11931 results for "cancer rna-seq"

in 20.01 milliseconds.

• Total RNA sequencing of fibroblasts from unmethylated full mutation carrier 1

  Total RNA sequencing of fibroblasts from an individual with a fragile X syndrome related unmethylated full mutation (UFM1). Libraries were prepared with total RNA with Ribo-Zero ribosomal RNA depletion (illumina), and sequenced paired-end, 75bp on a NextSeq 550 system. This dataset contains three RNA-sequencing replicates from the same cell line.

  Dataset EGAD50000000918

• Total RNA sequencing of fibroblasts from an unmethylated full mutation carrier (UFM2)

  Total RNA sequencing of fibroblasts from an individual with a fragile X syndrome related unmethylated full mutation (UFM2). Libraries were prepared with total RNA with Ribo-Zero ribosomal RNA depletion (illumina), and sequenced paired-end, 75bp on a NextSeq 550 system. This dataset contains three RNA-sequencing replicates from the same cell line.

  Dataset EGAD50000000919

• Total RNA sequencing of fibroblasts from an control individual

  Total RNA sequencing of fibroblasts from an individual with 30-55x GCC repeats in the FMR1 5'UTR. Libraries were prepared with total RNA with Ribo-Zero ribosomal RNA depletion (illumina), and sequenced paired-end, 75bp on a NextSeq 550 system. This dataset contains three RNA-sequencing replicates from the same cell line.

  Dataset EGAD50000000922

• Post Mortem brain data used in paper "Significant and pervasive effects of RNA degradation on Nanopore direct RNA sequencing"

  This dataset contains data used in the paper titled "Significant and pervasive effects of RNA degradation on Nanopore direct RNA sequencing. The data consists of one post mortem sample that was sequenced with direct RNA sequencing form Oxford Nanopore Technologies on a promethION flow cell.

  Dataset EGAD00001009308

• Location and Function of NSun2-Mediated Cytosine-5 Methylation in RNA and its Effect on Translation

  Mutations in the cytosine-5 RNA methyltransferase NSun2 can cause neurodevelopmental disorders and symptoms commonly found in patients with Dubowitz-like syndrome. Some tRNAs are known to be methylated NSun2, however the occurrence of cytosine-5 methylation (m5C) in other RNA biotypes is still under debate. Location in RNA and function of m5C has not been studied yet. This study is aimed at identifying new m5C methylated RNA biotypes, as well as the location at specific structures or sequences and the ultimate biological function. The impact of the loss of NSun2-mediated methylation is also determined by comparing gene expression data with the global cytosine-5 RNA methylome in Dubowitz-like syndrome patients. We also use ribosomal profiling to assess the impact of the loss and rescue of Nsun2-mediated cytosine-5 RNA methylation on translation rates and ribosome occupancy.

  Study phs000645

• ChIP-seq of primary AML patients with t(3;3)/inv(3)

  ChIP-seq was conducted in blasts from patients with t(3;3) AML to assess differences of the GATA2 super-enhancer between the translocated allele and the non-translocated allele. The dataset includes 2x H3K27ac ChIP-seq and 1x MYB ChIP-seq. ChIP samples were processed according to the Illumina TruSeq ChIP Sample Preparation Protocol (Illumina) or Diagenode Library V3 preparation protocol (Diagenode) and either sequenced single-end (1x 50 bp) on the HiSeq 2500 platform (Illumina) or paired-end (2x100 bp) on the Novaseq 6000 platform (Illumina). Briefly, reads were aligned to the human reference genome build hg19 with bowtie for single-end runs and bowtie2 for paired-end runs.

