9172 results for "cancer rna-seq"

in 48.97 milliseconds.

• ICGC PCAWG Dataset: RECA-EU_PCAWG_RNA-Seq_Star

  ICGC PCAWG Dataset for RNA-Seq BAM aligned using Star. Project: RECA-EU.

  Dataset EGAD00001003558

• ICGC PCAWG Dataset: RECA-EU_PCAWG_RNA-Seq_TopHat2

  ICGC PCAWG Dataset for RNA-Seq BAM aligned using TopHat2. Project: RECA-EU.

  Dataset EGAD00001003559

• ICGC PCAWG Dataset: MALY-DE_PCAWG_RNA-Seq_Star

  ICGC PCAWG Dataset for RNA-Seq BAM aligned using Star. Project: MALY-DE.

  Dataset EGAD00001003560

• ICGC PCAWG Dataset: MALY-DE_PCAWG_RNA-Seq_TopHat2

  ICGC PCAWG Dataset for RNA-Seq BAM aligned using TopHat2. Project: MALY-DE.

  Dataset EGAD00001003561

• preinvasive LUAD

  Whole-exome sequencing coupled with RNA-seq of preinvasive (n=98) and invasive (n=99) lung adenocarcinoma samples.

  Dataset EGAD00001005479

• Melanoma microRNA profiling

  This dataset includes microRNA profiling of 61 early-passage metastatic melanoma cell lines. The data are provided as single-end small RNA seq fastq files.

  Dataset EGAD00001006269

• Melanoma transcriptome profiling

  This dataset includes transcriptome profiling of 68 early-passage metastatic melanoma cell lines. The data are provided as paired-end RNA seq fastq files.

  Dataset EGAD00001006270

• Log2 normalized TPM matrix for POPLAR (GO28753)

  This dataset contains log2(TPM + 1) for 192 tumor samples profiled by RNA-seq for the entire transcriptome for samples originating from POPLAR (GO28753).

  Dataset EGAD00001008390

• Log2 normalized TPM matrix for OAK (GO28915)

  This dataset contains log2(TPM + 1) for 699 tumor samples profiled by RNA-seq for the entire transcriptome for samples originating from OAK (GO28915).

  Dataset EGAD00001008391

• RNA-Seq soft tissue sarcoma tumoroid biobank

  Dataset EGAD00001008467

• ATAC-seq data in normal colon mucosa

  This dataset includes ATAC-seq data generated in normal colon mucosa obtained in four healthy volunteers during colonoscopy indicated for colorectal cancer screening. Subjects had no lesions in the colon. Also includes one frozen sw480 colon adenocarcinoma cell line sample for piloting the protocol

  Study EGAS00001005281

• SCLC study MGH - RNAseq dataset

  RNA-seq analyses were performed on cDNA libraries prepared from PolyA+ RNA using the Illumina TruSeq protocol for mRNA. The final libraries were sequenced with a paired-end 2×75 bp protocol aiming at 8.5 Gb per sample for a 30x mean coverage of the annotated transcriptome. All sequencing reactions were conducted on an Illumina HiSeq instrument (Illumina, San Diego, CA, USA).

  Dataset EGAD00001003969

• A New High-Throughput Sequencing-Based Technology to Study Heterochromatin Structure

  In this study we report epigenomic and transcriptomics datasets for normal control fibroblasts. The following cell lines were obtained from the NIGMS Human Genetic Cell Repository at the Coriell Institute for Medical Research: AG08498, AG07095, originally collected as part of the NIA Aging Cell Repository study. We applied a high-throughput sequencing-based technique, named Sequential Analysis of MacroMolecules accessibilitY (SAMMY-seq), for the genome-wide mapping of chromatin regions separated by differential accessibility. The method is based on the sequential extraction of multiple chromatin fractions, corresponding to increasingly compacted and less accessible chromatin regions, which are mapped along the genome using high-throughput sequencing. Additionally we carried out ChIP-seq for the H3K9me3 and H3K27me3 histone modifications and RNA-seq for the characterization of transcriptome in control fibroblasts.

  Study phs002202

• Colorectal adenomas and carcinomas NKI-AvL TGO series Gut2009

  Colorectal cancer (CRC) develops from normal epithelium, through a benign precursor lesion called adenoma, by accumulation of genetic alterations affecting oncogenes and tumour suppressor genes. These CRC-related genomic alterations often result in specific RNA-expression patterns. RNA isolated from fresh frozen specimen of 32 adenomas and 29 CRCs was obtained from the previously published study (Carvalho et al. 2009) and RNA-sequencing was performed with the aim to examine RNA expression changes in colorectal adenoma-to-carcinoma progression.

  Study EGAS00001002758

• Chromatin run-on and RNA sequencing of fibrolamellar carcinoma

  Fibrolamellar carcinoma (FLC) is a rare, therapeutically intractable liver cancer that disproportionately affects youth. Here we used chromatin run-on sequencing to characterize the enhancer landscape in FLC and RNA sequencing to identify dysregulated genes in FLC.

