15128 results for "cancer studies using rna-seq"

in 29.12 milliseconds.

• BLUEPRINT release January 2015, ChIP-Seq for macrophage

  ChIP-Seq data for 13 macrophage sample(s). 55 run(s), 55 experiment(s), 55 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001001196

• BLUEPRINT release August 2015, Bisulfite-Seq for cytotoxic CD56-dim natural killer cell, on genome GRCh38

  Bisulfite-Seq data for 2 cytotoxic CD56-dim natural killer cell sample(s). 24 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820

  Dataset EGAD00001001473

• BLUEPRINT release August 2015, ChIP-Seq for neutrophilic metamyelocyte, on genome GRCh38

  ChIP-Seq data for 4 neutrophilic metamyelocyte sample(s). 18 run(s), 12 experiment(s), 12 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001495

• BLUEPRINT release August 2015, ChIP-Seq for Multiple myeloma, on genome GRCh38

  ChIP-Seq data for 2 Multiple myeloma sample(s). 16 run(s), 14 experiment(s), 14 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001592

• BLUEPRINT release August 2016, ChIP-Seq for Acute Promyelocytic Leukemia - MC2884 (4h), on genome GRCh38

  ChIP-Seq data for 1 Acute Promyelocytic Leukemia - MC2884 (4h) sample(s). 6 run(s), 6 experiment(s), 6 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002372

• BLUEPRINT release August 2016, ChIP-Seq for Chronic Lymphocytic Leukemia, on genome GRCh38

  ChIP-Seq data for 106 Chronic Lymphocytic Leukemia sample(s). 174 run(s), 163 experiment(s), 162 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002384

• BLUEPRINT release August 2016, ChIP-Seq for Mantle Cell Lymphoma, on genome GRCh38

  ChIP-Seq data for 5 Mantle Cell Lymphoma sample(s). 35 run(s), 35 experiment(s), 35 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002397

• BLUEPRINT release August 2016, ChIP-Seq for monocyte - RPMI_BG_T=24hrs, on genome GRCh38

  ChIP-Seq data for 3 monocyte - RPMI_BG_T=24hrs sample(s). 8 run(s), 8 experiment(s), 8 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002408

• BLUEPRINT release August 2016, ChIP-Seq for Acute Promyelocytic Leukemia - MC3324, on genome GRCh38

  ChIP-Seq data for 1 Acute Promyelocytic Leukemia - MC3324 sample(s). 2 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002431

• BLUEPRINT release August 2016, ChIP-Seq for neutrophilic metamyelocyte, on genome GRCh38

  ChIP-Seq data for 4 neutrophilic metamyelocyte sample(s). 32 run(s), 23 experiment(s), 23 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002435

• BLUEPRINT release August 2016, ChIP-Seq for mature eosinophil, on genome GRCh38

  ChIP-Seq data for 2 mature eosinophil sample(s). 14 run(s), 14 experiment(s), 14 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_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002477

• Bulk ATAC-Seq HiSeq2500 v4 reagents (100M reads)

  Human data for chromatin accessibility (ATAC-Seq) in eight B-cell precursors: HSC, CLP, pro-B, pre-B, Immature B, Transitional B, Naive B CD5-, Naive B CD5+ cells

  Dataset EGAD00001010909

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

  Bisulfite-Seq data for 4 CD38-negative naive B cell sample(s). 51 run(s), 5 experiment(s), 8 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_bisulphite_analysis_CNAG_20160816

  Dataset EGAD00001002520

• mRNA-seq of in vitro differentiation from induced pluripotent stem cells to hepatocyte-like cells

  Fastq files of mRNA-seq data of induced pluripotent stem cells (iPSC), definitive endoderm (DE) and hepatocyte-like cells (HLC). The dataset comprises data from the in vitro differentiation protocol Cellartis (Takara Bio, "CEL", n = 4) and several interventions (11x3 replicates).

  Dataset EGAD00001005935

• RNA bulk sequencing on organoids from different organs with or without TS2/16 antibody

  RNA bulk sequencing on organoids from colon, ileum, jejunum, duodenum and pancreas duct with or without TS2/16 antibody. Also there is difference in extracellular matrix used, BME vs Colagen.

  Dataset EGAD50000001606

• RNA sequencing of Human Organoid Lines

  The study will use RNA sequencing to aid in benchmarking different culture conditions in a set of genetically annotated human organoid lines. The data will be used to assess whether there are any clonal differences introduced when culturing these lines in different conditions.

  Dataset EGAD00001007971

• RNA sequencing of T-LGLL patients

  RNA sequencing was performed on 15 T-LGLL patients and five control samples. The raw data is provided as fastq files.