  Dataset EGAD00001006821

• Metagenomic Analysis to Identify Novel Infectious Agents in Systemic Anaplastic Large Cell Lymphoma

  Anaplastic large cell lymphoma (ALCL) is a rare T-cell non-Hodgkin lymphoma (NHL). Risk of systemic ALCL is markedly increased among immunosuppressed people, such as those with human immunodeficiency virus (HIV) infection or solid organ transplant recipients. This increased risk in immunosuppressed populations suggests a viral etiology, given similar elevations for diffuse large B-cell lymphoma (DLBCL), Burkitt lymphoma, and Hodgkin lymphoma (caused by Epstein-Barr virus [EBV]) and other virus-related cancers in immunosuppressed individuals. EBV might be a plausible candidate, but most reported ALCL tumors are EBV-negative. Therefore, we conducted a metagenomic analysis of microbial associations with ALCL to determine whether a known or novel pathogen is associated with the tumor. We obtained archived formal fixed paraffin embedded (FFPE) ALCL tumor tissue from the Iowa cancer registry and an additional case from an immunosuppressed individual infected with human immunodeficiency virus. Controls included 3 diffuse large B-cell lymphomas (DLBCLs) in transplant recipients (shown to be related to Epstein-Barr virus [EBV] by in situ hybridization) and 3 breast cancers (no known viral etiology). RNA was extracted from FFPE specimens, and total RNA libraries were prepared using the KAPA RNA HyperPrep Kit (Roche). Five samples (IA01, IA53, IA57, IA07, and IA17) were sequenced on a NextSeq 500 (Illumina) and the remainder on a NovSeq 6000 (Illumina). Using novel computational approaches, we eliminated human reads and aligned residual non-human reads to known microbial references using GATK-PathSeq or conducted de novo assembly of unassigned reads using virID pipeline. Although EBV was detected in the 3 DLBCL controls, we did not detect EBV or any novel pathogen in ALCL tumors or in the breast cancers. Our study had a modest sample size and only one case arising in HIV-infected individual. Therefore, further studies are required to characterize the metagenome of systemic ALCLs, especially cases arising in immunosuppressed people.

  Study phs002064

• Pediatric Patient-Derived-Xenograft development in MAPPYACTS – international pediatric cancer precision medicine trial in relapsed and refractory tumors

  Pediatric patients with recurrent and refractory cancers are in most need for new treatments. This study developed patient-derived-xenograft (PDX) models within the European MAPPYACTS cancer precision medicine trial (NCT02613962). To date, 131 PDX models were established following heterotopical and/or orthotopical implantation in immunocompromised mice: 76 sarcomas, 25 other solid tumors, 12 central nervous system tumors, 15 acute leukemias, and 3 lymphomas. PDX establishment rate was 43%. Histology, whole exome and RNA sequencing revealed a high concordance with the primary patient’s tumor profile, human leukocyte-antigen characteristics and specific metabolic pathway signatures. A detailed patient molecular characterization, including specific mutations prioritized in the clinical molecular tumor boards are provided. Ninety models were shared with the IMI2 ITCC Paediatric Preclinical Proof-of-concept Platform (IMI2 ITCC-P4) for further exploitation. This new PDX biobank of unique recurrent childhood cancers provides an essential support for basic and translational research and new treatments development in advanced pediatric malignancies.

  Dataset EGAD00001011048

• Small RNA-sequencing and RNA-sequencing data of tuberous sclerosis complex subependymal giant cell astrocytomas

  This data set contains small RNA-sequencing and RNA-sequencing data from subependymal giant cell astrocytomas (SEGA) resected from tuberous sclerosis complex patients. Small RNA-sequencing and RNA-sequencing were performed on the same set of SEGAs (n=19) and periventricular controls (n=8). For full details on library preparation and patients please refer to the paper "The coding and non-coding transcriptional landscape of subependymal giant cell astrocytomas." (PMID: 31834371 DOI: 10.1093/brain/awz370).