  Study EGAS00001004169

• RaScALL: Rapid screening of RNA-seq in acute lymphoblastic leukaemia

  RNA-sequencing (RNA-seq) efforts in acute lymphoblastic leukaemia (ALL) have identified numerous prognostically significant genomic alterations which can guide diagnostic risk stratification and treatment choices when detected early. However, a full RNA-seq Bioinformatics workflow is time-consuming and costly in a clinical setting where rapid detection and accurate reporting of clinically relevant alterations are essential. To accelerate the identification of ALL-specific alterations (including gene fusions, single nucleotide variants and focal gene deletions), we developed the rapid screening tool RaScALL, capable of identifying more than 100 prognostically significant lesions directly from raw sequencing reads. RaScALL uses the k-mer based targeted detection tool km and known ALL variant information to achieve a high degree of accuracy for reporting subtype defining genomic alterations compared to standard alignment-based pipelines. Gene fusions, including difficult to detect fusions involving EPOR and DUX4, were accurately identified in 98% (164 samples) of reported cases in a 180-patient Australian study cohort and 95% (n=63) of samples in a North American validation cohort. Pathogenic sequence variants were correctly identified in 75% of tested samples, including all cases involving subtype defining variants PAX5 p.P80R (n=12) and IKZF1 p.N159Y (n=4). Accurate detection of intragenic IKZF1 deletions resulting in aberrant transcript isoforms was also detectable with 98% accuracy. Importantly, the median analysis time for detection of all targeted alterations averaged 22 minutes per sample, significantly shorter than standard alignment-based approaches, ensuring accerelated risk-stratification and therapeutic triage.

  Study EGAS00001006460

• NextGen Consortium: GENESiPS Study: Identifying the Gene Networks of Insulin Resistance

  Variability in induced pluripotent stem cell (iPSC) lines remains a roadblock for disease modeling and regenerative medicine. Through linear mixed models we have described different sources of gene expression variability from RNA sequencing data in 317 human iPSC lines from 101 individuals. We found that ~50% of genome-wide expression variability is explained by variation across individuals and identified a set of expression quantitative trait loci that contribute to this variation. These analyses coupled with allele specific expression show that iPSCs retain a subject-specific gene expression pattern. Pathway enrichment and key driver analyses, based on predictive causal gene networks, found that Polycomb targets explain a significant part of the non-genetic variability present in iPSCs within and across individuals. These publically available iPSC lines and genetic datasets will be a resource to the scientific community and will open new avenues to reduce variability in iPSCs and improve their utility in disease modeling. SNP array data from individuals included in RNA-seq transcriptome profiling study of human induced pluripotent stem cells to characterize gene expression variation across individuals and within multiple iPSC lines from the same individual. Genotyping was performed on patient blood. Data availability: SNP-genotyping: dbGaP - current study RNA-seq counts: GEO - GSE79636 FASTQ files: SRA - SRP072417

  Study phs001139

• ChIP-Seq (H3K4me3, H3K4me1, H3K9me3, H3K27ac, H3K27me3, H3K36me3, Input) data for HL60 cell line generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency.

  ChIP-Seq (H3K4me3, H3K4me1, H3K9me3, H3K27ac, H3K27me3, H3K36me3, Input) data for HL60 cell line generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency.

  Dataset EGAD00001002238

• Tumor HTG EdgeSeq from metastatic castrate resistant prostate cancer

  This dataset contains tumor bulk HTG EdgeSeq from patients with metastatic castrate resistant prostate cancer. RNA libraries were prepared following manufacturer's user guide (HTG Molecular Diagnostics). Each library was sequenced in HTG EdgeSeq system.

  Study EGAS00001004852

• Colorectal adenomas, carcinomas and adjacent normal NKI-AvL TGO series NGS-ProToCol

  Cancer is caused by changes in the genome of cells, resulting in aberrant transcripts and proteins. In order to understand why normal cells become cancer cells and how we can identify and destroy them, the CTMM-NGS-ProToCol project aimed to understand prostate and colorectal cancer through DNA and RNA molecular profiling, to further improve diagnosis, prognosis and treatment.The state-of-the-art within the field of genome sequencing makes it possible to identify all the modifications in our genome that encode for RNA and of the transcripts themselves. The latest development in RNA sequencing is that if one does not select for polyA RNA, but first removes rRNA from the total RNA and then performs ‘random’ RNA sequencing, 30-60% of the reads are intronic. Since about 40% of the genome consists of genes (and only 1.6% is exonic), deep RNA sequencing will cover not only the exons, but also a large portion of the introns and therefore much of the genome. The power of the combined sequencing of genome and transcriptome is the full view of copy number aberrations (CNA), exon mutations and the consequence and relevance of the mutations at the RNA level in the form of differential gene expression, alternative splicing, alternative promoter usage, novel transcripts, fusion transcripts, read-through transcripts and mutations. For the colorectal (tumor) tissue dataset, we applied molecular profiling to 30 colorectal adenomas, 30 colorectal carcinomas and 18 normal adjacent colon tissues.

