12214 results for "cancer rna-seq"

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• SCLC study George et al. - RNA-sequencing data set

  RNA-sequencing (RNA-seq) was performed with RNA extracted from fresh-frozen human tumor tissue samples. cDNA libraries were prepared from poly-A selected RNA applying the Illumina TruSeq protocol for mRNA. The libraries were then sequenced with a 2 x 100bp paired-end protocol to a minimum mean coverage of 30x of the annotated transcriptome.

  Dataset EGAD00001001244

• BCG-Flu Challenge Study Human RNA-seq

  Whole blood RNA sequencing data generated from human samples collected as part of the BCG-Flu Challenge study. The dataset includes 746 samples. Paired-end sequencing was performed on an Illumina NovaSeq 6000 platform with a 150 bp paired-end configuration. Raw FASTQ files are provided.

  Dataset EGAD50000002407

• 10x single-nucleus RNA-seq of postoperative human FCD II brain tissues

  This dataset contains 10x Genomics single-nucleus RNA sequencing data from postoperative brain tissues of patients with focal cortical dysplasia type II (FCD II). The samples were processed using the Chromium platform.

  Dataset EGAD50000001403

• GCP Challenges in Hepatology

  raw RNAseq data from blood plasma of patients diagnosed with liver disease. Total RNA libraries were prepared using the SMARTer Stranded Total RNA-Seq-Kit v3 - Pico Input Mammalian (Takara Bio). Libraries were paired-end sequenced (2x100) o a NovaSeq 6000 instrument using NovaSeq S2 or S1 kit (Illumina).

  Dataset EGAD50000000775

• COLONOMICS small RNA sequencing

  This dataset consists of SOLiD small RNA-seq of 250 colorectal samples: 100 tumor tissue samples, 100 normal tissue samples (adjacent to tumor sites) and 50 matched control samples of healthy individuals. CSfasta and qual files converted to single fastq files prior to uploading.

  Dataset EGAD00001004827

• Transcriptome (RNA-seq) data for the validation of the glioblastoma progression study (GBMatch).

  37 transcriptomes derived from fresh-frozen glioblastoma tumor samples. These transcriptomes have been produced for validation purposes and match the corresponding RRBS and WGS profiles in that DNA and RNA was extracted from the same tumor samples.

  Dataset EGAD00001004076

• Genomic (WGS) data for the validation of the glioblastoma progression study (GBMatch).

  43 low-coverage genomes derived from fresh-frozen glioblastoma tumor samples. These genomes have been produced for validation purposes and match the corresponding RRBS and RNA-seq profiles in that DNA and RNA was extracted from the same tumor samples.

  Dataset EGAD00001004077

• KNS42 and SF188 H3K36me3 chipSeq

  Chromatin immunoprecipitation (ChIP) was carried out employing antibodies against H3K36me3 and RNA polymerase II using the HistonePath and TranscriptionPath assays by ActiveMotif. Whole genome sequencing was carried out using an Illumina HiSeq2000 and data is provided as 6 BAM files. H3K36me3 chipseq RNA polymerase II chipseq and input coverage for each cell line.

  Dataset EGAD00001004119

• Breast_cancer_topographs

  Breast cancer topography will be explored using a combination of multi-region whole geome sequencing and in-situ RNA sequencing of fixed tissue specimens.