  Dataset EGAD00001005932

• Targeted sequencing of genes recurrently mutated in AML

  Background Massively parallel sequencing technology has transformed cancer genomics. It is now feasible, in a clinically relevant time-frame, for a clinically manageable cost, to screen DNA from patient tumours for mutations essentially genome-wide. The challenge for personalised medicine will be to increase the sample size to thousands or tens of thousands of well-characterised cases in order to attain sufficient statistical power to stratify patients accurately across the complexity and genomic heterogeneity expected for most of the common tumour types. Currently, whole genome sequencing on this scale is not feasible, and targeted sequencing of relevant portions of the genome will be required. Pilot data We have developed protocols for large-scale, multiplexed sequencing of 100-200 genes in thousands of samples. Essentially, using robotic technology, genomic DNA from the cancer specimen is processed into sequencing libraries with unique DNA barcodes, thereby allowing sequencing reads to be attributed to the sample they derive from. Currently, these sequencing libraries can be generated in a 96-well format using fully automated protocols, and we are exploring methods to expand this to a 384-well format. The sequencing libraries are pooled and hybridized to custom sets of RNA baits representing the genomic regions of interest. Sequencing of the pulled-down libraries is done in pools of 48-96 samples per lane of an Illumina Hi-Seq. This protocol is already implemented at the Sanger Institute. We have published proof that somatic mutations in novel cancer genes can be identified from exome-wide sequencing. In unpublished pilot data, we have established the feasibility of robotic library production, custom pull-down, and multiplexed sequencing of barcoded libraries for 100 known myeloid cancer genes across 760 myelodysplasia samples. Highlights of the data thus far analysed reveal that the coverage is remarkably even between samples; when 96 samples are run, average coverage per lane of sequencing is ~250, with 90-95% of targeted exons covered by >25 reads; known mutations can be discovered in the data set; and the protocol is amenable to whole genome amplified DNA. The bioinformatic algorithms for identification of substitutions and indels in pull-down data are well-established; we have pilot data proving that copy number changes, LOH and genomic rearrangements in specific regions of interest can also be identified by tiling of baits across the relevant loci. Proposal We propose to apply this methodology to 10000 samples from patients with AML enrolled in clinical trials over the last 10-20 years. Oncogenic point mutations and potentially genomic rearrangements will be identified, and linked to clinical outcome data, with a view to undertaking the following sorts of analyses: ? Identification of co-occurrence, mutual exclusivity and clusters of driver mutations. ? Correlation of prognosis with driver mutations and potentially gene-gene interactions ? Exploration of genomic markers of drug response Ultimately, we would like to be in a position to release the mutation data together with matched clinical outcome data to genuine medical researchers via a controlled access approach, possibly within the COSMIC framework (www.sanger.ac.uk/genetics/CGP/cosmic/). The vision here is to generate a portal whereby a clinician faced with an AML patient and his / her mutational profile can obtain a ?personalised? prediction of outcome, together with a fair assessment of the uncertainty of the estimate. With a sufficient sample size, there would also be the potential to develop decision support algorithms for therapeutic choices based on such data.

  Dataset EGAD00001000606

• MMP-seq tumor samples, UDG treated (FASTQ)

  MMP-seq tumor samples, UDG treated (FASTQ)

  Dataset EGAD00001001104

• Total RNA sequencing of fibroblasts from an individual with fragile X syndrome

  Total RNA sequencing of fibroblasts from an individual with a methylated CGG repeat >200x in the FMR1 5'UTR. Libraries were prepared with total RNA with Ribo-Zero ribosomal RNA depletion (illumina), and sequenced paired-end, 75bp on a NextSeq 550 system. This dataset contains three RNA-sequencing replicates from the same cell line.

  Dataset EGAD50000000920

• Bulk and single-cell RNA-sequencing data from five lines of human iPSC-derived (hiPSC-derived) astrocytes (3 in-house and 2 commercial lines), both alone and in co-culture with neurons, to define the molecular response of astrocytes to misfolded alpha-synuclein

  RNA editing is a post transcriptional mechanism that targets changes in RNA transcripts to modulate innate immune responses. We report the role of astrocyte specific, ADAR1 mediated RNA editing in neuroinflammation in Parkinson’s disease. We generated hiPSC-derived astrocytes, neurons and co-cultures and exposed them to small soluble alpha-synuclein aggregates. Oligomeric alpha-synuclein triggered an inflammatory glial state associated with TLR activation, viral responses, and cytokine secretion. This reactive state resulted in loss of neurosupportive functions, and the induction of neuronal toxicity. Notably, interferon response pathways were activated leading to upregulation, and isoform switching of the RNA deaminase enzyme, ADAR1. ADAR1 mediates A-to-I RNA editing, and increases in RNA editing were observed in inflammatory pathways in cells, as well as in post-mortem human PD brain. Aberrant, or dysregulated, ADAR1 responses and RNA editing may lead to sustained inflammatory reactive states in astrocytes triggered by alpha-synuclein aggregation, and this may drive the neuroinflammatory cascade in Parkinson’s.

