10117 results for "cancer rna-seq"

in 65.74 milliseconds.

• BLUEPRINT release August 2016, RNA-Seq for endothelial cell of umbilical vein (proliferating), on genome GRCh38

  RNA-Seq data for 2 endothelial cell of umbilical vein (proliferating) sample(s). 2 run(s), 2 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_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002341

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

  RNA-Seq data for 10 CD4-positive, alpha-beta T cell sample(s). 10 run(s), 10 experiment(s), 10 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002348

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

  RNA-Seq data for 2 central memory CD4-positive, alpha-beta T cell sample(s). 2 run(s), 2 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_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002349

• BLUEPRINT release August 2016, RNA-Seq for erythroblast, on genome GRCh38

  RNA-Seq data for 8 erythroblast sample(s). 30 run(s), 8 experiment(s), 8 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_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002358

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

  RNA-Seq data for 1 CD3-negative, CD4-positive, CD8-positive, double positive thymocyte sample(s). 1 run(s), 1 experiment(s), 1 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_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002422

• BLUEPRINT release August 2016, RNA-Seq for endothelial cell of umbilical vein (resting), on genome GRCh38

  RNA-Seq data for 2 endothelial cell of umbilical vein (resting) sample(s). 2 run(s), 2 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_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002436

• BLUEPRINT release August 2016, RNA-Seq for CD38-negative naive B cell, on genome GRCh38

  RNA-Seq data for 3 CD38-negative naive B cell sample(s). 3 run(s), 3 experiment(s), 3 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_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002438

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

  RNA-Seq data for 2 effector memory CD8-positive, alpha-beta T cell sample(s). 2 run(s), 2 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_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002456

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

  RNA-Seq data for 3 mature neutrophil - G-CSF/Dex. Treatment (16-20 hrs) sample(s). 3 run(s), 3 experiment(s), 3 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_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002467

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

  RNA-Seq data for 2 effector memory CD4-positive, alpha-beta T cell sample(s). 2 run(s), 2 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_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002469

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

  RNA-Seq data for 3 mature conventional dendritic cell - GM-CSF_IL4_T=6_days_R848_T=24hrs sample(s). 3 run(s), 3 experiment(s), 3 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_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002471

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

  RNA-Seq data for 2 mesenchymal stem cell of the bone marrow sample(s). 2 run(s), 2 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_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002473

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

  RNA-Seq data for 1 central memory CD8-positive, alpha-beta T cell sample(s). 1 run(s), 1 experiment(s), 1 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_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002482

• BLUEPRINT release August 2016, RNA-Seq for immature conventional dendritic cell - GM-CSF_IL4_T=6_days, on genome GRCh38

  RNA-Seq data for 3 immature conventional dendritic cell - GM-CSF_IL4_T=6_days sample(s). 3 run(s), 3 experiment(s), 3 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_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002526

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

  RNA-Seq data for 1 CD3-positive, CD4-positive, CD8-positive, double positive thymocyte sample(s). 1 run(s), 1 experiment(s), 1 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_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002525

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

  RNA-Seq data for 205 mature neutrophil sample(s). 205 run(s), 205 experiment(s), 205 analysis(s) on human genome GRCh37. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/blueprint_Epivar/protocols/README_rnaseq_analysis_sanger_20160816

  Dataset EGAD00001002675

• Comparison of 3 protocols for deriving pancreatic progenitors from hPSCs (RNA-seq)

  This dataset contains 26 mapped bam files. The samples were generated with 3 different protocols for deriving pancreatic progenitors from hPSC. Three parallel differentiations were performed, all done in a hPSC NKX6.1-GFP reporter line. For each protocol there are three cellular populations: total (presort), GFP+ and GFP- . In summary: 3 differentiations x 3 protocols x 3 cellular populations. We prepared Smart-Seq2 RNA-seq libraries for the 27 samples, 1 sample failed library preparation and is not therefore included in this dataset.

  Dataset EGAD00001004823

• Ither NB in Organoids RNA-Seq dataset - Exploring high-throughput drug sensitivity testing in neuroblastoma cell lines and patient-derived tumor organoids in the era of precision medicine

  Ither NB in Organoids RNA-Seq dataset - We aimed to launch an online repository integrating genomics and transcriptomics with high-throughput drug screening (HTS) of nineteen commonly used neuroblastoma cell lines and fourteen generated neuroblastoma patient-derived organoids (NBL-PDOs) to improve identification of molecularly matched therapies and support clinical uptake.

  Dataset EGAD00001010283

• A first-in-human clinical study of an allogenic iPSC-derived corneal endothelial cell substitute transplantation for bullous keratopathy

  iPSC-derived corneal endothelial cell substitutes recover pathological corneal edema. No adverse reactions are observed after one year follow-up. Gene mutations may appear despite whole genome sequencing of the master cell bank. This study contains the RNA-seq data.

  Study EGAS50000000673

• Organoid Profiling Identifies Common Responders to Chemotherapy in Pancreatic Cancer

  We generated a collection of patient-derived pancreatic normal and cancer organoids. We performed whole genome sequencing, targeted exome sequencing, and RNA sequencing on organoids as well as matched tumor and normal tissue if available. This dataset is a valuable resource for pancreas cancer researchers, and those looking to compare primary tissue to organoid culture. In our linked publication, we show that pancreatic cancer organoids recapitulate the mutational spectrum of pancreatic cancer. Furthermore, RNA sequencing of organoids demonstrates the presence of both transcriptional subtypes of pancreas cancer.

  Study phs001611

• RNA sequencing of osteoarthritis patients in subchondral bone

  This dataset contains RNA-seq (Illumina Hiseq 4000) from macroscopically preserved and lesioned OA subchondral bone of patients that underwent joint replacement surgery due to OA (N=48).

  Dataset EGAD00001006197

• Richter Syndrome RNA-seq dataset

  Raw FASTQ files for 77 RS + DLBCL + CLL samples. RNA-sequencing with single-end 50 nt reads.