  Study EGAS00001002854

• Genome-wide chromatin accessibility profiling of primary human glomerular and kidney cortex tubular outgrowth cultures

  We generated primary cultures from mechanically isolated kidney glomeruli (filtration unit of the nephron) which are composed of podocytes and mesangial cells. In parallel, we generated primary kidney cortex tubule cell cultures, which are composed primarily of proximal tubule cells. Early passage cultures of these two cell types were subjected to chromatin accessibility profiling (DNase-Seq) and gene expression profiling (RNA-Seq). We found thousands of dynamically regulated enhancers in both cell types that potentially regulate nearby and distal target genes that are differentially expressed. These data will be useful for understanding the epigenomic regulation of gene transcription in key kidney cell types.

  Study phs001720

• Supraphysiologic MDM2 Expression Impacts P53-Independent Chromatin Networks and Therapeutic Responses in Sarcoma

  We collected multiple liposarcoma samples from different patients, including different subtypes (DD, WD) and normal adipose tissue as control. This study provides the biggest liposarcoma cohort to date, and examined the molecular regulatory circuits associated with MDM2 overexpression. To this end, we obtained not only RNA-seq data, but also ChIP-seq from Jun, RUNX, MDM2, P53 and H3K27ac, as well as hiChIP from tumor samples and cell lines. We found that MDM2 binds to thousands of genes involved in cellular growth and stress response in a P53-independent manner. Furthermore, we described these active genes engaged in multi-way topological interactions that resemble transcriptional hubs.

  Study phs003272

• Epigenetic Landscape of Human Parathyroids

  The goal of this study is to produce a comprehensive map of the chromatin landscape of human parathyroids. Data from 20 subjects with parathyroid adenoma causing primary hyperparathyroidism were used. For the sequencing platform, Illumina HiSeq 2000 with V3 high-output kits were used. For the data processing pipeline, reads were aligned to hg19 using Bowtie or BWA. For RNA-seq data, transcript levels were estimated per gene to RPKM using Cufflink. For ChIP-seq and ATAC-seq data, enrichment peaks were estimated compared to inputs or background using MACS2 after merging reads from replicates. For DNase-seq, significant peaks compared to background distribution were computed using Hotspot. For Hi-C data, significant interactions were detected using Juicer HiCCUPS and 5 kb resolution for the merged data from replicates. Chromatin states for parathyroids were computed using ChromHMM based on ChIP-seq profiles in parathyroids of H3K4me3, H3K4me1, H3K27ac, H3K36me3, H3K27me3 and H3K9me3 and the emission matrix from 18 states pre-trained in the Roadmap Epigenomics. Gene expression, binding positions of transcription factor, open chromatin regions, 3D-chromatin interaction, and chromatin states are submitted.

  Study phs003302

• cHCC-ICC RNAseq

  The RNA-seq data of 97 tumor samples from 77 cHCC-ICC cases, data of two other HCC tumor samples were also included.

  Dataset EGAD00001005182

• Esophageal Adenocarcinoma Organoid scRNAseq data

  This is 10X single cell RNA-seq data of esophageal adenocarcinoma organoids.

  Dataset EGAD00001007525

• Biomarker data

  Biomarker data for KATHERINE: Biomarker data include RNA-seq time point, Percent of tumor content, PAM50 subtypes, normalized gene expression of ERBB2, CD8 and CD274, normalized immune signature expression.

  Dataset EGAD00001008786

• 2_cortical-neurons_HD_vs_Ctrl_DMSO_Branaplam

  n=3 Ctrl and n=3 HD iPSC lines differentiated into cortical neurons were treated with DMSO or 10nM Branaplam for 72h and RNA-seq was performed.

  Dataset EGAD00001008808

• RNAseq following stent placement and removal in a porcine model 

  This dataset includes 2*76bp RNA-seq reads from 9 pigs sequenced using Illumina NextSeq500.

  Dataset EGAD00001009783

• Genomic Data for Integrative Profiling of T790M Negative EGFR Mutated NSCLC

  Contains WES and RNA-seq for the 59 patients with first- and second-generation EGFR TKI-resistant metastatic EGFR-mutated NSCLC.

  Dataset EGAD00001010272

• Profiling human first-trimester neurodevelopment using scATAC-seq and multiomics

  116 single cell ATAC runs and 23 single cell multiome (ATAC+RNA) runs on various brain regions during human first-trimester development.

  Dataset EGAD00001011300

• Single cell RNA seq of the developing human embryo brain

  The study aims at identifying the cell types and lineages of the developing human brain.

  Study EGAS00001004107

• Shallow nanopore RNA sequencing enables transcriptome profiling for precision cancer medicine (Hipo_021)

  Study EGAS00001006317

• Cell type-specific transcriptomics of esophageal adenocarcinoma

  3' mRNA-Seq obtained from distinct isolated cell types (epithelia cells,immune cells, fibroblasts) of endoscopically obtained esophageal adenocarcinoma tissue as well as normal esophageal mucosa. Libraries for RNA-sequencing were prepared using the QuantSeq 3' mRNA-Seq Library Prep Kit FWD for Illumina according to the low input protocol. Libraries were sequenced on a HiSeq 4000 (Illumina) by 1x 50 bases.