  Study EGAS50000000751

• snRNA-seq dataset and atlas from subcortical white matter MS lesions (CA & CI) and controls

  Dataset including FASTQ files for all snRNA-seq samples from subcortical Multiple Sclerosis (MS) lesions and controls (n=15), together with the curated and annotated snRNA-seq atlas.

  Dataset EGAD50000000521

• ChIP-seq for 10 samples

  This dataset contains ChIP-seq data generated from two patient-derived xenograft (PDX) models. For each model, sequencing data are provided from input control (n=1), IgG control (n=2), and FOXF1 immunoprecipitation (n=2). All the 10 samples are in bam file type.

  Dataset EGAD50000001786

• RNA, ATAC, ChIP datasets from Ankylosing Spondylitis patients and Healthy Controls

  This dataset consists of functional genomic data from 20 Ankylosing Spondylitis patients and 35 Healthy Controls taken from CD4+ T cells, CD8+ T cells and CD14 Monocytes. It contains 364 paired end fastq files consisting of 104 total RNA-seq samples and 116 ATAC samples, for ChIP there are 46 H3K4me3 samples, 46 H3K27ac samples and 3 H3K4me1 samples, along with 49 paired input samples. The samples were sequenced on Illumina HiSeq4000, Illumina NextSeq500 and Illumina NovaSeq 6000 platforms.

  Dataset EGAD00001008758

• scRNAseq of colonic organoids derived from biopsies taken from healthy human individuals treated with IL22

  scRNAseq dataset of colonic organoids derived from epithelium from biopsies taken from three healthy human individuals. The organoids have either been grown in standard conditions (control) or treated with IL22 (treated). Includes 6 samples in total, one control from each individual (ctrl1, ctrl2, ctrl3) and one treated from each (treat1, treat2, treat3). The samples have been multiplexed using the antibody hashing technique. The 6 samples have been pooled into the one organoids sample. In order to analyse the raw files, they have to be demultiplexed first. Information necessary for demultiplexing, as well as which files belong to which sample, can be found in the map_file.csv, attached to each sample. Dataset includes raw Fastq files and processed csv count matrices. Fastq files are divided into HTO (hashtag) and RNA (transcriptome) files. HTO has one index (I1) and two read (R1, R2) files and RNA has two index (I1, I2) and two read (R1, R2) files. The fastq files are for the pooled (organoids) sample and need to be demultiplexed. Count matrices contain comma-separated values with cell barcodes as column names and gene names as row names. Since count matrices have been created after the demultiplexing step, there’s one matrix for each of the 6 individual samples. scRNA-seq data from human colon organoids was analysed in the same manner as for the Colitis dataset, apart from the following changes. Data was generated with the Cell Hashing technique, which uses oligo-tagged antibodies against surface proteins to barcode single cells. This allows for samples to be multiplexed together and run in a single experiment. The data was demultiplexed using the HTODemux() function from Seurat (Hao et al., 2021).

  Dataset EGAD00001010168

• Whole genome landscape of adult T-cell leukemia/lymphoma

  Whole-genome sequence (WGS) data of tumor-normal pairs from 139 ATL patients and RNA sequence (RNA-seq) data of tumors from 28 ATL patients.