  Dataset EGAD00001007922

• The paired FF/FFPE colon set, RNA-Seq

  Dataset EGAD00001000831

• RNA-seq of CML074 Tumor tissue; Timpepoint 1

  Dataset EGAD00001001259

• RNA-seq of CML074 Tumor tissue; Timpepoint 2

  Dataset EGAD00001001260

• Aggregated count table

  RNA-seq count matrix for 296 bulk pre-treatment tumors from IMblaze370

  Dataset EGAD00001008552

• Combined Tumor and Immune Signals From Genomes or Transcriptomes Predict Outcomes of Checkpoint Inhibition in Melanoma

  Cancer immunotherapy with checkpoint blockade (CPB) leads to improved outcomes in melanoma and other tumor types, but a majority of patients do not respond. High tumor mutation burden (TMB) and high levels of tumor-infiltrating T cells have been associated with response to immunotherapy, and integrative models using DNA and RNA have improved predictions of clinical benefit. However, identification of immune and tumor-intrinsic features in models using DNA or RNA alone have not been comprehensively explored in melanoma. In this study, we sequenced DNA and RNA of tumors from 67 melanoma patients receiving CPB, and aggregated this cohort with previously published data, yielding whole exome sequencing (WES) data for 189 patients and bulk RNA sequencing data for 178 patients. Using these datasets, we derived genomic and transcriptomic factors that predict overall survival (OS) and response to immunotherapy. Using whole exome DNA data alone, we calculated T cell burden (TCB) and B cell burden (BCB) based on rearranged TCR/Ig DNA sequences, and found that melanoma patients with high TMB and either high TCB or high BCB survived longer and had higher response rates, as compared to patients with low TMB and either low TCB or low BCB. Next, using bulk RNA-Seq data, differential expression analysis identified 83 genes which are associated with high or low OS. By combining pairs of immune-expressed genes with tumor-expressed genes, we identified three gene pairs which are associated with response and survival (Bonferroni P<0.05). All three gene pair models were validated in an independent cohort (n=180) (Bonferroni P<0.05). The best performing gene pair model included the lymphocyte-expressed MAP4K1 (Gene ID: 11184) and the transcription factor TBX3 (Gene ID: 6926) which is overexpressed in poorly differentiated melanomas. We concluded that RNA-based (MAP4K1 and TBX3) or DNA-based (TCB and TMB) models combining with immune and tumor measures improve predictions of outcome after checkpoint blockade in melanoma.

  Study phs002683

• RNA-seq of hepatocellular carcinoma xenografts established from needle biopsies

  RNA-sequencing of human hepatocellular carcinoma biopsies (n=14), 44 HCC xenografts derived from 11 HCC biopsies and 3 lymphoma xenografts derived from 3 HCC biopsies. RNA-sequencing was performed using the TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero Gold (lllumina). SR126 sequencing was performed on an Illumina HiSeq 2500 using v4 SBS chemistry according to the manufacturer’s guidelines.

  Dataset EGAD00001004541

• Sequence Data for DEEP Release August 2016

  DEEP (German Epigenome Project) sequence data of following samples (Sequencing Types: Chip-Seq, WGBS-Seq, RNA-Seq, sncRNA-Seq, NOMe-Se, DNase-Seq): 41_Hf01_LiHe_Ct, 41_Hf02_LiHe_Ct, 41_Hf03_LiHe_Ct, 01_HepG2_LiHG_Ct1, 01_HepG2_LiHG_Ct2, 01_HepaRG_LiHR_D31, 01_HepaRG_LiHR_D32, 01_HepaRG_LiHR_D33, 43_Hm01_BlMo_Ct, 43_Hm03_BlMo_Ct, 43_Hm05_BlMo_Ct, 43_Hm03_BlMa_Ct, 43_Hm05_BlMa_Ct, 43_Hm03_BlMa_TO, 43_Hm05_BlMa_TO, 43_Hm03_BlMa_TE, 43_Hm05_BlMa_TE, 51_Hf01_BlCM_Ct, 51_Hf03_BlCM_Ct, 51_Hf04_BlCM_Ct, 51_Hf02_BlCM_Ct, 51_Hf05_BlCM_Ct, 51_Hf06_BlCM_Ct, 51_Hf06_BlCM_T1, 51_Hf06_BlCM_T2, 51_Hf03_BlEM_Ct, 51_Hf04_BlEM_Ct, 51_Hf02_BlEM_Ct, 51_Hf05_BlEM_Ct, 51_Hf06_BlEM_Ct, 51_Hf06_BlEM_T1, 51_Hf06_BlEM_T2, 51_Hf03_BlTN_Ct, 51_Hf04_BlTN_Ct, 51_Hf02_BlTN_Ct, 51_Hf05_BlTN_Ct, 51_Hf06_BlTN_Ct, 51_Hf06_BlTN_T1, 51_Hf06_BlTN_T2, 51_Hf07_BmTM4_Ct, 51_Hf08_BlTM4_Ct, 51_Hf08_BmTM4_SP1, 51_Hf08_BmTM4_SP2, 51_Hf05_BlTA_Ct, 44_Mm01_WEAd_C2, 44_Mm03_WEAd_C2, 44_Mm02_WEAd_C2, 44_Mm07_WEAd_C2, 44_Mm04_WEAd_C1, 44_Mm05_WEAd_C1

  Dataset EGAD00001002527

• Single-cell RNA sequencing of SarBC-01 treated with Dexamethasone vs DMSO, with or without Matrigel.

  This dataset contains raw FASTQ files from single cell RNA sequencing of SarBC-01 cells treated with Dexamethasone vs DMSO, with or without Matrigel, processed with MULTI-seq. Cells from 4 different culture conditions (+Mat/Dex, +Mat/DMSO, -Mat/Dex, -Mat/DMSO) were harvested, processed for multiplexing using the MULTI-seq protocol and loaded in a Chromium Single Cell 3ʹ GEM Library and Gel Bead Kit v3 (10x Genomics). Gene expression (cDNA) and MULTI-seq libraries were prepared according to the manufacturers’ protocol of Chromium Next GEM Single Cell 3’ reagents Kits v3.1 (Dual Index). Finally, cDNA and MULTI-seq libraries were analyzed using an Agilent Bioanalyzer (DNA High Sensitivity kit) and sequenced on a NovaSeq6000 (S2 flow cell) platform. MULTISEQ BARCODES: TTAGCCAG => Matrigel/DMSO CCACAATG => Matrigel/Dexamethasone GCACACGC => noMatrigel/DMSO AGAGAGAG => noMatrigel/Dexamethasone

  Dataset EGAD00001011155

• Intratumoral plasma cells predict outcomes to PD-L1 blockade in non-small cell lung cancer

  Inhibitors of the programmed cell death-1 (PD-1/PD-L1) signaling axis are approved to treat non-small cell lung cancer (NSCLC) patients, based on their significant overall survival (OS) benefit. Using transcriptomic analysis of 891 NSCLC tumors from patients treated with either the PD-L1 inhibitor atezolizumab or chemotherapy from two large randomized clinical trials, we found a significant B cell association with extended OS with PD-L1 blockade, independent of CD8+ T cell signals. We then derived gene signatures corresponding to the dominant B cell subsets present in NSCLC from single-cell RNA-seq data. Importantly, we found increased plasma cell signatures to be predictive of OS in patients treated with atezolizumab, but not chemotherapy. B cells were also associated with the presence of tertiary lymphoid structures and organized lymphoid aggregates. Our results suggest an important contribution of B and plasma cells to PD-L1 blockade efficacy in NSCLC.

