Search Results - EGA European Genome-Phenome Archive

Melanoma RNA Seq Data commitee

Dac EGAC00001002928

Single-nuclei RNA-sequencing (snRNA-seq) from subcortical white matter controls and MS lesions, specifically chronic active (CA) and chronic inactive (CI), that paired with the spatial transcriptomics from the same samples, was used to identify spatial niches and key cell interactions driving inflammation and disease progression.

Study EGAS50000000354

Single-nucleus RNA sequencing (snRNA-seq) of seven human diffuse midline glioma (DMG) patient tumour samples.

This dataset comprises 7 paired (14 total) FASTQ files of single-nucleus RNA sequencing (snRNA-seq) data generated from seven human diffuse midline glioma (DMG) patient tumour samples. snRNA-seq libraries were generated using the 10X Chromium Controller and Chromium Next GEM Single Cell 3’ kit version 3.1 in line with the manufacturer’s instructions. Generated libraries were sequenced on an Illumina NextSeq 2000 (P3 XLEAP-SBS chemistry) at targeted 20,000 reads per nucleus.

Dataset EGAD50000002514

Single-cell RNA-seq data of bronchoalveolar lavage fluid and extramedullary relapse of a multiple myeloma patient with sarcoidosis-like reactions after anti-BCMA CAR T-cell therapy

We performed single-cell RNA-sequencing (scRNA-seq) of cells in the bronchoalveolar lavage (BAL) fluid at 3-month follow-up of a multiple myeloma patient experiencing sarcoidosis-like pulmonary reactions after anti-BCMA CAR T-cell therapy (Sample alias: A8_3, A9_3; technical replicates). In addition we performed scRNA-seq of a extramedullary relapse lesion at 6-month follow-up (Sample alias: B10_3).

Dataset EGAD00001008649

Uncovering RNA Signatures of C9orf72-Linked ALS and Related Disorders

Substantial clinical and pathological variability has been reported in patients carrying an expanded repeat in C9orf72, who are generally diagnosed with amyotrophic lateral sclerosis (ALS) and/or frontotemporal dementia (FTD). Emerging evidence suggests that C9orf72 expression, RNA foci, and dipeptide-repeat proteins contribute to C9orf72-related diseases; however, the majority of the clinicopathological variability remains unexplained. We hypothesize that RNA sequencing (RNA-Seq) might reveal individual genes or groups of highly correlated genes (modules) that could account for this variability, which may help to identify much-needed druggable targets and/or biomarkers. Our preliminary studies performed in the frontal cortex, where we compared C9orf72 expansion carriers to (disease) controls, demonstrated that the top differentially expressed gene was C9orf72 itself. We also noticed that differentially expressed genes were enriched for the endocytosis pathway, which is consistent with the reported function of the C9orf72 protein in vesicle trafficking. Furthermore, we detected a module enriched for vesicular pathways, and additionally, we discovered an association with survival after onset for several promising candidates involved in vesicular transport. To find new therapeutic targets and biomarkers, here we have completed RNA-Seq on an increased number of samples to examine another relevant region: the cerebellum. As such, we performed RNA-Seq on a well-characterized cohort of C9orf72 expansion carriers, patients without this expansion, and control subjects without neurological diseases. We used multivariable linear regression models for gene-level analysis, weighted correlation network analysis for module-level analysis, and leafcutter for splicing analysis. Using the cerebellar RNA-Seq data, we found a large number (>6,000) of differentially expressed genes, with a notable increase in expression of homeobox genes in C9orf72 expansion carriers, as well as many gene modules that were associated with C9orf72 expansion status. Additionally, using leafcutter, we detected over 1,000 differential splicing events and an increase in the number of cryptic splicing events in C9orf72 expansion carriers.

Study phs003065

Data Access Committee for the DNA sequencing data included in the study "Multifocal cohort analysis unveils cell types associated with regional lymph node seeding in prostate cancer".