  Dataset EGAD00001008289

• Medulloblastoma exome sequence analysis

  Medulloblastomas are the most common malignant brain tumors in children. Identifying and understanding the genetic events that drive these tumors is critical for the development of more effective diagnostic, prognostic and therapeutic strategies. Recently, our group and others described distinct molecular subtypes of medulloblastoma based on transcriptional and copy number profiles. Here, we utilized whole exome hybrid capture and Illumina sequencing to identify somatic mutations across the coding regions of 92 primary medulloblastoma/normal pairs. Overall, medulloblastomas exhibit low mutation rates consistent with other pediatric tumors, with a median of 0.35 non-silent mutations per megabase. We identified twelve genes mutated at statistically significant frequencies, including previously known mutated genes in medulloblastoma such as CTNNB1, PTCH1, MLL2, SMARCA4 and TP53. Recurrent somatic mutations were identified in an RNA helicase gene, DDX3X, often concurrent with CTNNB1 mutations, and in the nuclear co-repressor (N-CoR) complex genes GPS2, BCOR, and LDB1, to our knowledge novel findings in medulloblastoma and all cancer. We show that mutant DDX3X potentiates transactivation of a TCF promoter and enhances cell viability in combination with mutant but not wild type beta-catenin. Together, our study reveals the alteration of Wnt, Hedgehog, histone methyltransferase and now N-CoR pathways across medulloblastomas and nominates the RNA helicase DDX3X as a component of pathogenic beta-catenin signaling in medulloblastoma. "Reprinted from 'MEDULLOBLASTOMA EXOME SEQUENCING UNCOVERS SUBTYPE-SPECIFIC SOMATIC MUTATION', with permission from Nature"

  Study phs000504

• A novel orthotopic patient-derived xenograft model of radiation-induced glioma following medulloblastoma

  Radiation-induced glioma (RIG) is a highly aggressive brain cancer arising as a consequence of radiation therapy. We report a case of RIG that arose in the brain stem following treatment for paediatric medulloblastoma, and the development and characterisation of a matched orthotopic patient-derived xenograft (PDX) model (TK-RIG915). Patient and PDX tumours were analysed using DNA methylation profiling, whole genome sequencing (WGS) and RNA sequencing. While initially thought to be a diffuse intrinsic pontine glioma (DIPG) based on disease location, results from methylation profiling and WGS were not consistent with this diagnosis. Furthermore, clustering analyses based on RNA expression suggested the tumours were distinct from primary DIPG. Additional gene expression analysis demonstrated concordance with a published RIG expression profile. Multiple genetic alterations that enhance PI3K/AKT and Ras/Raf/MEK/ERK signalling were discovered in TK-RIG915 including an activating mutation in PIK3CA, upregulation of PDGFRA and AKT2, inactivating mutations in NF1, and a gain-of-function mutation in PTPN11. Additionally, deletion of CDKN2A/B, increased IDH1 expression, and decreased ARID1A expression were observed. Detection of phospho-S6, -4EBP1 and -ERK via immunohistochemistry confirmed PI3K pathway and ERK activation. Here, we report one of the first PDX models for RIG, which recapitulates the patient disease and is molecularly distinct from primary brain stem glioma. Genetic interrogation of this model has enabled the identification of potential therapeutic vulnerabilities in this currently incurable disease.

  Study EGAS00001004709

• MethylScan data of plasma samples

  10ng from each cfDNA sample was used as the input material. For gDNA samples, 1.5-2ug each was first sonicated by Covaris R230 system (Woburn, MA). Next, size-selection with 0.8x-1.5x two-step Ampure XP beads was performed to enrich the 150-200bp fragments. 200ng of the size-selected gDNA was used as input material. The pre-capture library construction was performed with NEB UltraII DNA library prep kit for Illumina (Ipswich, MA) and the adapter was the methylated EM-seq adapter. Before the first PCR amplification, the gDNA samples were subjected to bisulfite conversion by QIAGEN Epitect kit, and cfDNA samples were subjected to enzymatic conversion by NEBNext enzymatic methyl-seq kit if the hybrid capture panel designed for converted DNA was used downstream. Twist panel hybrid capture was performed with their standard protocol (Twist Bioscience, South San Francisco, CA). The concentration of the post-capture library after the second PCR amplification was measured by Qubit 1xdsDNA HS kit (ThermoFisher, Waltham, MA). Their quality was examined by TBE-UREA PAGE and Bioanalyzer before sequencing. Libraries were then sequenced with 150bp paired-end reads on Illumina machines by Genewiz, Inc. (South Plainfield, NJ, USA). This dataset contains MethylScan data of the plasma samples from 248 noncancer individuals and 27 cancer patients (17 liver and 10 GI-tract cancers).