  Study EGAS00001005013

• DSRCT RNA genomic sequencing

  Purpose: To further understand the molecular pathogenesis of desmoplastic small round cell tumor (DSRCT), a rare but often fatal malignancy occurring primarily in young males, we used next-generation RNA sequencing to investigate the gene expression profiles intrinsic to this disease.Experimental Design: RNA from DSRCT tumor samples were obtained from the Cooperative Human Tissue Network biorepository. RNA sequencing was completed using the Illumina HiSeq 2000 system. Presence of the EWSR1-WT1 fusion was verified using both RNA-sequencing and PCR. Validation studies, including WT1 ChIP-seq, RNA sequencing, and EWS-WT1 knockdown experiments, were performed on an established DSRCT cell line, JN-DSRCT-1. Protein expression of clinically relevant genes determined by RNA sequencing was confirmed using immunohistochemistry. A panel of immune signature genes was also evaluated to identify possible immune therapeutic targets. Results: We analyzed the RNA from 14 tumor samples, of which two were confirmed negative for the diagnostic EWSR1-WT1 translocation. Principal component analysis of the sequencing data indicated that fusion-negative and fusion-positive tumors are transcriptionally distinct entities. Overlapping the significant ChIP-seq peaks with genes found to be highly expressed in the RNA sequencing data revealed that IGF2 and FGFR4 were both highly expressed, and targets of the EWS-WT1 fusion gene. This finding has potential clinical relevance for targeted therapeutic intervention. In addition, we identified the immune checkpoints CD200 and CD276 as potentially targetable genes whose expression is independent of the EWS-WT1 fusion gene in vitro.Conclusions: Despite the transcriptional complexity of this disease, we were able to identify IGF2, FGFR4, CD200, and CD276 as potential therapeutic targets for patients suffering from DSRCT.

  Study EGAS00001002770

• RNA_Seq_in_Patients_with_Primordial_Dwarfism

  Transcriptome studies in patients with rare genetic diseases can potentially aid in theinterpretation of likely causal genetic variation through identification of altered transcriptabundance and/or structure. RNA-Seq is the most sensitive assay for both investigatingtranscript structure and abundanceThe primary aim of this pilot project is to investigate to what degree integrating exome-Seqand RNA-Seq data on the same individual can accelerate the identification of causal allelesfor rare genetic diseases. There are two main strands to this: (i) identifying which variantsdiscovered in exome-seq appear to be having a functional impact on transcripts, and (ii)identifying transcript outliers, especially among known causal genes, that may not necessarilyhave a causal variant identified from exome sequencing. The latter may identify the presenceof causal variants that lie far from coding regions (e.g. the formation of cryptic splice sitesdeep within introns, or loss of long range regulatory elements), which can be confirmed withfurther targeted genetic assays. Just over 50% of all disease-causing variants recorded in theHuman Gene Mutation Database (HGMD) affect transcript structure and abundance (e.g.nonsense SNVs, essential splice site SNVs, frameshifting indels, CNVs).This pilot project will study RNA from lymphoblastoid cell-lines from 12 patients withprimordial dwarfism syndromes, for 10 of these samples we have previously generate exomedata as part of our collaboration with the group of Prof Andrew Jackson. The two remainingsamples are positive controls where the causal mutation is known, and is known to affecttranscript structure and/or abundance.Primordial dwarfism is a prime candidate for these RNA-seq studies because all knowncausal mutations to date have key roles in DNA replication and thus, unsurprisingly, theproducts of the causal genes are typically ubiquitously expressed.Each RNA will be sequenced, with two technical replicates (independent RT-PCR and libraries) persample, and each replicate run in 1/2 of a HiSeq lane using 100bp paired reads. Samples preparation was as follows :The cells were grown to confluency, then pellets frozen at -80. RNA samples were prepared using the Qiagen RNeasy kit, then nanodropped and analyzed using the bioanalyzer to determine concentration and purity.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/

  Study EGAS00001000283

• bulkRNA seq from fibroblasts stimmulated with bead or CD8 T cell supernatant

  CD8 T cells (5 Samples treated, 5 samples control) form the same donors (5 donors, paired design) was subject to RNA-seq (Illumina stranded mRNA) processing. Single end fastq-files are supplied.

  Dataset EGAD00001010004

• RNA sequencing of 31 pancreatic cancer organiods

  RNA sequencing of 31 pancreatic cancer organiods

  Dataset EGAD00001005217

• Molecular_risk_stratification_in_patients_with_T1_colorectal_cancer_WES

  The introduction of bowel cancer screening has led to a significant increase in the proportion of patients being diagnosed with asymptomatic, early-stage colorectal cancer (CRC). Although the majority of these patients are successfully treated with surgery alone, a small proportion of patients have ‘born-to-be-bad’ aggressive lesions with early dissemination leading to distant metastases. Current standard of care histological assessment is unable to distinguish between these aggressive versus non-aggressive early lesions which is essential to provide appropriate clinical management decisions. This study aims to carry out molecular and histological profiling of approximately 300 T1 CRCs in order to develop a molecular stratifier based on the risk of relapse in early-invasive CRC. This novel T1 cohort will represent the world’s largest molecularly characterised T1 cohort of samples, with digital pathology assessment alongside whole exome sequencing, copy number variation analysis and 3’ RNA-seq. This data will be used to generate a robust panel of molecular and/or histological markers applicable to formalin-fixed paraffin embedded (FFPE) archival tissue which discriminates between T1 lesions based on risk of relapse, which will ultimately be used to inform clinical management of CRC at the earliest stages of the disease.