  Dataset EGAD00001008408

• RNA sequencing of control OM cells exposed to traffic-related air pollutants

  Total RNA sequencing of olfactory mucosa (OM) cells derived from cognitively healthy individuals exposed to traffic-related ultrafine particles (UFPs) for 24h and 72h in submerged cultures. The UFPs used for exposures were: A0, A20 and Euro6. Exposures were compared to the corresponding blank samples.

  Dataset EGAD00001011317

• Longitudinal evaluation of serum microRNAs as biomarkers for neuroblastoma burden and therapeutic p53 reactivation

  Small RNA sequencing data (TruSeq small RNA library preparation kit v2) from serum samples and tumor tissue of orthotopically injected mice (SH-SY5Y cell line) and unengrafted mice, treated with idasanutlin, temsirolimus and vehicle control.

  Dataset EGAD00001009625

• A molecular atlas of the human postmenopausal fallopian tube and ovary from single-cell RNA

  This datasets contains raw sequencing fastq data of 17 samples from 7 donors of single cell RNA using10x genome technology of human postmenopausal fallopian tube and ovary tissues.

  Dataset EGAD00001010076

• Comprehansive analysis of somatic mutations and genetic variations with whole genome sequencing

  Indetification of stractural variations by using of long read whole genome sequencing data

  Study JGAS000516

• WGS data of pediatric T-ALL acute lymphoblastic leukemia (set1)

  The dataset includes FASTQ and BAM files from diagnostic and matched remission (control) samples of one T-ALL patient (ALLT-317). Relapsed (BM ALLT-317L and Tonsil ALLT-3107L) sample files are in dataset set2 of this submission. Sequencing library was made using PCR free-based WGS library preparation (PCR-), using TruSeq DNA PCRfree library preparation kit v1 (PE150). Both diagnostic (60x) and remission (30x) samples were sequenced using HiSeq X.

  Dataset EGAD50000002013

• WGS data of paediatric hyperdiploid B cell acute lymphoblastic leukemia (set5)

  The dataset includes FASTQ and CRAM files from diagnostic and matched remission (control) samples of four hyperdiploid ALL patients (ALLT-502, ALLK-130, ALLK-137, ALLK-139). Sequencing libraries were made using PCR free-based WGS library preparation (PCR-), using Novogene NGS DNA Library Prep Set (Cat No. PT004). Both diagnostic (90x) and remission (30x) samples were sequenced using Illumina NovaSeq X Plus.

  Dataset EGAD50000002428

• GenomeDenmark Phase 2 - whole genome variants called using BayesTyper

  Variants and genotypes called in 50 danish parent-offspring trios from 80x Illumina sequencing data using BayesTyper. Data was produced using different insert size libraries of the sizes 180, 500, 800, 2000, 5000, 10000 and 20000 bp. The sample IDs for the fathers and mothers are TrioID-01 and TrioID-02, respectively, and the IDs for the children are TrioID-0x, where x is a number between 3 and 7

  Dataset EGAD00001003188

• Whole exome and targeted sequencing data from glioblastoma multiforme samples

  Whole exome and targeted sequencing data from 11 glioblastoma multiforme patients. A total of 70 tumour specimens and 11 blood samples were used for whole exome sequencing (WES) using the Agilent SureSelectXT Human All Exon V5 Kit. Two custom targeted sequencing panels were designed using the using Agilent’s Haloplex (TES1) or Agilent SureSelect XT2 technology (TES2). Libraries were sequenced on an Illumina HiSeq2500

  Dataset EGAD00001004420

• Non-invasive human skin transcriptome analysis using mRNA in skin surface lipids

  Non-invasive acquisition of mRNA data from the skin can be extremely useful for understanding skin physiology and diseases. Inspired by the holocrine process, in which the sebaceous glands secrete cell contents into the sebum, we focused on the possible presence of mRNAs in skin surface lipids (SSLs). We found that measurable levels of human mRNAs exist in SSLs, where the sebum protects them from degradation by RNases. The AmpliSeq transcriptome analysis was modified to measure SSL-RNA levels, and our results revealed that the SSL-RNAs predominantly comprised mRNAs derived from sebaceous glands, the epidermis, and hair follicles. Analysis of SSL-RNAs non-invasively collected from patients with atopic dermatitis revealed significantly increased expression of inflammation-related genes and decreased expression of terminal-differentiation���related genes, consistent with the results of previous reports. Further, we found that lipid-synthesis���related genes were downregulated in the sebaceous glands of patients with atopic dermatitis. These results indicate that the analysis of SSL-RNAs is a promising strategy to understand the pathophysiology of skin diseases.