  Dataset EGAD00001015815

• RNA sequencing data for Molecular Characterization of ETMRs

  The dataset contains two samples from one patient. As a representative FFPE tissue sample, ET174 was histologically iden- tified, targeted and microdissected with a puncher for nucleic acid extraction. RNA was extracted using the automated Maxwell system with the Maxwell 16 LEV RNA FFPE Kit (Promega), according to the manufacturer’s instructions. To evaluate FFPE RNA quality, we used the percentage of RNA fragments >200 nt fragment determination value (DV200). Only RNA samples with DV200 > 70% were included for sequencing on a NextSeq 500 (Illumina). Eight lanes have been sequenced resulting in 16 Fastq files (paired end).

  Dataset EGAD00001006209

• Long read mRNA sequencing of human neural retinal samples - Usher syndrome transcript landscape

  Long-read (PacBio) RNA sequencing dataset of three neural retinal samples. Three PacBio libraries were prepared according the 'standard workflow' optimized for sequencing transcripts centered around 2kb. Additionally one Library (input HNR_S2) was prepared according an optimized 'long workflow' to enrich for larger transcripts up to >10kb. To further enhance the capture of full-length transcripts for USH2A and ADGRV1 (USH2C) genes, we also employed a targeted enrichment approach using the Samplix Xdrop System, followed by PacBio long-read sequencing. USH2A and ADGRV1 enrichment was performed by targeting '5- mid and 3' targets of the respective genes. Finally, we also added ONT (Oxford Nanopore technology) long-read mRNA sequencing of three independent neural retina samples. These data were used for the validation of events observed from the Iso-Seq and Samplix data. The ONT datasets contain sequencing data of the Usher-associated genes. Files are raw BAM, and CRAM format files generated by a Sequel II machine. Additionally, the ccs3 BAM format files are included.

  Dataset EGAD50000000720

• Single-nucleus RNA-seq of human fetal liver hematopoiesis

  The fetal liver is the primary haematopoietic organ during early human development, yet the timing and regulatory mechanisms governing blood formation remain incompletely understood. To define the cellular, transcriptional, and epigenetic changes underlying human fetal liver hematopoiesis over development, we generated a high-resolution, time-resolved single-nucleus multiome atlas of human fetal liver spanning 5–18 post-conception weeks (PCW) for CD45+CD235- cells. In total, 308,021 high-quality nuclei from 53 donors were profiled using paired chromatin accessibility and transcriptomic modalities. This study is for the gene expression.

  Study EGAS50000001631

• Single Cell RNAseq at various stages of HiPSCs differentiating toward definitive endoderm and endoderm derived lineages

  When comparing the differentiation capacities of pluripotent stem cell lines that have different genetic backgrounds, batch to batch experimental variablility poses a significant challenge, especially when trying to identify smaller effects. One way to address this issue is to differentiate several different lines in the same culture dish, thereby elimating experimental variation. In addition, it allows researchers to analyze many more lines with less experiments. Parallel single cell RNA-Seq exploits that individual cells are tagged and hence each cell can be reliably assigned to the donor of origin based on the genetic variants it contains. In addition, analyzing the genetic signature of single cells within a differentiating population can reveal differentation stages that are not easily detected in bulk RNAseq data. 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 EGAD00001005741

• RNAseq of circulating monocytes of familial hypercholesterolaemia (FH) patients before and after treatment, and healthy controls.

  RNAseq of circulating monocytes of familial hypercholesterolaemia (FH) patients before and after treatment, and healthy controls. Please cite original paper: Monocyte and macrophage lipid accumulation results in downregulated type-I interferon responses. Willemsen et al. Frontiers in Cardiovascular Medicine (2022) Familial hypercholesterolemic patients (n=10) and healthy subjects (n=9): the study population, design, and further processing of these human study subjects and their samples have been extensively described (Stiekema et al., 2021). Briefly, untreated FH patients who indicated to start lipid-lowering therapy (statin, PCSK9 antibody, and/or ezetimibe) according to their treating physician were included. The healthy controls were age, sex, and body mass index (BMI) matched with the FH patients. After inclusion, FH patients fasted for at least 9 hours before blood samples were drawn for lipid measurements and monocyte isolation. This was repeated after 12 weeks of lipid-lowering therapy. RNA-seq was performed on circulating monocytes. V1 = visit 1. V2 = visit 2.