  Study EGAS00001005734

• Exploring the cell-free total RNA transcriptome in diffuse large B-cell lymphoma and primary mediastinal B-cell lymphoma patients as biomarker source in blood plasma liquid biopsies

  The goal of this study was to investigate cell-free RNA (cfRNA) biomarkers in DLBCL and PMBCL patients. Blood plasma samples (n=168) and matched diagnostic formalin-fixed paraffin-embedded (FFPE) tissue samples (n=69) of DLBCL patients, PMBCL patients and healthy controls were collected between 2016-2021. Plasma samples were collected at diagnosis, at interim evaluation, after treatment, and in case of refractory or relapsed disease. RNA was extracted from 200 µl plasma using the miRNeasy serum/plasma kit and from FFPE tissue using the miRNeasy FFPE kit. RNA was subsequently sequenced on a NovaSeq 6000 instrument using the SMARTer Stranded Total RNA-seq pico v3 library preparation kit.

  Study EGAS00001007585

• Mutational Landscape of Plasmablastic Lymphoma

  Plasmablastic lymphoma (PBL) represents a clinically heterogeneous subtype of aggressive B-cell non-Hodgkin lymphoma. Although targeted sequencing studies and a single center whole exome sequencing (WES) study in HIV+ patients recently revealed several genes, associated with PBL pathogenesis, the global mutational landscape and transcriptional profile of PBL remain elusive. To inform on disease-associated mutational drivers, mutational patterns and perturbed pathways in HIV+ and HIV- PBL we performed WES and RNA-sequencing (RNA-seq) of 34 PBL tumors.

  Study EGAS00001004906

• RNA-seq FASTQ files from newborn screening dried blood spot samples

  Paired-end RNA-seq FASTQ files from 21 newborn screening dried blood spot (DBS) samples. These DBS samples were obtained from extremely low gestional age newborns, where 10 of them were affected by a fetal inflammatory response (FIR) before birth, and 11 were unaffected. Total RNA was sequenced using an Illumina NextSeq-500 instrument. The sample preparation protocol included the depletion of rRNA and globin mRNA using the Globin Zero Gold rRNA Removal Kit from Illumina. Libraries were prepared using the NebNext Ultra TM II Directionl RNA LIbrary Prep Kit (New England Biolabs). Each sample was sequenced in 4 lanes, leading to 8 FASTQ files per sample and a total of 21x8=168 FASTQ files. There is an additional number of 8 FASTQ files corresponding to sample BS13, which was downsampled to 1/4 of its original depth (see BS13_README file for details).

  Dataset EGAD00001004991

• Cardiac Translatomes of 80 Human Samples

  Dataset consists of fastq files of Ribo-seq, polyA-RNA and total RNA sequencing of 80 samples (65 DCM cases and 15 controls)

  Dataset EGAD00001004394

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

  SMARTer Stranded Total RNA-Seq method of human platelet-rich plasma, platelet-free plasma, urine, conditioned medium, and extracellular vesicles (EVs) from these biofluids. Including a titration experiment with spikes.

  Dataset EGAD00001006150

• RNA-seq samples

  Raw FASTQ files obtained by RNA sequencing of tumor samples from patients (age 12-29) with newly diagnosed, recurrent intermediate or high-grade sarcoma.

  Dataset EGAD00001008393

• Single cell sequencing data for chronic myeloid leukemia cell lines

  This dataset contains RNA sequencing information for Chronic Myeloid Leukemia. In total 2 single-end RNA-seq tumor cell line samples are present.

  Dataset EGAD00001009736

• RNA-seq in endometrial healthy and tumor tissues

  RNA has been extracted by Rneasy mini kit from around 30mg of flash frozen tissue derived from 3 healthy and 3 tumor endometrial tissues of post-menopausal patients. Raw paired-end fastq.gz files are provided.

  Dataset EGAD50000000200

• ICGC prostate cancer RNA sequencing

  ICGC prostate cancer RNA sequencing

  Dataset EGAD00001000305

• Deciphering Intratumoral Molecular Heterogeneity in Clear Cell Renal Cell Carcinoma with a Radiogenomics Platform

  We used 200 ccRCC samples from 51 tumors to simultaneously isolate DNA, RNA, and protein according to established protocol. RNA quality was assessed using an Agilent Bioanalyzer, and total RNA with RIN>7 was used for further RNA sequencing. 184 ccRCC samples from 49 tumors passing initial quality control underwent RNA sequencing at Admera Health Inc. (Genohub Inc., Austin, TX). RNA sequencing libraries were prepared using the Illumina TruSeq Stranded mRNA high throughput (HT) sample preparation kit following the manufacturers’ protocol. Pair-end RNA Seq data was deposited in this cohort.

  Dataset EGAD00001005356

• RNA-seq on neuroblastoma PDX model COG-N-519 treated with control miR-1283 and test miR-99b-5p mimics

  Study EGAS00001005368

• 20200417_PNET_methylation_paper

  Illumina platform RNA-seq data from 47 Pancreatic neuroendocrine tumour samples

  Dataset EGAD00001006063

• IMpower133 subtype assignments

  This dataset contains subtype assignments for 271 tumor samples profiled by RNA-seq.

  Dataset EGAD00001006926

• IL1R1+ cancer-associated fibroblasts drive tumor development and immunosuppression in colorectal cancer

  180502: RNA-Sequencing data of cocultured matched CRC patient (P4) derived normal fibroblasts (NFs), cancer associated fibroblasts (CAFs) and tumor spheroids. 200503_coculture: RNA-Sequencing data of cocultured CRC patient derived normal fibroblasts (NFs) or cancer associated fibroblasts (CAFs) (P16, P19, P22, P32, P41, P42) and tumor spheroids (HT29). 200503_il1b: RNA-Sequencing data of IL-1β stimulated fibroblasts (NFs and CAFs) Cole: scRNA-sequencing of matched CRC tumour samples and normal tissue counterparts derived from 3 patients. 220501: RNA-Sequencing of FACS sorted IL1R1 high and IL1R1 low CT5.3 CAFs

  Dataset EGAD00001010322

• The Immune Microenvironment Shapes Transcriptional and Genetic Heterogeneity in Chronic Lymphocytic Leukemia

  Tumor microenvironment (TME) and somatic mutations drive progression of chronic lymphocytic leukemia (CLL). Integrated bulk and single-cell RNA sequencing (RNA-seq) of paired peripheral blood (PB) and lymph node (LN) samples from patients with treatment-naïve CLL showed upregulation of oncogenic processes in LN attributable to a minor population of activated tumor cells. A 10-gene tumor signature derived from this population was positively correlated with activated CD4+ T cells and M2 macrophages in the TME. Whole exome sequencing of paired PB and LN samples showed subclonal expansion in LN in some patients. In remaining patients with clonal stability between PB and LN, a T-cell inflamed TME was detected by RNA-seq. These data connect the TME with molecular events in the evolution of CLL.This cohort was later augmented with whole exome sequencing for 15 additional CLL samples. In an integrative analysis of genetic, transcriptomic, and epigenetic data, including the data from this study, we built new models to improve CLL patient prognostication.