  Dataset EGAD00001005508

• The effect of freezing delay of cell-type specific transcriptome responses in human brain via snRNA-seq

  In other analysis in the current manuscript, we find a similar gene signature (to dissociation based artifacts in mouse and human tissue) is present in post-mortem microglia and astrocytes, across all snRNA-seq datasets analyzed, although it is highly variable between subjects. ​ Using acutely-resected neurosurgical tissue, we performed single-nucleus RNA-seq and reveal that a similar signature can be detected in microglia following prolonged exposure to room temperature. Tissue handling and methods details, as well as sequencing and analysis details) can be found in the methods section of related manuscript (Marsh et al., 2022). Together, these results suggest that the presence of this signature in post-mortem brain samples may be the result of a combination of acute pre-mortem (agonal state, cause of death, comorbidities, etc.) and post-mortem (post-mortem interval (PMI), storage time, RNA quality, etc.) variables and may not represent normally present cell state.

  Dataset EGAD00001008541

• RNA-seq of iPSC-derived oligodendrocytes of individuals with and without t(1;11) translocation

  This dataset contains high-throughput RNA-sequencing of 14 samples, each sample comprising oligodendrocytes derived from human induced pluripotent stem cells, from individuals with and without a balanced t(1;11) translocation which substantially increases risk of major mental illness. 5 samples derive from 2 control individuals, and 9 samples from 3 individuals carrying the translocation. Libraries were prepared from each total-RNA sample using the TruSeq Stranded Total RNA with Ribo-Zero kit. Libraries were then sequenced using the NextSeq 500/550 High-Output v2 (150 cycle) Kit on the NextSeq 550 platform. Raw paired-end sequencing data is stored in two FASTQ files per sample.

  Dataset EGAD00001006341

• Single cell RNA sequencing of colorectal cancer with diverse tissue dissociation protocols or fresh vs. frozen cell preparations.

  To evaluate 3 different tissue dissociation protocols or fresh vs. frozen cell preparations, we performed single-cell RNA sequencing on cancer or distant normal tissue dissociates from 2 colorectal cancer patients. Total 18,409 cells from 10 sample preparations were analyzed (5 primary colorectal cancer and 5 matched normal mucosa). The results suggest highly consistent cellular proportions were recovered with different sample preparation methods.

  Dataset EGAD00001005191

• Significant and pervasive effects of RNA degradation on Nanopore direct RNA sequencing

  Abstract Oxford Nanopore direct RNA sequencing (DRS) is capable of sequencing complete RNA molecules and accurately measuring gene and isoform expression. However, as DRS is designed to profile intact RNA, expression quantification may be more heavily dependent upon RNA integrity than alternate RNA-seq methodologies. It is currently unclear how RNA degradation impacts DRS or if it can be corrected for. To assess the impact of RNA integrity on DRS we performed a degradation time-series using SH-SY5Y neuroblastoma cells. Our results demonstrate that degradation is a significant and pervasive factor that can bias DRS measurements, including a reduction in library complexity resulting in an overrepresentation of short genes and isoforms. Degradation also biases differential expression analyses; however, we find explicit correction can almost fully recover meaningful biological signal. In addition, DRS provided less biased profiling of partially degraded samples than nanopore cDNA-PCR sequencing. Overall, we find samples with RIN > 9.5 can be treated as undegraded and samples with RIN > 7 can be utilised for DRS with appropriate correction. These results establish the suitability of DRS for a wide range of samples, including partially degraded in-vivo clinical and post-mortem samples, whilst limiting the confounding effect of degradation on expression quantification.

  Study EGAS00001006542

• Mapping_regulatory_variation_in_sensory_neurons_using_IPS_lines_from_the_HIPSCI_project

  Sensory neurons are nerve cells that are activated by sensory input such as heat, light and convey information to the brain. Although a key cell type in complex organisms, human sensory neurons are challenging to study because they are impossible to obtain from living donors. We have collaborated with the Neucentis Pharmaceutical Research Unit to differentiate sensory neuron like cells from human induced pluripotent stem cells derived as part of the Human Induced Pluripotent Stem Cells Initiative. We will sequence RNA from 100 IPS lines derived from healthy individuals and perform RNA-seq on the differentiated cells to identify noncoding variants that alter gene expression in human sensory neurons.

  Study EGAS00001001149

• Cambridge COVID-19 Single-cell PBMC

  Single-cell multi-omic profiling of healthy controls, asymptomatic and hosptial-admitted COVID19 patients recruited from Addenbrookes and Royal Papworth hospitals, in collaboration with the NIHR Cambridge Bioresource. 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. Samples are pooled, with 4 donors per pool. Germ-line genotypes are provided (VCF) to aid demultiplexing of single-cell and assignment to specific patient donor samples.