  Study EGAS00001003698

• The Finland-United States Investigation of NIDDM Genetics (FUSION) Tissue Biopsy Study

  The Finland-United States Investigation of NIDDM Genetics (FUSION) study is a long-term effort to identify genetic variants that predispose to type 2 diabetes (T2D) or that impact the variability of T2D-related quantitative traits (QTs). Most of the variants associated with T2D and related traits (glucose and insulin, anthropometrics, lipids) through genome-wide association studies (GWAS) occur in non-coding regions, suggesting a strong regulatory component to disease susceptibility. Regulatory element activity is often tissue-specific, which further complicates discovery of the causal/functional variation. Therefore, there is a critical need to identify the appropriate cell type, regulatory elements, target genes, and causal variants(s) in T2D-relevant tissues. We hypothesize that a subset of T2D and related variants alter gene expression regulation in skeletal muscle and adipose tissue - two major insulin target tissues and play key roles in insulin resistance. To that end, our study contains a comprehensive survey of genomics, epigenomics and transcriptomics in skeletal muscle and adipose tissue from individuals with glucose tolerance categories ranging from normal to T2D.For this FUSION Tissue Biopsy Study, we obtained RNA-Seq, microRNA (miRNA)-Seq, and DNA methylation (methyl)-Seq data on biopsy samples from 331 individuals from across the range of glucose tolerance: 124 normal glucose tolerance (NGT), 77 impaired glucose tolerance (IGT), 44 impaired fasting glucose (IFG), and 86 newly-diagnosed T2Ds. Participants completed two study visits, two weeks apart. First visits comprised most of the clinical phenotyping, including four-point OGTT (fasting, and 30, 60, and 120 minute post-load); BMI, WHR; lipids; blood pressure; and many other variables. Participants also completed FUSION health history, medication, and lifestyle questionnaires. On the second visit, we obtained ~250mg vastus lateralis skeletal muscle, ~750mg abdominal subcutaneous adipose, and a ~5x15mm section of abdominal skin. Visits were completed in March 2013. RNA isolation is ongoing in the Collins laboratory at the NIH, RNA and miRNA sequencing at the NIH Intramural Sequencing Center (NISC), and genotyping at the Center for Inherited Disease Research (CIDR). Individual-level data is available here for the 306 individuals who consented to data deposit. To focus on evaluation of gene expression and its regulation in skeletal muscle, we analyzed mRNA extracted from vastus lateralis skeletal muscle obtained from 271 of the 331 individual subjects from Finland, along with genome-wide genotypes. Individual-level data is available here for the 250 subjects who consented to the use of their data.Release phs001048.v2.p1 adds muscle data for an additional 42 subjects and data from adipose tissue for 276 subjects. Total RNA was isolated using Trizol extraction in the Collins laboratory at the NIH. The mRNA was poly-A selected, 24-plex libraries were generated using the Illumina TruSeq directional mRNA-seq library protocol and RNA sequencing was performed on HiSeq2000 sequencers using 101bp paired-end reads at NISC. miRNA libraries were prepared from total RNA from 296 muscle and 270 adipose samples, pooled and sequenced 50bp single-end reads on Illumina HiSeq2500. Data for 272 muscle and 251 adipose samples are available here for individuals with consent for data deposit. DNA was extracted from blood in the Collins laboratory, and genotyping on the Illumina Omni2.5M array was performed at CIDR. Genotypes were imputed using the HRC 2016 reference panel. In order to assess regions of open chromatin in skeletal muscle, we obtained muscle tissue from a commercial provider to perform ATAC-seq; these samples were sequenced at the University of Michigan DNA Sequencing Core.Release phs001048.v3.p1 adds single-nucleus (sn) RNA-seq and ATAC-seq data in 287 skeletal muscle samples out of the original 331 individuals. Individual-level data is available here for the 265 subjects who consented to the use of their data. The frozen tissue biopsy samples were processed in ten batches, each consisting of 40-41 samples. These batches were organized using a randomized block design to protect against experimental contrasts of interest including cohort, age, sex, BMI among others. Samples in each batch were pulverized, pooled together followed by nuclei isolation. The nuclei were processed on the 10X Genomics Chromium platform separately for snATAC-seq and snRNA-seq (v. 3.1 chemistry for snRNA-seq).Release phs001048.v4.p1 adds additional phenotypes and provides some corrections to several previous phenotypes.