  Study phs002297

• The RNA, ChIP and whole exome sequencing analysis of human colorectal cancer organoids and normal colon organoids treated with (+)-JQ1

  To reveal the mechanism of anti-tumor effect of (+)-JQ1, we performed RNA, ChIP and whole exome sequencing using human colorectal cancer and normal colon organoids.

  Study JGAS000378

• Genomic, epigenomic and transcriptomic profiling of GCTB

  This dataset contains primary raw data of whole-genome sequencing, whole-genome bisulfite sequencing, ATAC-seq, ChIP-seq (ChIP-mentation) of histone variants and modifications, as well as RNA-seq of giant cell tumor of bone tissue and primary cell line samples.

  Dataset EGAD00001005109

• RCC Infiltrated Macrophages and Monocytes

  Tumor infiltrated Macrophages and Monocytes were sorted on Aria II (Becton Dickinson) into TRIzol LS and flash frozen. RNA was extracted with chloroform. Isopropanol and linear acrylamide were added, and the RNA was precipitated with 75% ethanol. Total RNA (0.649–1 ng) with RNA integrity numbers 6.8 to 10 underwent amplification using the SMART-Seq v4. Ultra Low Input RNA Kit (Clontech; cat. #63488). Amplified cDNA (15 ng) was used to prepare libraries with the KAPA Hyper Prep Kit (Kapa Biosystems, KK8504) using 8 cycles of PCR.

  Dataset EGAD00001009393

• RNA-seq

  Our cohort represents infants with ALL in whom KMT2Ar was not detected by FISH or by standard cytogenetics. Whole-transcriptome sequencing (WTS) libraries were prepared using the NEBNext Ultra II RNA Directional library kit for samples with at least 100ng RNA (n=19), the Clontech double stranded cDNA conversion kit plus the Nextera XT library protocol for samples with less than 100ng RNA (n=4), or ribodepletion using NEBNext rRNA Depletion Kit v2 (Human/Mouse/Rat) for Total RNA (n=1). Libraries were paired-end sequenced using the Illumina HiSeq 2500.

  Dataset EGAD50000000595

• Exome-seq, RNA-Seq, SNP array profiling of gastric tumor samples and cell lines.

  Gastric cancer is the second leading cause of worldwide cancer mortality, yet the underlying genomic alterations remain poorly understood. Here we performed exome and transcriptome sequencing and SNP array assays to characterize 51 primary gastric tumors and 32 cell lines. Meta-analysis of the exome data and previously published data sets revealed 24 significantly mutated genes in MSS tumors, and 16 in MSI tumors. More than half of the patients in our collection could potentially benefit from targeted therapies. We identified 55 splice-site mutations accompanied by aberrant splicing products, in addition to mutation-independent differential isoform usage in tumors. The ZAK kinase isoform TV1 is preferentially upregulated in gastric tumors and cell lines relative to normal samples. This pattern is also observed in colorectal, bladder, and breast cancers. Overexpression of this particular isoform activated multiple cancer-related transcription factor reporters, while depletion of ZAK in gastric cell lines inhibited proliferation. These results reveal the spectrum of genomic and transcriptomic alterations in gastric cancer, and identify isoform-specific oncogenic properties of ZAK.

  Study EGAS00001000736

• Molecular profiling of tissue autopsies and ctDNA

  The dataset contains high-throughput sequencing data derived from a cancer autopsy series of 10 patients. As part of this study, whole-exome sequencing and RNA-seq were performed for spatially distinct tissue biopsies from the patients. In addition, plasma samples from the patients were sequenced using a custom panelt to profile ctDNA. There are 106 files containing whole-exome sequencing data, 107 files containing RNA-seq data, and 9 files containing plasma sequencing data.

  Dataset EGAD00001007040

• Whole Exome Sequencing of Localized Prostate Cancer Patients

  We performed whole-exome sequencing on localized prostate cancer patients to validate tumor content as part of a single-cell RNA sequencing study of localized prostate cancer patients.

  Study EGAS00001005685

• G_WTS_001 data

  RNA-seq data from Korean CRC samples

  Dataset EGAD00001006985

• ChIP-seq ERa in primary breast cancer tissues

  ChIP-seq has been perfomed on 5 tumor fresh-frozen primary breast cancer tissues from female patients. Immunoprecipitation has been performed for ERa (SC-543, Santa Cruz). Raw single-end fastq data have been aligned using bwa-mem using Hg19 genome assebly as reference. Unfiltered aligment bam files are provided.

  Dataset EGAD50000000014

• ERa ChIP-seq in breast healthy, primary cancer and metastatic tissues

  ChIP-seq has been perfomed on fresh-frozen tissue derived from healthy breast (HB), primary breast cancer (PB), BCa-derived liver metastasis (LM). Immunoprecipitation has been performed for ERa (sc-542, SantaCruz). Raw paired-end fastq.gz files are provided for both immunoprecipitated DNA and input samples.

  Dataset EGAD50000000642

• Comparison of the single-cell and single-nucleus hepatic myeloid landscape within decompensated cirrhosis patients

  In-patient comparison of single-cell RNA-sequencing (scRNA-seq) and single-nucleus (snRNA-seq) technologies and accompanying tissue processing protocols on transjugular liver biopsy from decompensated cirrhosis patients (n = 3).

  Dataset EGAD50000000105

• Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses

  Background Single-cell RNA sequencing (scRNAseq) is a powerful tool for studying complex biological systems, such as tumour heterogeneity and tissue microenvironments. However, the sources of technical and biological variation in primary solid tumour tissues and patient-derived mouse xenografts for scRNAseq, are not well understood. Here, we used low temperature (6°C) protease and collagenase (37°C) to identify the transcriptional signatures associated with tissue dissociation across a diverse scRNAseq dataset comprising 128,481 cells from patient cancer tissues, patient-derived breast cancer xenografts and cancer cell lines.Results We observe substantial variation in standard quality control (QC) metrics of cell viability across conditions and tissues. From FACS sorted populations gated for cell viability, we identify a sub-population of dead cells that would pass standard data filtering practices, and quantify the extent to which their transcriptomes differ from live cells. We identify a further subpopulation of transcriptomically “dying” cells that exhibit up-regulation of MHC class I transcripts, in contrast with live and fully dead cells. From the contrast between tissue protease dissociation at 37°C or 6°C, we observe that collagenase digestion results in a stress response. We derive a core gene set of 512 heat shock and stress response genes, including FOS and JUN, induced by collagenase (37°C), which are minimized by dissociation with a cold active protease (6°C). While induction of these genes was highly conserved across all cell types, cell type-specific responses to collagenase digestion were observed in patient tissues. We observe that the yield of cancer and non-cancer cell types varies between tissues and dissociation methods.Conclusions The method and conditions of tumour dissociation influence cell yield and transcriptome state and are both tissue and cell type dependent. Interpretation of stress pathway expression differences in cancer single cell studies, including components of surface immune recognition such as MHC class I, may be especially confounded. We define a core set of 512 genes that can assist with identification of such effects in dissociated scRNA-seq experiments.