A data transfer agreement (DTA), based on the example DTA provided by UZ Gent, is to be filled out by the requester and Multifocal RNA-seq and tNGS data from primary and metastatic tissues of locally advanced and de novo metastatic cohorts - Data Access Committee. https://www.uzgent.be/nl/over-uz-gent/organisatie/data-access-comite/wat-zijn-de-opdrachten-van-het-data-access-comite Coordinator: Muriel Fouquet E-mail: dataaccesscommittee@uzgent.be

Dac EGAC50000000930

Comprehensive single cell study of lung adenocarcinoma from early to metastatic stages

We performed single cell RNA sequencing (scRNA-seq) for 208,506 cells derived from 58 lung adenocarcinomas from 44 patients, which covers primary tumour, lymph node and brain metastases, and pleural effusion in addition to normal lung tissues and lymph nodes. The extensive single cell profiles depicted a complex cellular atlas and dynamics during lung adenocarcinoma progression which includes cancer, stromal, and immune cells in the surrounding tumor microenvironments.

Dataset EGAD00001005054

Translation of non-canonical open reading frames as a cancer cell survival mechanism in childhood medulloblastoma - Ribo-Seq

This study aims to investigate the dysregulation of RNA translation and identify functional non-canonical open reading frames (ORFs) as potential targets for medulloblastoma treatment. The study involves ribosome profiling and RNAseq of medulloblastoma tissues and cell lines to observe the translation of non-canonical ORFs. Multiple CRISPR-Cas9 screens will be used to identify functional non-canonical ORFs implicated in medulloblastoma cell survival.

Dataset EGAD00001011193

Exploration of neuroblastoma xenograft models for tumor extracellular RNA profiling in murine blood plasma

Total RNA sequencing (SMARTer Stranded Total RNA-Seq Kit v2) data of extracellular RNA (exRNA) from liquid biopsies of neuroblastoma xenograft models.

Dataset EGAD00001010905

T-ALL RNA-Seq raw data files

The data set consists of unprocessed RNA-Seq data from 225 patients diagnosed with T cell acute lymphoblastic leukemia in fastq file format. Samples from bone marrow or peripheral blood were subjected to mRNA library prep using Poly-A selection and sequencing on a NovaSeq 6000 system yielding approximately 30 million reads per sample.

Dataset EGAD50000000308

Immunotesting cohort with RNA-seq data of melanoma samples

This dataset contains RNA-seq raw data in fastq format from 9 melanoma samples. The samples are formalin-fixed paraffin-embedded (FFPE) treated. For target enrichment SureSelect XT Human All Exon V6 was used. The libraries were sequenced in paired-end mode (2 x 50 nt) on a NovaSeq6000 S2 flow cell.

Dataset EGAD00001006783

Integrative multi-omic analyses of malignant pleural mesothelioma

Multi-omic data (whole-genome sequencing, RNA-seq, EPIC 850K methylation arrays) for 123 samples from the MESOMICS project, the French project of molecular characterization of malignant pleural mesothelioma

Study EGAS00001004812

Chromatin landscape of medulloblastoma reveals context dependent driver

In this study, we defined subgroup specific chromatin landscape (H3K27ac, H3K27me3, RNA-Seq, 27ac hichip, WGS) of medulloblastoma to identify pathogenic epigenetic alterations that regulate expression of a context dependent driver gene.

Study EGAS00001006741

BLUEPRINT release August 2016, RNA-Seq for macrophage - T=6days LPS, on genome GRCh38

RNA-Seq data for 4 macrophage - T=6days LPS sample(s). 4 run(s), 4 experiment(s), 4 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 EGAD00001002337

BLUEPRINT release August 2016, RNA-Seq for macrophage - T=6days untreated, on genome GRCh38

RNA-Seq data for 4 macrophage - T=6days untreated sample(s). 4 run(s), 4 experiment(s), 4 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 EGAD00001002457

BLUEPRINT release August 2016, RNA-Seq for macrophage - T=6days B-glucan, on genome GRCh38

RNA-Seq data for 4 macrophage - T=6days B-glucan sample(s). 4 run(s), 4 experiment(s), 4 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 EGAD00001002522

He et al. RNA-seq data

This dataset are the bam files of RNA-seq data from the paper by He et al.

Dataset EGAD00001007135

RNA-Seq data for manuscript titled: Multi-omic features of oesophageal adenocarcinoma in patients treated with preoperative neoadjuvant therapy

Dataset EGAD00001008656

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

RNA-sequencing on neuroblastoma PDX model COG-N-519 treated with control miR-1283 and test miR-99b-5p mimics. Three samples from each of the treatment condition were analysed. Next-Seq platform was used for sequencing.