  Study phs001048

• ChIP-seq in colorectal cancer and paired adjacent normal mucosa

  Chip-seq samples for 20 colorectal patients with paired adjacent normal mucosa to characterize H3K27ac and H3K4me1.

  Study EGAS00001005303

• Oesophageal_Adenocarcinoma_Organoids_Iso_Seq

  RNA Sequencing of 5 patient derived organoid cell models. Each model was derived from a piece of patient tumour taken following surgical rescetion of the tumour. All model derivations took place with the CGaP facility in Sanger. This PacBio RNA data will be combined with other sequencing data in order to generate accurate reference cancer genomes and study how structural variants affect gene expression

  Study EGAS00001004051

• Characterizing the cell-free transcriptome in a humanized DLBCL patient-derived tumor xenograft model for RNA-based liquid biopsy in a preclinical setting

  This study explores the cell-free transcriptome in a humanized DLBCL patient-derived tumor xenograft (PDTX) model. Blood plasma samples (n=171) derived from a DLBCL PDTX model including 27 humanized (HIS) PDTX, 8 HIS non-PDTX and 21 non-HIS PDTX NOD-scid IL2Rgnull mice were collected during humanization, xenografting, treatment, and sacrifice. The mice were treated with either R-CHOP, huCD20-Fc-AFN-CHOP, or phosphate-buffered saline (PBS). RNA was extracted using the miRNeasy serum/plasma kit and sequenced on the NovaSeq 6000 platform using the SMARTer Stranded Total RNA-seq pico v3 kit.

  Study EGAS50000000566

• Single-cell RNA sequencing of human IL-18R supported CAR T cells targeting oncofetal Tenascin C

  scRNA-seq raw data

  Dataset EGAD50000001134

• Time course acetalax bisacodyl treatment

  RNA-Seq raw data of PDX treated with acetalaxor bisacodyl for 4h00 to 24h00.

  Dataset EGAD50000000875

• Recurrent somatic mutations in POLR2A define a distinct subset of meningiomas: RNAseq variants

  Variants called from RNA-seq data of meningioma tumors.

  Dataset EGAD00001002649

• RNA-Seq of human stimulated and cultured CD4+ Treg cells

  This dataset includes whole transcriptome data of human stimulated and cultured CD4+ Treg cells (39 samples).

  Dataset EGAD00001005964

• Follicular T cell lymphoma

  Paired-end RNA-seq of follicular T cell lymphoma for the discovery of fusion transcripts

  Dataset EGAD00001006379

• The Effect of the Menstrual Cycle on DNA Expression in the Normal Human Breast Epithelium

  The Susan G. Komen for the Cure® Tissue Bank at the IU Simon Cancer Center [www.komentissuebank.iu.edu] (KTB) was established expressly for the prospective collection of normal, healthy breast tissue from volunteer donors. Blood is also obtained from donors at the time of donation and is processed for serum, plasma and peripheral blood leukocyte DNA. Specimens are annotated and data includes age, race, ethnicity, personal health history, family cancer history, medication usage at the time of donation, and breast cancer risk factors. Premenopausal donors to the KTB were identified by a query of the Bank's database. Hematoxylin and eosin stained sections of the formalin-fixed paraffin-embedded tissue of the identified donors were reviewed and tissue was graded on the basis of the abundance of epithelium within the section. Only tissue containing abundant epithelium was considered for this study. Based on dates, the specimens of nine women in the follicular phase of the menstrual cycle and five in the luteal phase were chosen. Six donors using hormonal contraception at the time of donation were also included. Whole blood obtained from 19 of the 20 donors at the time of tissue donation was available and it was processed for serum. Estradiol, estriol, luteinizing hormone and progesterone concentrations were determined by the Indiana University Health Pathology Laboratory using a Beckman Unicel DxI 800 Immunoassay System. The phase of the menstrual cycle was verified by serum progesterone concentration. The epithelium of these 20 specimens was microdissected from multiple 8 micron frozen tissue sections. Total RNA extracted from the tissue was subsequently depleted of rRNA via locked nucleic acid probes. This enabled profiling of both poly-A and non-poly-A RNA species. Barcoded cDNA libraries from the 20 normal breast epithelia were prepared and sequenced on an Applied Biosystems (AB) SOLiD3 or SOLiD 4 platform. RNA-seq reads for each sample were then mapped to the human genome (hg19) using the LifeScope software version 2.5.1 (Life Technologies, Foster City, CA) and BAM (Binary Alignment/Map) files generated. Read counts for each gene were derived from the output BAM files using the RefSeq database (UCSC Genome Brower) as the gene model.