  Dataset EGAD00001007867

• RNA-sequencing of gluten-reactive and non-reactive T-cells from blood samples of treated CeD patients during a gluten-challenge

  Gluten-specific CD4+ T cells are drivers of celiac disease (CeD). Here we aimed to characterize such cells in blood of treated CeD patients during gluten challenge with comparison to similar cells of untreated disease. Treated CeD patients underwent a 3-day gluten-challenge with blood sampling at baseline and day 6 (d6). Blood cells were stained with HLA-DQ:gluten tetramers (Tetramer). CD4+, gut-homing Tetramer+ and Tetramer- effector-memory T (TEM) cells at d6 were subjected to bulk RNA-seq (n=7).

  Study EGAS00001004988

• Deciphering RBP - alternative splicing networks in ALS iPSC-MN: TDP-43, NOVA1, NOVA2 and RBFOX2 eCLIP-seq

  We produced enhanced cross-linking immunoprecipitation (eCLIP) sequencing data of the RNA binding proteins (RBP) TDP-43, NOVA1, NOVA2 and RBFOX2 in iPSC motor neurons of two healthy control individuals, respectively.

  Study EGAS00001005880

• Comprehensive assay for the molecular profiling of cancer by target enrichment from formalin-fixed paraffin-embedded specimens

  Tumor molecular profiling is becoming a standard of care for patients with cancer, but the optimal platform for cancer sequencing remains undetermined. We established a comprehensive assay, the Todai OncoPanel (TOP), which consists of DNA and RNA hybridization capture-based next-generation sequencing panels. A novel method for target enrichment, named the junction capture method, was developed for the RNA panel to accurately and cost-effectively detect 365 fusion genes as well as aberrantly spliced transcripts. The TOP RNA panel can also measure the expression profiles of an additional 109 genes. The TOP DNA panel was developed to detect single nucleotide variants and insertions/deletions for 464 genes, to calculate tumor mutation burden and microsatellite instability status, and to infer chromosomal copy number. Clinically relevant somatic mutations were identified in 32.2% (59/183) of patients by prospective TOP testing, signifying the clinical utility of TOP for providing personalized medicine to cancer patients.

  Study JGAS000164

• Whole exome sequencing (WES), shallow whole genome sequencing (sWGS), ultra-deep targeted sequencing (TS), RNA whole transcriptome sequencing (RNAseq), targeted TCR sequencing in RNA (RNA-TCRseq) from breast cancer samples.

  Whole exome sequencing (WES), shallow whole genome sequencing (sWGS), ultra-deep targeted sequencing (TS), RNA whole transcriptome sequencing (RNAseq) bam files. Targeted TCR sequencing in RNA (RNA-TCRseq) cram files.

  Dataset EGAD00001003933

• smRNA-Seq assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, as part of the International Human Epigenome Consortium.

  smRNA-Seq assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001226

• 46 patients primary malignant glioma cohort in Chinese population

  We recruited 46 Chinese patients with primary malignant glioma. All the patients were analyzed with whole-exome sequencing (WES) and 27 of them were analyzed with RNA-seq. We compared the molecular features between patients in different WHO grades. We used six-month progression-free survival (PFS6) status to group glioblastoma (GBM) patients to a good and a poor survival compared two groups genomic profiles.

  Study EGAS00001005583

• Novel manifestations of immune dysregulation and granule defects in gray platelet syndrome

  Gray Platelet Syndrome (GPS) is a rare recessive bleeding disorder resulting from biallelic variants in NBEAL2. As part of a comprehensive evaluation of the phenotype and genotype in 47 patients with GPS, four different blood cell-types (platelets, neutrophils, monocytes, and CD4-lymphocytes) were evaluated using bulk RNA-seq in five patients and five controls. These data are deposited in this archive in FASTQ format.

  Study EGAS00001004216

• Molecular profiling for a patient with lipoblastoma-like tumor of the vulva

  Lipoblastoma-like tumors of the vulva (LLTVs) are exceptionally rare indolent adipocytic mesenchymal tumors arising in adults. Only total 19 cases have been reported previously and has just been categorized as mesenchymal tumours of the lower genital tract on the latest WHO classification of tumours, 5th edition. This is the first case of LLTV assessed for RNA-seq, WES, and WGS by next generation sequencing.

  Study JGAS000529

• To_profile_the_landscape_of_sebaceous_tumours___RNA

  Sebaceous tumours are a rare cutaneous cancer with potential for aggressive behaviour. However, limited information is available on these cancers with few published cases. Here we wish to exome sequence these cancers to define the first genomic landscape for this malignancy. We will extract RNA from formalin-fixed, paraffin-embedded (FFPE) cores. Cores may be obtained from lesional and non-lesional tissues of primaries as well as matching metastases. The extracted RNA will be used for RNA sequencing.

  Study EGAS00001007803

• The evolutionary dynamics of human colorectal cancer using single-gland spatial multi-omic profiling of DNA, RNA and chromatin.

  Study EGAS00001005827

• The evolutionary dynamics of human colorectal cancer using single-gland spatial multi-omic profiling of DNA, RNA and chromatin.

  Study EGAS00001006088

• The evolutionary dynamics of human colorectal cancer using single-gland spatial multi-omic profiling of DNA, RNA and chromatin.