Dataset EGAD00001008035

Intellance-2: rRNA-minus RNA-seq

Dataset EGAD00001007943

single-cell RNA-Seq samples of CRC patients

The dataset contains samples of 11 CRC patients (2 samples for each patient, tumor and normal adjacent tissue site, 22 samples in total). Dataset is composed by fastq file (paired end) type from 10x single-cell RNA-Seq.

Dataset EGAD00001009634

Single-cell RNA-seq of matched pediatric AML tumors

Single-cell RNA-seq of pediatric AML tumours from patients enrolled in the clinical trial AAML1031. Obtained using the 10X Chromium Single Cell 3’ Reagent Kit, v3.0. A total of 75 samples were obtained from biopsies at diagnosis, remission and relapse from 28 patients.

Dataset EGAD00001011195

RNA-seq dataset of Neoantigen Peptides derived from V(D)J-recombined Immunoglobulins Drive Outgrowth of Cytolytic CD8+ T-cells

Dataset EGAD00001015647

High-coverage whole exome sequence in non-TRU-type lung adenocarcinomas

In order to elucidate the key genetic events in non-TRU-type lung cancer, we selected 43 non-TRU-type lung adenocarcinomas and performed a whole exome sequence and RNA-seq analysis using a next-generation sequencer. The results of the analysis identified mutations in TP53, KRAS and NKX2-1 as the top three significantly mutated genes, while the EGFR mutation was rare in this cohort. Eight NKX2-1 mutations (5 frameshift, 2 nonsense, and one missense) were identified, with one case harboring two distinct NKX2-1 mutations (missense and frameshift). All NKX2-1 mutants were transcriptionally inactive in reporter assays. Histologically, invasive mucinous adenocarcinomas accounted for most of the NKX2-1 mutations (5 cases), while 1 enteric and 1 acinar adenocarcinoma harbored the NKX2-1 mutation.

Study JGAS000105

RNA-Seq data from tumor samples collected from 12 UTSW translocation renal cell carcinoma (tRCC) patients.

This study investigates differentially expressed genes associated with the progression of translocation renal cell carcinoma (tRCC) by analyzing RNA-Seq data from 23 tumor samples obtained from 12 patients. The samples were collected from affiliated hospitals of the University of Texas Southwestern Medical Center (UTSW), including Parkland Hospital and Children’s Medical Center. RNA isolated from tumor samples was sequenced using the Illumina platform.

Dataset EGAD50000000172

RNA-seq data

This dataset contains 200 RNA-seq bam files (142 SLE, 58 healthy individuals). RNA libraries were prepared with the Illumina TruSeq sample preparation kit and were sequenced on Illumina HiSeq2000. 49 bp paired-end reads were mapped to the GRCh37 reference human genome using the GEM mapper.This dataset was generated as part of the following study: Panousis et al (2019). Combined genetic and transcriptome analysis of patients with SLE: Distinct, targetable signatures for susceptibility and severity

Dataset EGAD00001005037

fibroblast RNAseq from a GINS3 patient and two parents

RNA-seq was performed from 3 separate GINS3 patient fibroblast cultures and 1 replicate of fibroblasts derived from each of the two parents. RNA-seq libraries were generated with NEBNext Ultra II Directional RNA library prep for Illumina with NEBNext Poly(A) mRNA Magnetic Isolation Module (New England Biolabs) and sequenced on Illumina NextSeq500 with paired-end 150 bp read length. SIRV Set 3 (Lexogen) spike-ins were added. Two fastq files are provided for each RNAseq sample.

Dataset EGAD00001008571

WGS and RNA-Seq data of 2 additional patients of newly diagnosed multiple myeloma (NDMM)

For WGS DNA of tumor or control samples was prepared for paired sequencing using the Illumina TruSeq DNA Nano Kit and sequenced on NovaSeq 6000. For RNA-Seq the sequencing Kit Illumina TruSeq stranded mRNA was used with the same sequencer. There are 4 samples for WGS (18 runs) and 4 samples for RNA (4 runs) available.