  Study JGAS000416

• Non-invasive human skin transcriptome analysis using mRNA in skin surface lipids

  Non-invasive acquisition of mRNA data from the skin can be extremely useful for understanding skin physiology and diseases. Inspired by the holocrine process, in which the sebaceous glands secrete cell contents into the sebum, we focused on the possible presence of mRNAs in skin surface lipids (SSLs). We found that measurable levels of human mRNAs exist in SSLs, where the sebum protects them from degradation by RNases. The AmpliSeq transcriptome analysis was modified to measure SSL-RNA levels, and our results revealed that the SSL-RNAs predominantly comprised mRNAs derived from sebaceous glands, the epidermis, and hair follicles. Analysis of SSL-RNAs non-invasively collected from patients with atopic dermatitis revealed significantly increased expression of inflammation-related genes and decreased expression of terminal-differentiation���related genes, consistent with the results of previous reports. Further, we found that lipid-synthesis���related genes were downregulated in the sebaceous glands of patients with atopic dermatitis. These results indicate that the analysis of SSL-RNAs is a promising strategy to understand the pathophysiology of skin diseases.

  Study JGAS000418

• Non-invasive human skin transcriptome analysis using mRNA in skin surface lipids

  Non-invasive acquisition of mRNA data from the skin can be extremely useful for understanding skin physiology and diseases. Inspired by the holocrine process, in which the sebaceous glands secrete cell contents into the sebum, we focused on the possible presence of mRNAs in skin surface lipids (SSLs). We found that measurable levels of human mRNAs exist in SSLs, where the sebum protects them from degradation by RNases. The AmpliSeq transcriptome analysis was modified to measure SSL-RNA levels, and our results revealed that the SSL-RNAs predominantly comprised mRNAs derived from sebaceous glands, the epidermis, and hair follicles. Analysis of SSL-RNAs non-invasively collected from patients with atopic dermatitis revealed significantly increased expression of inflammation-related genes and decreased expression of terminal-differentiation���related genes, consistent with the results of previous reports. Further, we found that lipid-synthesis���related genes were downregulated in the sebaceous glands of patients with atopic dermatitis. These results indicate that the analysis of SSL-RNAs is a promising strategy to understand the pathophysiology of skin diseases.

  Study JGAS000417

• One-step generation of tumor models by base editor multiplexing in adult stem cell-derived organoids

  Recent optimization of CRISPR/Cas9-mediated genome engineering has resulted in the development of base editors that can efficiently mediate C>T and A>G transitions. Combining these genome engineering tools with human adult stem cell (ASC)-derived organoid technology holds promise for disease modeling. Here, we demonstrate the application of base editors for the generation of complex tumor models in human ASC-derived hepatocyte, endometrial and intestinal organoids. First, using conventional and evolved Cas9-variants, we show efficacy of both cytosine and adenine base editors and use them to model four hot-spot point mutations in CTNNB1 in hepatocyte organoids. Next, we apply C>T base editors in endometrial organoids to insert nonsense mutations in PTEN and demonstrate tumorigenicity even in the heterozygous state. Furthermore, we use cytosine base editors for simultaneous oncogene activation (PIK3CA) and tumor-suppressor inactivation (APC and TP53). To increase the flexibility of base editor multiplexing, we then combine SpCas9 and SaCas9 base editors for simultaneous C>T and A>G editing at individual target sites. Finally, we show the power of base editor multiplexing by modeling colorectal tumorigenesis in a single step by simultaneously transfecting sgRNA’s targeting four cancer genes. Seven clonal organoid lines and one bulk wild-type control sample were paired-end whole-genome sequenced using the Illumina Novaseq 6000 system. We sequenced four clonal intestinal organoid lines harbouring engineered TP53 and FBXW7 mutations as well as three lines targeted for oncogenic APC/TP53/PIK3CA/SMAD4 mutations. This WGS showed, as previously reported, a genome-wide increase in C>T mutations due to C>T base editor off-target activity, which is not enriched in predicted off-target regions based on the sgRNA sequences. Furthermore, we confirmed the absence of editing-induced driver mutations and lack of off-target mutational hotspots created by the genomic engineering.

  Study EGAS00001006886

• scRNA-seq of patient-derived PDAC organoids

  Dataset EGAD00001006448

• ChIP_3PEAKS

  Third batch of ChIP-seq narrowPeaks. Software: MACS2 v2.1.2

  Dataset EGAD00010002155

• Illumina HiSeqX whole genome sequence data on 58 samples including 54 with known HTT triplet repeat expansions (2 premutation and 52 full expansions)

  Whole genome sequence (WGS) data was generated on 58 samples with validated repeat lengths for the CAG repeat associated with Huntington disease, These samples were sequenced using 2x150bp reads on an Illumina HiSeqX sequencer and the repeat expansions were called using ExpansionHunter to demonstrate the ability to call large repeats from high throughput, WGS data.

  Study EGAS00001002593