  Study EGAS00001003753

• Systematic kinase inhibitor profiling identifies CDK9 as a synthetic lethal target in NUT midline carcinoma

  Kinase inhibitors represent the backbone of targeted cancer therapy, yet only a limited number of oncogenic drivers are directly druggable. By interrogating the activity of 1,505 kinase inhibitors we found that BRD4-NUT-rearranged NUT midline carcinoma (NMC) cells are specifically killed by CDK9 inhibition (CDK9i) and exhibit a unique dependency on CDK9 and Cyclin-T1 expression. We show that CDK9i leads to robust induction of apoptosis and of markers of DNA damage response in NMC cells. While both CDK9i and bromodomain inhibition over time result in reduced Myc protein expression, only bromodomain inhibition induces cell differentiation and a p21-induced cell cycle arrest in these cells. Finally, RNA-Seq and ChIP-based analyses reveal a BRD4-NUT specific CDK9i-induced perturbation of transcriptional elongation. Thus, our data provide a mechanistic basis for the genotype-dependent vulnerability of NUT midline carcinoma cells to CDK9i that may be of relevance for the development of targeted therapies for NMC patients.

  Study EGAS00001002588

• Ipilimumab and Decitabine in Treating Patients With Relapsed or Refractory Myelodysplastic Syndrome or Acute Myeloid Leukemia

  The NCI Experimental Therapeutics Clinical Trials Network (ETCTN)/Cancer Therapy Evaluation Program (CTEP) 10026 study (NCT02890329) tested combined ipilimumab and decitabine treatment in two cohorts: Arm A consisted of patients with relapsed acute myeloid leukemia (AML) after allogeneic hematopoietic stem cell transplantation. Arm B consisted of patients with advanced myelodysplastic syndrome (MDS) or AML that did not previously undergo stem cell transplantation. During the study, peripheral blood and bone marrow samples were obtained from study participants at study entry (screening), following the first lead-in cycle of decitabine monotherapy, during combined treatment with decitabine and ipilimumab, and at the end of treatment.This study tested the combination of the CTLA-4 blocking antibody ipilimumab and the DNA methyltransferase inhibitor decitabine in advanced myeloid disease in the transplant-naive and post-transplant context. The samples were used for bulk and single cell RNA sequencing (scRNA-seq) as well as whole exome sequencing (WES).

  Study phs003015

• An epigenomics time course analysis of covid19 patients from Quebec, Canada

  Investigating the cellular and epigenetic changes at play in severely ill hospitalized COVID-19 patients at admission and how it evolves with prognosis. Single-cell RNA-seq analysis done on longitudinal samples highlighted changes in the monocytic compartment, which we explored using whole-genome epigenomics methods (ATACseq abd WGBS).

  Study EGAS00001005468

• BLUEPRINT release August 2014, RNA-Seq for CD34-negative, CD41-positive, CD42-positive megakaryocyte cell

  RNA-Seq data for 4 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 22 run(s), 4 experiment(s), 4 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001000903

• BLUEPRINT release January 2015, RNA-Seq for CD34-negative, CD41-positive, CD42-positive megakaryocyte cell

  RNA-Seq data for 5 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 23 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_rnaseq_analysis_crg_20140811

  Dataset EGAD00001001165

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

  RNA-Seq data for 5 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 23 run(s), 5 experiment(s), 5 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001534

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

  RNA-Seq data for 1 effector memory CD8-positive, alpha-beta T cell, terminally differentiated sample(s). 1 run(s), 1 experiment(s), 1 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_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002320

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

  RNA-Seq data for 6 CD34-negative, CD41-positive, CD42-positive megakaryocyte cell sample(s). 24 run(s), 6 experiment(s), 6 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002339

• Blueprint: A human variation panel of genetic influences on epigenomes and transcriptomes in three immune cell types, (RNA-Seq for CD4-positive, alpha-beta T cell, on genome GRCh37)

  RNA-Seq data for 212 CD4-positive, alpha-beta T cell sample(s). 212 run(s), 212 experiment(s), 212 analysis(s) on human genome GRCh37. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/blueprint_Epivar/protocols/README_rnaseq_analysis_sanger_20160816

  Dataset EGAD00001002671

• Blueprint: A human variation panel of genetic influences on epigenomes and transcriptomes in three immune cell types, (RNA-Seq for CD14-positive, CD16-negative classical monocyte, on genome GRCh37)

  RNA-Seq data for 197 CD14-positive, CD16-negative classical monocyte sample(s). 197 run(s), 197 experiment(s), 197 analysis(s) on human genome GRCh37. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/blueprint_Epivar/protocols/README_rnaseq_analysis_sanger_20160816

  Dataset EGAD00001002674

• VFF RNA-Seq data

  RNA-Seq data from vocal fold fibroblasts from controls and patients with Reinke’s edema

  Dataset EGAD00001007079

• TIGER samples

  The TIGER samples dataset contains PISA cohort samples which consist of paired RNA-seq and genotyping array data. It contains 127 RNA-seq pair-end samples in fastq format and 127 individuals genotypes in PLINK format.

  Dataset EGAD00001007990

• Paired RNA-Seq was performed on 125 samples of low grade pediatric glioma

  Paired RNA-Seq was performed on 125 samples of low grade pediatric glioma. The sequencing was done with Illumina Novaseq 6000 and the Illumina TruSeq stranded mRNA kit.

  Dataset EGAD00001010171

• BELLINI clinical trial single-cell RNA-Seq and TCR data: cohorts A & B

  Single-cell RNA-Seq data and TCR sequencing data (both by 10X Genomics) of 51 TNBC primary tumors obtained from 29 unique patients from BELLINI clinical trial. The data includes pre- and post-treatment samples. Patients in cohort A (16 patients, 28 samples) received nivolumab for 4 weeks, patients in cohort B (13 patients, 23 samples) received nivolumab + ipilimumab for 4 weeks. The included sequencing data was generated from frozen material for cohort A and from fresh material for cohort B.