Dataset EGAD00001009627

RNA-seq study of human long-term and short-term hematopoietic stem cells from umblical cord blood with lentiviral overexpression of S1PR3

To investigate the molecular and biological pathways altered by S1PR3OE in human hematopoietic stem cells (HSC), we performed RNA-sequencing (RNA-seq) of LT- and ST-HSC 3 days after transduction with control or S1PR3 overexpression (OE) lentiviral vectors. LT-HSC and ST-HSC from 3 pool of CB lin- were FACS-purified, cells were prestimulated for 4 hours and transduced with lentiviral vectors. At day 3, 2000-5300 BFP+ cells were FACS-purified for RNA isolation with a PicoPure kit. We were able to isolate only 1600-1800 BFP+ cells from LT-HSC control samples as opposed to 4000-5400 BFP+ cells from S1PR3OE samples. Thus, we pooled all control BFP+ LT-HSC cells into one sample for RNA-seq analysis. BFP- LT-HSC from control vector transduction were purified from CB1 as an additional LT-HSC control. Nextera libraries generated from 10 ng RNA from 5 LT-HSC samples (2 controls, 3 S1PR3OE) and 6 ST-HSC samples (3 controls, 3 S1PR3OE) were subjected to 125 bp, paired-end RNA-sequencing on the Illumina HiSeq 2500 with an average of 50 million reads/sample at the Center for Applied Genomics, Sick Kids Hospital.

Dataset EGAD00001006582

Single Cell Analysis of Pulmonary Fibrosis

Pulmonary fibrosis is a heterogenous syndrome in which fibrotic scar replaces normal lung tissue. We performed massively parallel single-cell RNA-Seq on lung tissue from eight lung transplant donors and eight patients with pulmonary fibrosis. Combined with in situ RNA hybridization, with amplification, these data provide a molecular atlas of disease pathobiology. We identified a distinct, novel population of profibrotic alveolar macrophages exclusively in patients with fibrosis. Within epithelial cells, the expression of genes involved in Wnt secretion and response was restricted to non-overlapping cells. We identified rare cell populations including airway stem cells and senescent cells emerging during pulmonary fibrosis. Analysis of a cryobiopsy specimen from a patient with early disease supports the clinical application of single-cell RNA-Seq to develop personalized approaches to therapy.

Study phs001750

Comprehensive Transcriptional Analysis of Early Stage Urothelial Carcinoma using whole transcriptome sequencing

The expression profile and sequence variants of 476 early stage urothelial carcinoma were studied using whole transcriptome sequencing. RNA-Seq libraries were prepared by Ribo-Zero treatment of total-RNA followed by library preparation using ScriptSeq (both Epicentre/Illumina). RNA-Seq libraries were paired-end sequenced (2x 101 bp) on Illumina HiSeq 2000 and the resulting fastq files were processed using tools from the Genome Analysis Toolkit (GATK and from the Tuxedo suite. Access to the sequence data (mapped and un-mapped bam and vcf files), containing person identifying information, needs signature on a controlled access form, and can be accessed at The European Genome-phenome Archive (EGA) following request. An expression matrice of FPKM values are available without restriction at ArrayExpress (E-MTAB-4321).

Study EGAS00001001236

RNA sequencing dataset of mesothelioma MIST4 study

This dataset includes BAM files from RNA-seq of 20 tumor samples.

Dataset EGAD50000002634

Epigenomes and Transcriptomes of Brain Samples of Schizophrenics and Controls

We examined the effects of antipsychotic medications on the cell-specific epigenomics and transcriptomics in the frontal cortex of schizophrenic subjects. We performed ChIP-seq (H3K4me3 and H3K27ac) and RNA-seq on neuronal and non-neuronal nuclei of postmortem frontal cortex samples from two cohorts of schizophrenics, either previously treated or not with antipsychotic medications, and control subjects individually matched by sex and age. In total, we tested 29 schizophrenics (15 untreated and 14 treated patients) and their matched control samples. Two replicates were produced on each brain sample for each assay. ChIP-seq data were generated using MOWChIP-seq (Zhu et al., PMID: 31666743) and RNA-seq data were produced using the combination of SMART-seq2 (Picelli et al., PMID: 24385147) and a Nextera XT DNA library preparation kit. The filename contains the information on the experimental group, the number of the sample within the group, the type of the brain nuclei, the epigenomic/transcriptomic data set (either H3K27ac or mRNA), and the number of replicate. For example, “SCZ-1-untreated-neuron-H3K4me3-R1” refers untreated schizophrenic sample #1, replicate 1 ChIP-seq data on H3K4me3.

Study phs002487

Human and rat skeletal muscle multi-omic profiling

Skeletal muscle accounts for the largest proportion of human body mass, on average, and is a key tissue in complex diseases and mobility. It is composed of several different cell and muscle fiber types. Here, we optimize single-nucleus ATAC-seq (snATAC-seq) to map skeletal muscle cell-specific chromatin accessibility landscapes in frozen human and rat samples, and single-nucleus RNA-seq (snRNA-seq) to map cell-specific transcriptomes in human. We additionally perform multi-omics profiling (gene expression and chromatin accessibility) on human and rat muscle samples.