  Study EGAS00001006122

• RNA sequencing of in vitro generated suppressive myeloid cells using parental and Sialidase expressing A549 cancer cell lines

  Study EGAS00001007618

• High-throughput Detection of Clinically Relevant Mutations in Archived Tumor Samples By Multiplexed PCR and Next Generation Sequencing

  PURPOSE: Tailoring cancer treatment to tumor molecular characteristics promises to make personalized medicine a reality. However, reliable genetic profiling of archived clinical specimens has been hindered by limited sensitivity and high false positive rates. Here, we describe a novel methodology, MMP-seq, which enables sensitive and specific high-throughput, high content genetic profiling in archived clinical samples. EXPERIMENTAL DESIGN: We first validated MMP-seq’s technical performance in 66 cancer cell lines and a Latin square cross-dilution of known somatic mutations. We next characterized the performance of MMP-seq in 17 formalin-fixed paraffin embedded (FFPE) clinical samples using matched fresh frozen (FF) tissue from the same tumors as benchmarks. To demonstrate the potential clinical utility of our methodology, we profiled FFPE tumor samples from 73 endometrial cancer patients. RESULTS: We demonstrated that MMP-seq enabled rapid and simultaneous profiling of a panel of 88 cancer genes in 48 samples, and detected variants at frequencies as low as 0.4%. We identified DNA degradation and deamination as the main error sources and developed practical and robust strategies for mitigating these issues, and dramatically reduced the false positive rate. Applying MMP-seq to a cohort of endometrial tumor samples identified extensive, potentially actionable alterations in the PI3K and RAS pathways, including novel PIK3R1 hotspot mutations that may disrupt negative regulation of PIK3CA. CONCLUSIONS: MMP-seq provides a robust solution for comprehensive, reliable and high- throughput genetic profiling of clinical tumor samples, paving the way for the incorporation of genomic-based testing into clinical investigation and practice.

  Study EGAS00001000674

• 20210729_EGA_BrainMet Saunus et al J Path (2015)

  Exome sequencing on HiSeq platform of 36 brain metastases with matched normal samples, 32 having matched RNA seq. Published Saunus et al J Path, (2015); https://doi.org/10.1002/path.4583

  Dataset EGAD00001007973

• Transcriptome Profiling of human AT2 cells in COPD

  RNA-seq of FACS sorted AT2 cells from ex-smokers with (n=6) and without (n=3) COPD at different disease stages. Fastq files are provided.

  Dataset EGAD00001011115

• Gene expression profile of mesothelial-derived carcinoma-associated fibroblasts

  RNA-sequencing was carried out on ascetic fluid-isolated mesothelial cells from low-grade serous ovarian cancer patients, high-grade serous ovarian cancer patients, chemotherapy-treated high-grade serous ovarian cancer patients and control mesothelial cells obtained from non-oncologic patients to identify differentially expressed genes associated to mesothelial-to-mesenchymal transition process.

  Study EGAS00001003747

• RNA-Seq of RTT patient-derived cells

  Using a direct reprogramming method, human dermal fibroblasts from a Rett Syndrome (RTT) individual and a healthy control were used to generate neurons. RNA from fibroblasts, induced neuronal progenitor cells and neurons of patient-derived and control cells were sequenced to study the differentiation process and the differences between RTT and wildtype cells.

  Study EGAS00001007376

• Indonesian RNA-seq data

  Transcription data were collected to study patterns of functional variation across the broad geography of Indonesia. The region has extremely diverse populations, with very different demographic histories and multiple genetic ancestries. This dataset reports high-throughput RNA-sequencing data for individuals from three islands spanning this geographical region: Mentawai, Sumba and West Papua.

  Study EGAS00001003671

• Genomic Studies of Bipolar Disorder in a Large Cohort from The Netherlands

  The transcriptomes of whole blood samples of a large cohort of individuals from the Netherlands were assayed using RNA-seq. These whole blood samples included patients diagnosed with schizophrenia or bipolar disorder, family members of patients, and healthy controls. Within the whole blood dataset, about 600 of the samples were sequenced to an average of 13.9 million mapped reads per sample, while about 2,000 were sequenced to an average of 5.9 million mapped reads per sample, in order to assess changes in power to detect eQTLs based on sample size. We find that expression, defined as the log transcripts per million reads (TPMs), is highly correlated when comparing the moderate (13.9M) and lower (5.9M) coverage datasets. Additionally, a subset of about 150 individuals provided fibroblast cell lines which were assessed for the levels of gene expression using RNA-seq at an average of 50 million mapped reads per sample. We use downsampling techniques to generate synthetic datasets derived from this real fibroblast RNA-Seq data to explore the relationship between coverage and number individuals in an eQTL analysis. Corresponding individual-level genotypes for the samples included in the expression matrix are also made available. The genotypes were derived from multiple other project cohorts, each using different genotyping platforms including OmniExpress Exome, Global Screening Array, Illumina550, and PsychChip. A Plink file set of these cohorts is provided here after merging the separate project file sets and extracting only the individuals who have expression data also provided here; quality control for SNP-missingness is recommended. We demonstrate in this study that given a fixed budget, eQTL discovery power can be increased by lowering the sequencing depth per sample to allow for an a greater number of individuals sequenced. 