  Dataset EGAD50000000807

• Patient-Derived Follicular Lymphoma Spheroids recapitulate lymph node signaling and immune profile, uncovering galectin-9 as a novel immunotherapeutic target

  RNA-seq data from CD20+ sorted cells obtained from peripheral blood and lymph node Follicular Lymphoma patients. These samples were unstimulated after thawing and additionally, peripheral blood samples were stimulated during 7 days in culture as described in Dobaño-López C et. al.)

  Study EGAS50000000233

• RNA seq of MPNST tumour samples

  RNA sequencing of 10 MPNST tumour samples as part of a larger study of MPNST. Article: Lyskjær et al, 2020, J Pathol, "H3K27me3 expression and methylation status in histological variants of malignant peripheral nerve sheath tumours".

  Study EGAS00001004528

• INSPIRE RNA-seq tumors

  INSPIRE whole transcriptome sequencing of tumors

  Dataset EGAD00001006564

• Whole Transcriptome Sequencing

  RNA-seq data of 15 snap-frozen tissue of peritoneal mesothelioma. The strand specific RNA library prepared using TruSeq (Illumina) and pair-end sequencing performed in Illumina HiSeq 4000. The datasets contains paired fastq files for each of 15 tumor samples.

  Dataset EGAD00001004504

• RNA-seq explants chondrocytes

  Osteochondral explants were obtained from knee joints (n=17 explants) from the RAAK study. Paired-end 2x150 bp RNA sequencing (Illumina TruSeq mRNA Library Prep Kit, Illumina HiSeq X) was performed.

  Dataset EGAD00001008752

• RNA-seq of AD, MCI and control ONS cells

  Total RNA sequencing of cultured ONS cells derived from patients with Alzheimer's disease (AD), individuals with mild cognitive impairment (MCI) and cognitively healthy controls.

  Dataset EGAD00001009395

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

  Data supporting: "Repurposing of KLF5 activates a cell cycle signature during the progression from Barrett’s Oesophagus to Oesophageal Adenocarcinoma." Rogerson et al. RNA-seq data 2 samples

  Dataset EGAD00001005915

• ImmuNEO CD8 cell lines

  Paired RNA-Seq data from 16 samples of different tumors CD8+ T cells added to the study "Proteogenomic analysis reveals RNA as a source for tumor-agnostic neoantigen identification (H021)". Sequencing was performed on Illumina NextSeq 500. The sequencing was always paired

  Dataset EGAD50000000193

• Newcastle COVID-19 Single-cell PBMC

  Single-cell multi-omic profiling of healthy controls, asymptomatic and hosptial-admitted COVID19 patients recruited from Newcastle University hospitals. These data also include healthy control volunteers treated with IV-LPS as inflammatory controls. Data represent RNA-seq, surface protein measurements (CITE-seq) of 192 antibody targets, along with VDJ-seq profiling of single T cell and B cell receptors.

  Dataset EGAD00001007866

• Effect of the Placental Transcriptome on Stunting in a Longitudinal African Cohort

  Mammals with placentas and flowering plants evolved genomic imprinting in nutritive tissues, the placenta and endosperm, respectively. In these tissues, the genomes inherited from the mother and father are in conflict over resource allocation to offspring. In imprinted genes, transcription is repressed on the paternal or the maternal allele, resulting in allele specific expression (ASE). We investigated the variation in ASE of imprinted genes in term human placentas in order to detect loss of imprinting (LOI), which leads to partial expression of the repressed allele. We collected the placental tissue from birth to women in our multigenerational, prospective cohort study in Mali, West Africa. We followed the women from their own infancies, early childhood to adulthood (age 18+ years). Contingent on prior informed consent, we collected placental tissue and umbilical cord tissue. We conducted RNA-Seq of the fetal compartment of the placentas and targeted DNA-Seq of the umbilical cord tissue, which is fetal, and of saliva samples from parents. Our sequencing effort produced two datasets. The first dataset is the whole transcriptome RNA-Seq dataset of 111 biopsies (59 placentas) and genotyping of 96 genes. Birth length, weight, and placental weight for the children associated with this dataset are listed in the phenotype file (DOI: 10.1093/molbev/msz226). The second dataset includes targeted RNA-Seq of 262 samples (251 placentas) and targeted DNA-Seq for 766 genes. The genes were selected because they met any one of the following criteria: (1) imprinted and reported in some studies, (2) highly expressed in placenta, or (3) relevant to diseases of interest in this cohort (https://doi.org/10.1093/g3journal/jkab176). This study provides the first systematic analysis of variation in LOI across genes and individuals in a human population, and should shed light on the hypothesis that the modulation of imprinting is an epigenetic mechanism and plays a role in the regulation of offspring growth.

  Study phs001782

• Single-nuclei RNA sequencing of pheochromocytoma and paraganglioma arising from germline SDHB mutations

  10x genomics single-nuclei RNA sequencing of 9 SDHB-deficient non-metastatic and metastatic pheochromocytoma and paraganglioma. snRNA-seq was performed using the ‘Frankenstein’ protocol (dx.doi.org/10.17504/protocols.io.bqxymxpw). Briefly, nuclei were extracted from frozen tissues and subjected to fluorescence-activated nuclei sorting (FANS) using 4′,6-diamidino-2-phenylindole (DAPI). Sorting was performed using a BD FACSaria 2 instrument, sorting between 3000 and 10,000 nuclei per sample, capturing both diploid and tetraploid populations. FAN-sorted nuclei were immediately processed using either the 10x Chromium Single Cell 5’ (PN-1000006, 4 samples) or 3’ (PN-1000075, 4 samples) Library & Gel Bead Kit (10x Genomics, USA). Once processed, snRNA-seq libraries were sequenced on the Illumina Nova-Seq 6000 (Illumina, USA) using 150bp paired-end sequencing. This dataset contains raw sequencing reads in FASTQ format.