Study EGAS00001005730

Enhanced cortical neural stem cell identity through SMAD/WNT inhibition in human cerebral organoids facilitates emergence of outer radial glial cells

For scRNA-Seq, single live cells were suspended in 0.4% BSA in DPBS buffer (1000 cells/µL) and subjected for GEM generation and barcoding. Library preparation was performed according to the recommended procedures of the manufacture Chromium Single Cell 3’ reagent Kit V3.1 chemistry. 10,000 cells were targeted for capturing and 9 cycles were used for cDNA amplification, while 12 cycles were performed for library formation, and sequencing was performed on an Illumina NovaSeq 6000 sequencer. For bulk RNA-Seq, RNA was purified using the miRNeasy™ RNA MiniPrep (Qiagene) and RNA-seq libraries were generated either using the Illumina TruSeq RNA Library Preparation Kits and sequenced on the Illumina HiSeq 2500 sequencer as 76 bp paired-end reads, or using the NEBnext UltraDirectional RNA Library Preparation Kits after rRNA depletion using the NEBNext rRNA depletion kit and sequenced on an Illumina HiSeq 2500 sequencer using 50 cycles of single-end sequencing.

Dataset EGAD00001008609

Single-cell omics data for COVID-19 patients

Single-cell RNA-seq, single-cell ATAC-seq, and genotypes used in the analysis for the study "Altered and allele-specific open chromatin landscape reveal epigenetic and genetic regulators of innate immunity in COVID-19". The RNA-seq and ATAC-seq are raw data in FASTQ format while the genotypes are in the VCF format which was filtered and imputed (more details are available in the main text of the study).

Dataset EGAD00001009331

Single cell RNA-seq, TCR-seq and bulk TCR-seq on HNSCC patients treated with ICB

We performed single cell RNA- and TCR-sequencing (10x Genomics) on immune infiltrates (CD45+ cells) from 18 HNSCC patients enrolled in the IMCISION trial (Vos et al. 2021). Viable immune cells were isolated from pre-treatment and post-treatment primary tumor biopsies of 10 patients responding (1 partial pathological response and 9 major pathological responses) and 7 patients non-responding to anti-PD-1 and anti-CTLA4 combination immunotherapy. One patient treated with anti-PD-1 monotherapy (1 major pathological response) was included in the dataset. Bulk TCR-seq was performed on the PBMCs of responding patients, pre- and post-treatment.

Dataset EGAD00001011311

MDS-HSC-RNA-SEQ

Dac EGAC00001000185

utero-tubal lavage RNA seq DAC

Dac EGAC00001002241

GLASS-NL RNA-seq Data access committee

Dac EGAC00001003470

Multi-Omic Investigation of Beckwith-Wiedemann Syndrome Hepatoblastoma

Hepatoblastoma (HB) is the most common malignant liver tumor diagnosed in children under 5 years of age. One of the most common HB predisposition syndromes is Beckwith-Wiedemann Syndrome (BWS, OMIM 130650), which affects approximately 1/10,000 live births. In this study, we perform Whole Exome Sequencing (WES), DNA methylation array, messenger RNA-Sequencing (mRNA-Seq), and microRNA-Sequencing (miRNA-Seq) to examine the genomic, methylomic, and transcriptomic signature of BWS HB. We analyzed five tumor-normal paired samples, two BWS tumor only samples, and five non-BWS control samples to identify a predisposition and oncogenic signature of BWS HB development. To further understand the new impact of 11p15 changes, specifically in the liver, we performed single-nucleus RNA sequencing (snRNA-seq) and single-nucleus assay for transposase-accessible chromatin with sequencing (snATAC-seq) to generate paired, cell-type-specific transcriptional and chromatin accessibility profiles of both BWS-liver and nonBWS-liver nontumorous and tumor tissues.