  Study phs002856

• Kidney_tumour_RNA

  This is a bulk DNA and RNA sequencing study of human renal tumours

  Study EGAS00001002487

• Studying the single cell characteristics of pancreatic cancer

  Pancreatic cancer is a dangerous malignancy in the pancreas. In this study we use single-cell RNA sequencing technique to help understand the transcriptome characteristics of pancreatic tumor cells. This study help understands the complex microenvironment of pancreatic tumors and will likely to benefit clinical research of pancreatic cancer treatments.

  Study EGAS00001003889

• Characterization of Immune-Related Gene Expression in Lung Cancer

  We performed a comprehensive analysis of inter- and intratumor heterogeneity of immune gene expression in 160 lung cancer patients from the Environment And Genetics in Lung cancer Etiology (EAGLE) study. The transcriptome was profiled with RNA sequencing in 269 tumor samples and 110 normal tissue samples from 160 subjects.

  Study phs002346

• G&T-seq: parallel sequencing of the genomes and transcriptomes of single cells

  The ability to simultaneously sequence the genome and transcriptome of the same single cell offersa powerful means to dissect functional genetic heterogeneity at the cellular level. Here we describeG&T-seq, a method for separating and sequencing genomic DNA and full-length mRNA from singlecells. By applying G&T-seq to over 220 single cells we reveal cellular properties that cannot beinferred from DNA or RNA sequencing alone, including associations between DNA copy numbervariation and gene expression dosage. We further demonstrate the detection of coding interchromosomalfusions and single nucleotide variants in both the genomes and transcriptomes ofindividual cells. G&T-seq enables the study of genotype-phenotype associations in single cells, andthe investigation of DNA cell lineage trees of healthy and diseased tissues with transcriptome inferredcell types and states.

  Study EGAS00001001204

• Molecular determinants of response to PD-L1 blockade across tumor types

  Immune checkpoint inhibitors targeting the PD-1/PD-L1 axis lead to durable clinical responses in subsets of cancer patients across multiple indications, including non-small cell lung cancer (NSCLC), urothelial carcinoma (UC) and renal cell carcinoma (RCC). Herein, we complement PD-L1 immunohistochemistry (IHC) and tumor mutation burden (TMB) with RNA-seq in 366 patients to identify unifying and indication-specific molecular profiles that can predict response to checkpoint blockade across these tumor types. Multiple machine learning approaches failed to identify a baseline transcriptional signature highly predictive of response across these indications. Signatures described previously for immune checkpoint inhibitors also failed to validate. At the pathway level, significant heterogeneity was observed between indications, in particular within the PD-L1+ tumors. mUC and NSCLC were molecularly aligned, with cell cycle and DNA damage repair genes associated with response in PD-L1- tumors. At the gene level, the CDK4/6 inhibitor CDKN2A was identified as a significant transcriptional correlate of response, highlighting the association of non-immune pathways to the outcome of checkpoint blockade. This cross-indication analysis revealed molecular heterogeneity between mUC, NSCLC and RCC tumors, suggesting that indication-specific molecular approaches should be prioritized to formulate treatment strategies.

  Study EGAS00001004343

• CPTAC: Proteogenomic Studies of Ovarian Tumor Responses to Agents Targeting the DNA Damage Response

  There is a critical unmet need for predictors of chemo-refractory High-grade serous ovarian cancer (HGSOC). Despite over 3 decades of research on platinum responses in cancer, no predictive biomarker has been translated into clinical use. Predictors of refractory disease could spare these patients the unnecessary toxicity of a platinum-based regimen and provide a means to triage these patients to clinical trials to identify effective therapies for refractory disease. This study has approached the development of a predictor in a novel way enabling detection of a multi-analyte panel biomarker capable of detecting a subset of refractory HGSOCs with high specificity and implicating potential treatment vulnerabilities for refractory disease. We reported the first proteogenomic analysis of platinum refractoriness in HGSOC and made the novel dataset available as a resource to the community, including a ProTrack portal: http://ptrc.cptac-data-view.org/. Detailed proteogenomic profiles were generated for this study from a retrospective cohort of 242 treatment-naive HGSOCs with enriched representation of "exceptional non-responders" (i.e., patients with chemo-refractory disease). Whole genome sequence (WGS) and RNA seq FASTQ files are available through dbGaP. Proteomic data are available through the NCI Proteomic Data Commons (PDC): https://pdc.cancer.gov/pdc/.

  Study phs003152

• RNA sequencing of Korean ER positive breast cancer females aged under 35 years old.

  Corresponding data set is composed of RNA sequencing of Korean ER positive breast cancer under 35 years old. This set provides 50 alignment files of 50 tumor samples. This is a part of total project data set.

  Dataset EGAD00001003243

• Single cell RNAseq of PBMC from bladder cancer patients

  This dataset contains single cell RNA sequencing data of PBMC samples from 10 bladder cancer patients. cDNAs and single cell RNA libraries were prepared following manufacturer’s user guide (10x Genomics). Each library was sequenced in HiSeq4000 (Illumina) to achieve ~300 million reads following manufacturer’s sequencing specification.