  Dataset EGAD00001008967

• Alignment BAM files and gene count files of the Illumina Sequencing Data (10 tumor samples)

  Reads were processed with the RNA-seq workflow 1.3.0 developed by the DKFZ Omics IT and Data Management Core Facility (https://github.com/DKFZ-ODCF/RNAseqWorkflow). First, FASTQ reads were aligned via two-pass alignment using STAR 2.5.3a. The STAR index was generated from the 1000 Genomes assembly and GENCODE Version 19 gene models with a sjdbOverhang of 200. Duplicate marking of the resultant main alignment file was done with sambamba 0.6.5. Gene-specific read counting was performed using featureCounts (from Subread 1.5.1) over exon features based on GENCODE Version 19 gene models. Both reads of a paired fragment were used for counting, and the quality threshold was set to 255, indicating that STAR found a unique alignment. Strand-specific counting was also used. For RPKM and TPM calculations, all genes on chromosomes X and Y, the mitochondrial genome, as well as rRNA and tRNA genes were omitted as they are likely to introduce library size estimation biases.

  Dataset EGAD00001008969

• miRNA seq data of 13 cases

  miRNA seq data of 13 cases (MMML)

  Dataset EGAD00001001632

• NanoString nCounter® PanCancer IO 360™on anti-PD1/anti-PD1+CTLA4 in patients with metastatic melanoma

  Patients with advanced melanoma were treated with standard-of-care single agent anti-PD-1 (nivolumab or pembrolizumab) or a combined anti-PD-1+anti-CTLA-4 (ipilimumab) therapy. Patients were retrospectively identified, based on formalin-fixed paraffin-embedded (FFPE) tissue availability. Total RNA was isolated from macro-dissected FFPE tissue sections using the AllPrep DNA/RNA FFPE Kit (Qiagen) or High Pure FFPET RNA Isolation Kit (Roche) according to the manufacturer’s instructions. RNA quantity was assessed on Qubit, and RNA integrity was assessed using the Tapestation system (Agilent). Total RNA samples (60ng/ul, total 200ng) were used as input for the NanoString PanCancer IO360 Panel, run on the nCounter MAX/FLEX prep station and scanner. Samples were hybridised for 20hrs, and each cartridge contained a panel standard.

  Study EGAS00001006977

• scD&D-seq of mobilized PBMC from a healthy individual having IDH2 R140Q CHIP

  Single-cell D&D-seq profiles from a mobilized CHIP (clonal hematopoiesis of indeterminate potential) PBMC sample (2 replicates) co-profiled with IDH2 R140Q GoT-ChA.

  Study EGAS50000001590

• ETMR H3K27Ac ChIPSeq

  H3K27Ac ChIP-seq DNA libraries for 5 ETMR samples were prepared using NEBNext ChIP-seq Illumina Sequencing library preparation kit. ChIP-seqlibraries were sequenced using single-end 50 bp reads on the Illumina HiSeq 2000 platform. ChIP-seq peaks analysed was conducted as published previously(Torchia et al. 2016).

  Dataset EGAD00001004809

• miRNA Profiling of Maternal and Non-Maternal Healthy Adult Blood Plasma Using Small RNA-Sequencing

  We compared several performance characteristics of four miRNA profiling methods: small RNA-sequencing, HTG EdgeSeq, Abcam FirePlex, and NanoString nCounter. We used pools of synthetic miRNAs and extracellular RNA from healthy individuals to assess these characteristics.

  Study phs001892

• TwinsUK_EpiTwin_DNA_Methylome

  MeDIP-seq RPM chromsome BED files for Peripheral Blood from EPITWIN Project (Columns 4-4353 represent samples)

  Dataset EGAD00010000983

• Nasal brushes analysis

  scRNA-seq samples from healthy and asthma donors part 1.