Study phs002614

Uncovering Gene Regulatory Differences between Human and Chimpanzee Neural Cells

A major challenge in human evolutionary biology is to pinpoint the genetic differences that underlie phenotypic changes in the human lineage, such as increased neuron number and a prolonged period of neuronal maturation. Here, we used human-chimpanzee tetraploid cells to distinguish changes in gene expression due to cis-acting sequence variants that change local gene regulation, from trans expression changes due to species differences in the cellular environment, in neural progenitor cells and excitatory neurons using RNA-seq and ATAC-seq. Using a CRISPR inhibition screen with scRNA-seq, transcription factor motif analyses with CUT&Tag, and downstream single-locus studies with RNA-seq, we further characterized cis-acting gene regulatory differences, including changes to FOS, TNIK, FOSL2, and MAZ, that influence neurogenesis and neuronal maturation. This study identifies specific genomic changes that may contribute to human neural specializations and provides a general framework for understanding genetic differences that underlie human traits.

Study phs004053

Benchmarking V(D)J Repertoire Reconstruction: Bulk RNA-Seq vs PCR-Based RepSeq Validated by SMRT Sequencing

The aim of this study is to benchmark methods for immunoglobulin repertoire profiling using human B-cell samples. We compare targeted VDJ mRNA sequencing and repertoire reconstruction from bulk RNA-seq data to PCR-independent full-length transcript sequencing using Single-Molecule Real-Time technology. The objective is to assess methodological biases and establish a robust reference framework for immunoglobulin repertoire analysis.

Study EGAS50000001541

RNA-seq analysis of megakaryocytes and granulocytes in Quebec platelet disorder

Quebec Platelet disorder (QPD) is a unique bleeding disorder that markedly increases urokinase plasminogen activator (uPA) in megakaryocytes and platelets but not in plasma or urine. The cause is tandem duplication of a 77 kb region of chromosome 10 containing PLAU and C10orf55. Blood cells and cultured megakaryocytes from donors (7 QPD, 10 control subjects) were prepared for total and allele-specific, quantitative reverse transcription polymerase chain reaction, immunoassays, Western blots and RNA-seq. Transcriptomes for cultured megakaryocytes and peripheral blood granulocytes from 4 control and 3 QPD individuals were analyzed using mRNA-seq.

Study EGAS00001001840

Genentech gastric tumor sequencing

Exome-seq, RNA-Seq, SNP array profiling of gastric tumor samples.

Dataset EGAD00001000815

Genomic Analysis of Relapsed/Refractory DLBCL

Molecular phenotyping techniques have established a landscape of genomic variants in diagnostic Diffuse Large B Cell Lymphoma (DLBCL), however these have not yet been applied in large scale studies of relapsed/refractory DLBCL resulting in incomplete characterization of mechanisms driving tumor progression and treatment resistance. Here, we performed an integrated multiomic analysis on relapsed/refractory DLBCL samples. Tumors from 87 relapsed/refractory DLBCL patients were included in this study and were available for data deposition [Tumor whole exome sequencing (WES): n=75, Germline WES: n=73, RNA sequencing (RNA-Seq): n=72]. Tumor DNA was extracted from formalin-fixed, paraffin embedded (FFPE) tissue sections, germline DNA was extracted from blood, and WES of all samples was performed using the Agilent SureSelect XT All Exon v6 kit and sequencing was carried out on an Illumina NovaSeq, 100 x 2 paired end reads. Tumor RNA was extracted from FFPE tissue sections and RNA-Seq was performed using the Illumina TruSeq RNA Exome Kit (Illumina) for library preparation, sequencing platform HiSeq 4000, 100 x 2 paired end reads.

Study phs003868

Circulating RNAs prior to endometrial cancer diagnosis

We analyzed circulating RNA levels using small RNA sequencing, targeting RNA in the size range 17 to 47 nucleotides, in samples collected prior to endometrial cancer diagnosis compared to cancer-free controls. The analysis included 316 cases with samples collected 1-11 years prior to diagnosis , and 316 matched controls, both from the Janus Serum Bank Cohort in Norway.

Study EGAS50000000267

RNAseq on 20 samples of multiple myeloma patients and 3 normal plasma cells.

RNAseq was performed using 200 ng of total RNA by GATC Biotech. Directional libraries were performed after mRNA selection by polyA selection using UTP method. RNA-seq libraries were sequenced on HiSeq2500 Illumina machine using 100bp paired-end reads. Reads alignment was performed using the STAR aligner (version 2.4.0f1) and human genome hg19 as reference.

Study EGAS00001004347

12300 results for "cancer rna-seq"

in 140.04 milliseconds.

DS-ALL RNA-Seq DAC