  Study phs000644

• Genomic and epigenomic study of Japanese renal cell carcinoma including WGS, RNA-seq, ATAC-seq, and methyl-seq

  We performed whole-genomic and transcriptomic sequencing of more than 100 Japanese renal cell carcinoma (RCC) cases, including clear cell RCC, papillary RCC, chromophobe RCC, and TFE3-translocated RCC. In addition, we conducted epigenome sequencing analyses: the assay for transposase-accessible chromatin sequencing (ATAC-seq) and enzymatic methyl sequencing.

  Study EGAS00001006919

• MIBC NAC2020 cohort RNA sequencing

  The dataset contains RNA sequencing data from N=48 transurethral resections of bladder tumours (TURBTs) from N=48 patients with muscle-invasive bladder cancer. All TURBTs originate from formalin-fixed paraffin embedded tissue. We used the Illumina TruSeq RNA exome kit, previously known as the TruSeq RNA Access Library Prep Kit. This kit converts total RNA into template molecules of known strand origin, followed by sequence-specific capture of coding RNA. All samples were run in an Illumina NovaSeq6000 instrument. Paired FASTQ files from all 48 patients are provided.

  Study EGAS50000000741

• Amplicon sequencing of long non-coding RNA associated with gastritis and gastric carcinogenesis

  This study aimed to identify dysregulations of long non-coding RNA (lncRNA) in gastric cancer, and to reveal molecular functions of lncRNAs associated with gastritis and gastric carcinogenesis. We also aimed to reveal the correlation between clinicopathological characteristics and lncRNA alterations. To this end, we will try to develop predictive markers of gastric cancer risk, which enables prevention and early detection of gastric cancer. We will also try to develop molecular markers which enable us to select treatment strategies for gastric cancer.

  Study JGAS000353

• Ribosomal Depleted Total RNA-Seq of PBMCs and Skin from Controls and Systemic Sclerosis Patients

  This study involved prospective collection of skin biopsies and peripheral blood mononuclear cell (PBMC) samples from controls with no self-reported history of autoimmune or inflammatory disease and cases with Rheumatologist-confirmed systemic sclerosis: limited cutaneous systemic sclerosis (lcSSc), diffuse cutaneous systemic sclerosis (dcSSc), very early diagnosis of systemic sclerosis (VEDOSS), and systemic sclerosis sine scleroderma (SSS). Some SSc cases were sampled at a 6 month routine follow-up visit. PBMCs were collected and lysed immediately. Skin punches were stabilized in RNAlater until extraction. All RNA-Seq libraries were created using Takara/Clontech ribosomal depletion kits, and sequenced on either a HiSeq2500 or HiSeq3000.

  Study phs002902

• BLUEPRINT RNA-seq data for common cells in the haematopoietic lineages, from adult and cord blood samples.

  RNA-seq data for common cells in the haematopoietic lineages, from adult and cord blood samples.

  Study EGAS00001000327

• Additional RNAseq data of metastatic breast cancer samples

  Paired-end RNA sequencing data from 33 metastatic breast cancer samples. Sequencing was performed on the Illumina NovSeq 6000 using NEBNext Single Cell and Low Input RNA Library Prep Kit for Illumina.

  Dataset EGAD00001015678