  Study EGAS00001006657

• ATAC-seq in colon normal mucosa

  ATAC-seq

  Dataset EGAD00001007690

• Dataset for NSCLC-RNA

  Rare cancer sequencing data of 45 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008846

• Dataset for liposarcoma-RNA

  Rare cancer sequencing data of 40 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008854

• RNA sequencing of peripheral blood samples from 17 Greenlanders

  The data contain whole deep RNA sequencing of leukocytes from 17 Greenlanders. RNA was purified from peripheral blood with the PAXGene Blood miRNA Kit (Qiagen). The RNA sequencing library was prepared following the instructions of the TruSeq RNA Sample Prep Kit v2 (Illumina). For mRNA isolation and fragmentation 200 ng of total RNA was purified by oligo-dT beads. The qualified libraries were amplified on cBot to generate the cluster on the flowcell (TruSeq PE Cluster Kit V3–cBot–HS, Illumina). The amplified flow cell was sequenced paired-end on the HiSeq 4000 System (TruSeq SBS KIT-HS V3, Illumina).

  Dataset EGAD00001003814

• RNA-sequencing of HCC patients undergoing sorafenib treatment

  RNA-sequencing of hepatocellular carcinomas at various stages of sorafenib treatment

  Study EGAS00001005662

• Mapping genetic effects on cell type-specific chromatin accessibility using single nucleus ATAC-seq

  Gene regulation is highly cell type-specific and understanding the function of non-coding genetic variants associated with complex traits requires molecular phenotyping at cell type resolution. In this study we performed single nucleus ATAC-seq (snATAC-seq) and genotyping in peripheral blood mononuclear cells from 13 individuals. We mapped chromatin accessibility QTLs (caQTLs) in each immune cell type and sub-type in a subset of 10 samples of European genetic ancestry.

  Study EGAS00001006184

• Whole exome sequencing, RNA sequencing and single-cell RNA sequencing of 4 melanoma patients

  We perfomed whole exome sequencing and RNA sequencing of 4 melanoma patients to assess the detailed biological mechanisms of resistance to immune checkpoint inhibitors.

  Study JGAS000285

• Elucidation of male-specific genetic regulation through multi-layered omics analysis

  We performed single-cell RNA-sequencing of peripheral blood mononuclear cells from asthma patients and single-cell multiome (RNA+ATAC) profiling from COVID-19 patients.

  Study JGAS000862

• Reference epigenome OB56_N_PreA_mRNA-Seq data generated from KEP study

  A OB56_N_PreA_mRNA-Seq paired end data for Preadipocytes(fat)

  Dataset EGAD00001003486

• Reference epigenome ADMSC07 h3k4me1 ChIP-Seq data generated from KEP study

  ADMSC07 h3k4me1 ChIP-Seq paired end data

  Dataset EGAD00001007391

• BLUEPRINT: DNaseI-seq for monocytes

  DNaseI-seq for monocytes

  Dataset EGAD00001000674

• bulk mRNA-seq of iGRAN (CD14neg) cells from CMML patients and healthy donors

  bulk mRNA-seq of iGRAN (CD14neg) cells from CMML patients and healthy donors [Publication title] CXCL8 secreted by immature granulocytes inhibits wildtype hematopoiesis in chronic myelomonocytic leukemia

  Study EGAS50000000555

• ATAC-seq, H3K27ac CUT&Tag, and UMI-4C in LCLs derived from constitutional MLH1 epimutation carriers and non-carrier relatives

  ATAC-seq, H3K27ac CUT&Tag, and UMI-4C in lymphoblastoid cell lines derived from constitutional MLH1 epimutation carriers and non-carrier relatives

  Study EGAS50000000499

• H3K27ac ChIP-Seq datasets from human islets in high glucose conditions

  14 ChIP-Seq datasets of H3K27ac in human pancreatic islets from 14 donors, where islets were treated in high (11mM) glucose conditions. Samples IDs HI-129, HI-130, HI-131, HI-132, HI-135, HI-137 and HI-152 were also cultured in low glucose conditions.

  Dataset EGAD00001005204

• H3K27ac ChiIP-seq of monocyte and granulocytes from TB and non-TB samples

  This dataset contains 135 H3K27ac ChiP-seq experiments. Monocytes and granulocytes from TB and non-TB samples were obtained, ChIP-seq was performed, and the reads were aligned to hg19.

  Dataset EGAD00001004206

• PhIP-Seq LLD

  Bacteriophage Immunoprecipitation Sequencing (PhIP-Seq) of LLD participants. Libraries and protocol were developed in the Weizmann Institute of Science. Two different libraries were used, containing microbial and other immunological peptides respectively.

  Study EGAS00001006999