, and the target sequencing depth was 21 Gb.

  Dataset EGAD50000002579

• RNA sequencing data of pediatric BCR::ABL1 acute lymphoblastic leukemia (set 2)

  The dataset includes RNA sequencing FASTQ files from a diagnostic tumor sample of one BCR::ABL1 ALL patient (ALLT-399). TruSeq Stranded Total RNA Library Prep (Illumina) kit was used in library preparation, and Novogene's internal method was utilized in rRNA removal. The diagnostic tumor sample was sequenced using Illumina Novaseq X Plus, and the target sequencing depth was 21 Gb.

  Dataset EGAD50000002580

• RNA sequencing data of pediatric KMT2A-rearranged acute lymphoblastic leukemia (set 2)

  The dataset includes RNA sequencing FASTQ files from a diagnostic tumor sample of one KMT2A-r ALL patient (ALLT-355). NEBNext Ultra Directional RNA Library Prep Kit (New England Biolabs) was used in library preparation, and Ribo-Zero Magnetic Kit (Illumina) was utilized in rRNA removal. The diagnostic tumor sample was sequenced using Illumina Novaseq 6000, and the target sequencing depth was 21 Gb.

  Dataset EGAD50000002583

• RNA sequencing data of pediatric ETV6::RUNX1 acute lymphoblastic leukemia (set 3)

  The dataset includes RNA sequencing FASTQ files from a diagnostic tumor sample of one ETV6::RUNX1 ALL patient (ALLT-397). TruSeq Stranded Total RNA Library Prep (Illumina) kit was used in library preparation, and Novogene's internal method was utilized in rRNA removal. The diagnostic tumor sample was sequenced using Illumina Novaseq X Plus, and the target sequencing depth was 21 Gb.

  Dataset EGAD50000002587

• RNA sequencing data of pediatric ETV6::RUNX1 acute lymphoblastic leukemia (set 1)

  The dataset includes RNA sequencing FASTQ files from a relapse sample of one ETV6::RUNX1 ALL patient (ALLT-341). NEBNext Ultra Directional RNA Library Prep Kit (New England Biolabs) was used in library preparation, and Globin-Zero Gold rRNA Removal Kit (Illumina) was utilized for rRNA removal. The relapse sample was sequenced using Illumina Novaseq 6000, and the target sequencing depth was 21 Gb.

  Dataset EGAD50000002588

• RNA sequencing data of pediatric hyperdiploid acute lymphoblastic leukemia (set 2)

  The dataset includes RNA sequencing FASTQ files from a diagnostic tumor sample of one hyperdiploid ALL patient (ALLT-356). NEBNext Ultra Directional RNA Library Prep Kit (New England Biolabs) was used in library preparation, and Ribo-Zero Magnetic Kit (Illumina) was utilized in rRNA removal. The diagnostic tumor sample was sequenced using Illumina Novaseq 6000, and the target sequencing depth was 21 Gb.

  Dataset EGAD50000002593

• RNA sequencing data of pediatric hyperdiploid acute lymphoblastic leukemia (set 4)

  The dataset includes RNA sequencing FASTQ files from diagnostic tumor samples of three hyperdiploid ALL patients (ALLT-382, ALLT-395, ALLK-111). TruSeq Stranded Total RNA Library Prep (Illumina) kit was used in library preparation, and Novogene's internal method was utilized in rRNA removal. The diagnostic tumor samples were sequenced using Illumina Novaseq 6000, and the target sequencing depth was 21 Gb per sample.

  Dataset EGAD50000002596

• RNA sequencing data of pediatric B-other acute lymphoblastic leukemia (set 2)

  The dataset includes RNA sequencing FASTQ files from diagnostic tumor samples of three B-other ALL patients (ALLT-357, ALLT-361, ALLK-108). NEBNext Ultra Directional RNA Library Prep Kit (New England Biolabs) was used in library preparation, and Ribo-Zero Magnetic Kit (Illumina) was utilized in rRNA removal. The diagnostic tumor samples were sequenced using Illumina Novaseq 6000, and the target sequencing depth was 21 Gb.

  Dataset EGAD50000002597

• RNA sequencing data of pediatric B-other acute lymphoblastic leukemia (set 5)

  The dataset includes RNA sequencing FASTQ files from a diagnostic tumor sample of one B-other ALL patient (ALLT-396). TruSeq Stranded Total RNA Library Prep (Illumina) kit was used in library preparation, and Novogene's internal method was utilized in rRNA removal. The diagnostic tumor sample was sequenced using Illumina Novaseq X Plus, and the target sequencing depth was 21 Gb.