  Dataset EGAD50000000505

• Pulmonary atypical carcinoid multi-omic dataset on up to 42 tumours from same patient

  Pulmonary atypical carcinoid. DNA WES and RNA-Seq on 42 tumour samples collected at autopsy, 10x Chromium linked read whole genome sequencing on four tumours plus one normal sample, and targeted DNA sequencing on two clinical biopsies and one blood plasma sample. Note – RNA-Seq dataset features complex batch effect attributable to tissue processing artefacts, as described in "Complex patterns of genomic heterogeneity identified in 42 tumor samples and ctDNA of a pulmonary atypical carcinoid patient" - Robb et al., 2022 and detailed in Supplementary Table S3. Note – RNA-Seq dataset features complex batch effect attributable to tissue processing artefacts, as described in "Complex patterns of genomic heterogeneity identified in 42 tumor samples and ctDNA of a pulmonary atypical carcinoid patient" - Robb et al., 2022 and detailed in Supplementary Table S3.

  Dataset EGAD00001009296

• UROMOL 2020 - RNA-seq data for validation

  Total RNAseq data from 47 patients with NMIBC.

  Study EGAS00001005050

• RNA-seq data from diagnosis and relapse samples of Down Syndrome acute lymphoblastic leukemia.

  Dataset EGAD00001003280

• sc-RNA-Seq soft tissue sarcoma tumoroid biobank

  Dataset EGAD00001009002

• KUI6280

  RNA seq data normal and hypomethylation

  Dataset EGAD00001009887

• Microvascular Permeability, Inflammation, and Lesion Physiology in Endometriosis: A Microphysiological Systems Approach

  The goal of the study is to identify novel molecular pathways involved in the etiology of endometriosis and to develop in vitro model systems to enable the study of the mechanisms regulating reproductive function. Using a physiomimetic modeling approach, primary tissue samples of the human endometrium derived from patients diagnosed with and without endometriosis and/or endometriotic diseases (e.g. adenomyosis) were used for secondary analysis using multi-omic systems biology analysis and to build tissue engineered models. We performed single cell RNA sequencing (scRNA-Seq, N=6)) to study the cellular and transcriptomic composition of the endometrial tissue microenvironment and proteomics (LC-MS/MS) to study protein-level signaling pathways and the matrisome of the native endometrium. Systems biology analysis of these datasets helped identified a putative dysregulated inflammatory signaling pathway in endometriosis patients compared to controls. Moreover, subsets from these scRNA-Seq and proteomic datasets were used to aid the design of a synthetic extracellular matrix hydrogel as an in vitro platform for the culture of endometrial cells. Tissue-engineered synthetic PEG hydrogel enables the simultaneous co-culture of endometrial epithelial organoids and stromal fibroblasts in a fully defined, 3D, and tunable environment. We demonstrated that the in vitro co-culture model recapitulates key phenotypic processes observed across the human menstrual cycle in response to sex hormone stimulation through both biochemical and transcriptomic (bulk RNA-sequencing) analysis. This model will enable future mechanistic studies that examine origins of endometriotic disease phenotypes. The transcriptomic data generated for this study including the scRNA-Seq data from primary human endometrial tissues and the bulk RNA-Seq datasets from the experimental co-culture models is available through dbGAP.

  Study phs003326

• RNA-sequencing of Human Thyroid cancer cell lines

  RNA-sequencing data of 5 human thyroid cancer cell lines cultured in control conditions

  Dataset EGAD00001011677

• scEC&T-seq manuscript data

  This dataset includes all data produced in the study describing "scEC&T-seq", a method for parallel sequencing of extrachromosomal circular DNA and transcriptome in single cells. This dataset includes: - Illumina scEC&T-seq Circle-seq data (scCircle-seq) for a total of 626 single cells / nuclei - bam files - Illumina scEC&T-seq RNA-seq data (scRNA-seq-Illumina) for the same single cells / nuclei - bam files - Nanopore scCircle-seq data for 18 single cells - bam files - Nanopore bulk WGS for 2 cell lines and 2 primary tumor samples - bam files - Illumina bulk WGS for 2 cell lines - bam files - Illumina bulk Circle-seq data from 1 cell line - bam file - Illumina ChIP-seq H3K27me3 data from 1 cell line - fasta files + peaks bed file + coverage bw file

  Dataset EGAD00001010071

• Evaluation of triple negative breast cancer with heterogeneous immune infiltration

  Identification of potential RNA markers fir TILs infiltration in patients with triple negative breast cancer with heterogeneous immune infiltration.

  Study EGAS00001007159

• RNA-sequencing of mechanical stress induced osteoarthritis-like damage in aged human cartilage explants treated with the anti-deiodinase iopanoic acid

  The current study aimed to confirm chondroprotective effects of the D2 inhibitor iopanoic acid (IOP) in an ex vivo aged human osteochondral explant model in which injurious mechanical stress is applied to inflict OA-like damage. This dataset contains RNA-seq (Illumina HiSeq X ten) of osteochondral explant cartilage from aged human patients that underwent a joint replacement surgery due to OA (N=10 donors; n=21 explants).

  Study EGAS00001006242

• RNA-seq of cultured human hematopoietic stem and progenitor cells from umblical cord blood in cytokine-rich ex vivo culture conditions following sphingolipid modulation

  In order to elucidate the biological pathways altered by sphingolipid modulation with N-(4-hydroxyphenyl) retinamide (4HPR) treatment in human HSPC that may contribute to the restraint in proliferation while promoting persistence of HSC self-renewal, as well as determine the mechanism of synergy in enhancement of HSC self-renewal with CB CD34+ agonists UM171 and StemRegenin 1 (SR1), we performed RNA-sequencing (RNA-Seq) of 3 pools of lin-CB cells following 2 or 4 days with DMSO, 4HPR, UM171+SR1 or 3-Factor (4HPR+UM171+SR1). We identified modulation of sphingolipid metabolism regulates self-renewal through activating coordinated stress pathways that coalesce on endoplasmic reticulum stress and autophagy programs.

  Dataset EGAD00001005140

• single cell RNA-seq of bone marrow from infants with MLL-rearranged Acute Lymphoblastic Leukemia by single cell RNA-sequencing

  This dataset contains two experiments. 1) Single cell RNA-seq of diagnostic samples from patients with MLL-rearranged infant ALL that underwent relapse or not (samples ending in R relapsed, samples ending in N did not). For some of the patients, multiple indipendent plates were produced (each plate is a sample). 2) in vitro prednisolone exposure experiment. diagnostic bone marrow samples from patient 4662R were cultured for three days with and without prednisolone. Single cell experiments were conducted according to Muraro et al (cell systems, 2016, doi:10.1016/j.cels.2016.09.002). Cell barcodes and UMI sequences are embedded in the header of each fastq entry. Cell barcodes irrelevant to this experiment were removed before submission.

  Dataset EGAD00001005461