  Dataset EGAD00001005481

• Single cell RNAseq of PBMC from bladder cancer patients

  This dataset contains single cell RNA sequencing data of PBMC samples from 20 bladder cancer patients. cDNAs and single cell RNA libraries were prepared following manufacturer’s user guide (10x Genomics). Each library was sequenced in HiSeq4000 (Illumina) to achieve ~300 million reads following manufacturer’s sequencing specification.

  Dataset EGAD00001006182

• small RNA next generation sequencing in head and neck cancer

  small RNA next generation sequencing in head and neck cancer

  Dataset EGAD00001008402

• Strand-specific mRNA-Seq assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, as part of the International Human Epigenome Consortium.

  Strand-specific mRNA-Seq assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001227

• ChIP-Seq (Input) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, as part of the International Human Epigenome Consortium.

  ChIP-Seq (Input) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001235

• Fastq data for smRNA-Seq assays for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  Fastq data for smRNA-Seq assays assay for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001401

• Chromatin accessibility maps of chronic lymphocytic leukemia identify subtype-specific epigenome signatures and transcription regulatory networks

  Chronic lymphocytic leukemia (CLL) is characterized by substantial clinical heterogeneity, despite relatively few genetic alterations. To provide a basis for studying epigenome deregulation in CLL, we established genome-wide chromatin accessibility maps for 88 CLL samples from 55 patients using the ATAC-seq assay, and we also performed ChIPmentation and RNA-seq profiling for ten representative samples. Based on the resulting dataset, we devised and applied a bioinformatic method that links chromatin profiles to clinical annotations. Our analysis identified sample-specific variation on top of a shared core of CLL regulatory regions. IGHV mutation status – which distinguishes the two major subtypes of CLL – was accurately predicted by the chromatin profiles, and gene regulatory networks inferred for IGHV-mutated vs. IGHV-unmutated samples identified characteristic differences between these two disease subtypes. In summary, we discovered widespread heterogeneity in the chromatin landscape of CLL, established a community resource for studying epigenome deregulation in leukemia, and demonstrated the feasibility of chromatin accessibility mapping in cancer cohorts and clinical research.

  Dataset EGAD00001002110

• RNAseq of 76 samples from Uveal Melanoma tumors

  Hotspot mutations in the spliceosome gene SF3B1 are reported in 20% of uveal melanomas. SF3B1 is involved in 3'-splice site (3'ss) recognition during RNA splicing; however, the molecular mechanisms of its mutation have remained unclear. Here we show, using RNA-Seq analyses of uveal melanoma, that the SF3B1 R625/K666 mutation results in deregulated splicing at a subset of junctions, mostly by the use of alternative 3'ss.

  Dataset EGAD00001004398

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX021_SA854_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 3 samples; filetype=fastq

  Dataset EGAD00001005141

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX021_SA854_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 3 samples; filetype=fastq

  Dataset EGAD00001005142

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX021_SA854_003

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 3 samples; filetype=fastq

  Dataset EGAD00001005143

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX021_SA854_004

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 3 samples; filetype=fastq

  Dataset EGAD00001005144

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX023_SA604X9XB02413_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005145

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX023_SA604X9XB02413_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 24 samples; filetype=fastq

  Dataset EGAD00001005146

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX024_SA604X9XB02417_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005147

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX024_SA604X9XB02417_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005148

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX020_SA604X8XB02164_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 3 samples; filetype=fastq

  Dataset EGAD00001005149

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX019_SA604X7XB02089_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 36 samples; filetype=fastq

  Dataset EGAD00001005150

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX019_SA604X7XB02089_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 36 samples; filetype=fastq

  Dataset EGAD00001005151

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX019_SA604X7XB02089_003

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 24 samples; filetype=fastq

  Dataset EGAD00001005152

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX019_SA604X7XB02089_004

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 24 samples; filetype=fastq

  Dataset EGAD00001005153

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX_014_SA604X6XB01979_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 3 samples; filetype=fastq

  Dataset EGAD00001005154

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX_015_SA604X6XB01979_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 3 samples; filetype=fastq

  Dataset EGAD00001005155

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX018_VOA11019SA_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 24 samples; filetype=fastq

  Dataset EGAD00001005156

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX018_VOA11019SA_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 24 samples; filetype=fastq

  Dataset EGAD00001005157

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX026_VOA11083SD_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005158

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX003_SA605X3XB01966_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005159

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX003_SA605X3XB01966_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005160

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX004_SA605X3XB01966_003

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005161

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX004_SA605X3XB01966_004

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005162

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX006_PBC04106_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 3 samples; filetype=fastq

  Dataset EGAD00001005163

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX006_PBC04106_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 3 samples; filetype=fastq

  Dataset EGAD00001005164

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX038_VOA11267_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 3 samples; filetype=fastq

  Dataset EGAD00001005165

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX050_PBC04573_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005166