  Dataset EGAD50000002601

• Genomic and Transcriptomic Landscape of Fibrolamellar Hepatocellular Carcinoma

  Fibrolamellar hepatocellular carcinoma (FL-HCC) is a rare liver tumor primarily affecting adolescents and young adults. Little is known of the molecular pathogenesis. To characterize the disease we performed RNA sequencing and whole genome sequencing on FL-HCC tumors and adjacent normal tissue. The results demonstrate few consistent differences on the chromosomal level and many hundreds of alterations in the expression of RNA transcripts.

  Study phs000709

• Study of wound response like states in glioblastoma

  In order to investigate wound reponse-like states in glioblastoma, we carried out experiments on primary tissue as well as organoids. Single cell RNA sequencing was performed on core and periphery of three human glioblastoma. Bulk RNA sequencing was performed on glioblastoma-derived organoids subject to treatment for 72h with plasma, hypoxia, or both, and analyzed at 0, 24, 72, and 144h.

  Study EGAS50000001442

• Genomic and Transcriptomic sequencing of neuroblastoma cell lines

  Genomic and Transcriptomic sequencing of neuroblastoma HSR and ecDNA cell lines. Data represents five 96-well plates that were processed with G&T sequencing, resulting in genomic and transcriptomic data from the same single cells. Dataset contains 95 bam files containing the DNA sequencing data and 95 bam files containing the RNA sequencing data of CHP212 cells, 380 bam files (190 DNA and 190 RNA) for TR14 cells, 188 bam files (94 DNA and 94 RNA) for Kelly cells and 192 bam files (96 DNA and 96 RNA) for IMR5/75 cells.

  Dataset EGAD50000000729

• Pathogenic Neurofibromatosis type 1 (NF1) RNA splicing resolved by targeted RNAseq

  Neurofibromatosis type 1 (NF1) is caused by loss-of-function variants in the NF1 gene. Approximately 10% of these variants affect RNA splicing and are either missed by conventional DNA diagnostics or are misinterpreted by in silico splicing predictions. Therefore, a targeted RNAseq-based approach was designed to detect pathogenic RNA splicing and associated pathogenic DNA variants. an in-house developed tool (QURNAS) was used to calculate the enrichment score (ERS) for each splicing event. RNA enrichment of NF1 and SPRED1 was done using SPET (NUGEN - NF1 only) and using SureSelect (Agilent - NF1 and SPRED1).

  Dataset EGAD00001007978

• Genomic Analysis of Diffuse Large B Cell Lymphoma

  Tumors from 383 newly diagnosed diffuse large B cell lymphoma were included in this study. Tumor DNA was extracted from formalin-fixed, paraffin embedded (FFPE) tissue sections, germline DNA was extracted from blood, and whole exome sequencing (WES) of all samples (n=340 tumor normal pairs) was performed using the Agilent SureSelect XT AllExon v5 + UTR kit and sequencing was carried out on an Illumina NovaSeq, 100 x 2 paired end reads. Tumor RNA (n=321) was extracted from formalin-fixed, paraffin embedded (FFPE) tissue sections and RNA sequencing was performed using the Illumina TruSeq RNA Exome Kit (Illumina) for library preparation, sequencing platform HiSeq 4000, 100 x 2 paired end reads.

  Study phs003634

• Single-cell RNA-seq of peripheral blood mononuclear cells in classic Hodgkin lymphoma

  Classic Hodgkin lymphoma (cHL) is a largely MHC class I-negative tumor with recurrent 9p24.1/ PD-L1/ PD-L2 copy gains and the highest reported response rates to PD-1 blockade. We utilized scRNA sequencing to characterize the peripheral immune response to PD-1 blockade and more broadly define non-CD8+ dependent mechanisms of immune evasion in cHL. Peripheral blood mononuclear cells were obtained from 20 patients with relapsed/refractory (R/R) cHL treated with PD-1 blockade (nivolumab) on the CheckMate 205 clinical trial (paired samples from cycle 1 day 1 [C1D1] and cycle 4 day 1 [C4D1]), 11 patients with newly diagnosed, previously untreated cHL and 13 healthy donors.

  Study EGAS00001007569

• Raw RNA sequencing of hepatoblastoma PDX cell line HB-303-LEF

  This dataset contains raw RNA sequencing data for hepatoblastoma PDX cell line HB-303-LEF

  Dataset EGAD50000001358

• HipSci - Healthy Normals - RNA Sequencing - July 2017

  HipSci - Healthy Normals - RNA Sequencing - July 2017

  Dataset EGAD00001003529

• RNA-sequencing of blastic plasmacytoid dendritic cell neoplasm

  RNA sequencing of frozen tumor biopsies from patients with blastic plasmacytoid dendritic cell neoplasm. 4 samples. Illumina HiSeq 4000.

  Dataset EGAD00001005031

• single cell RNA sequencing for healthy controls and patients having NFATc1 deficiency

  single cell RNA sequencing for 4 healthy controls and 2 patients having NFATc1 deficiency

  Dataset EGAD00001011044

• Spontaneously differentiatiated iPSCs to EBs

  SUM-seq data (single-cell chromatin accessibility and gene expression) for spontaneously differentiatiated iPSCs. This data is the representative data in the Nature Protocols publication.

  Study EGAS50000001094

• Cell subtypes subsets from subcortical MS snRNA-seq atlas

  Curated subsetting of cell subtypes derived from the 9 principal cell types within our subcortical Multiple Sclerosis (MS) lesions snRNA-seq atlas.

  Dataset EGAD50000000522

• scRNA-seq and scTCR-seq from 7 MF patients

  Dataset containing scRNA and scTCR sequencing of 7 patients with cutaneous T cell lymphoma. Sequencing was performed on Illumina NextSeq 550, HiSeq 4000 and NovaSeq 6000. The sequencing was always paired.

  Dataset EGAD50000000332

• BLUEPRINT September 2016, ATAC-seq Mantle Cell Lymphoma from venous blood, on Genome GRCh38

  ATAC-seq data for 5 sample(s) Mantle Cell Lymphoma from venous blood, on Genome GRCh38. 5 run(s), 5 experiment(s), 5 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002918

• BLUEPRINT September 2016, ATAC-seq Chronic Lymphocytic Leukemia from venous blood, on Genome GRCh38

  ATAC-seq data for 106 sample(s) Chronic Lymphocytic Leukemia from venous blood, on Genome GRCh38. 111 run(s), 109 experiment(s), 109 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002916

• siRNA knockdown of Allelic Imbalance target TFs followed by mRNA-seq

  siRNA knockdown of 43 Allelic Imbalance target TFs followed by mRNA-seq done in triplicates in three (GP5D, LoVo, COLO320DM) different cell colorectal adenocarcinoma cell lines.

  Dataset EGAD00001004098

• NKI-AvL OpACIN DNA-seq of stage III melanoma patients

  The dataset “NKI-AvL OpACIN DNA-seq of stage III melanoma patients" includes 2 x 18 normal and 2 x 18 tumor FASTQ files from paired-end whole exome sequencing on Illumina HiSeq2500 for 18 stage III melanoma patients.

  Dataset EGAD00001004217

• BLUEPRINT September 2016, ATAC-seq for tonsil, on Genome GRCh38

  ATAC-seq data for 7 sample(s) from tonsil, on Genome GRCh38. 7 run(s), 7 experiment(s), 7 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002708

• ctDNA mutation analysis using the SiMSen-seq approach

  Mutation analysis in plasma samples with low ctDNA levels using a molecular barcoding technology, i.e. the single target approach SiMSen-seq (Simple, multiplexed, PCR-based barcoding of DNA for sensitive mutation detection using sequencing).

  Dataset EGAD00001006104

• Transcription factor binding in human monocyte differentiation

  This dataset consists of ChIP-seq data data from human monocytes, monocyte-derived dendritic cells as well as monocyte-derived cells that were subjected to mRNA transfection for PU.1, IRF4, and EGR2. In total, it the data set includes 18 samples.

  Dataset EGAD00001006602

• COVID-19 Postmortem Lung snRNA-seq

  A deeper understanding of the pathological mechanisms of SARS-CoV-2 infection is required to combat COVID-19. Through this dataset, we analyze postmortem lung cells from patients that are infected/uninfected with SARS-CoV-2 with snRNA-seq.

  Dataset EGAD00001006584

• Human tumor scATAC-seq

  We profiled 4 high-grade gliomas patient brain tumor samples by single-cell ATAC-seq using the 10X Chromium 3' technology. The raw fastq and index files are provided.

  Dataset EGAD00001008347