11768 results for "cancer rna-seq"

in 13.45 milliseconds.

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=24hrs_RPMI_T=5days from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=24hrs_RPMI_T=5days from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002904

• BLUEPRINT September 2016, ATAC-seq for unswitched memory B cell from venous blood, on Genome GRCh38

  ATAC-seq data for 3 sample(s) for unswitched memory B cell from venous blood, on Genome GRCh38. 3 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002905

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=1hr from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=1hr from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002906

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=24hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=24hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002909

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=4hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=4hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002910

• BLUEPRINT September 2016, ATAC-seq for germinal center B cell from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for germinal center B cell from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002911

• Separation, characterization, and identification of individuals from multi-person blood mixtures with single cell ATAC-seq

  We report a deconvolution and identification strategy of scATAC-seq datasets using mixed PMBCs data. After sequencing the data were processed with the de-goulash pipeline and analyzed with aim to identify and acquire biogeogrpahical ancestry of the involved individuals. The study includes samples of biological mixtures and in silico mixtures in different mixed ration and cell volumes.

  Study EGAS00001007380

• LuCaP cell line ChIP-seq

  ChIP-seq of 2 LuCaP cell lines with different factors. LuCaP cell line 189.4 was ChIP-sequenced for 6 factors with different conditions as well as the input DNA (n=31 in total). LuCaP 189.4 ChIP-sequence experiments include; 3 H3K27ac/DMSO, 3 H3K27ac/vorinostat, 3 H3K27ac/dexamethasone, 3 H3K27ac/dexamethasone/vorinostat, 3 GR dexamethasone, 3 GR dexamethasone/vorinostat, 3 HDAC3/DMSO, 3 AR, 3 FOXA1, 3 H3K27ac and 1 input sample. LuCaP 35 ChIP-sequence experiments as well as input include (n=10 in total); 3 H3K27ac, 3 AR, 3 FOXA1 and 1 input sample. All 41 samples were sequenced using paired-end reads on Illumina NovaSeq 6000. Each sample has 2 fastq files, one for the forward and reverse read, respectively.

  Dataset EGAD50000001345

• Single cell and plasma RNA sequencing

  Single cell and plasma RNA sequencing for RNA liquid biopsy for hepatocellular carcinoma

  Study EGAS00001005194

• RNA sequencing from patient-derived intestinal organoids

  RNA from the duodenal organoids was isolated using an RNeasy Kit (Qiagen, Hilden, Germany) following the manufacturer’s instructions. RNA purity and concentration were measured using a NanoDrop One spectrophotometer (NanoDrop Technologies, Wilmington, Delaware, USA). Preparation of the RNA library and transcriptome sequencing was conducted by Novogene Co., LTD (Cambridge, UK). Messenger RNA was purified from total RNA using polyA selection and subjected to library construction. Sequencing was performed on an Illumina platform, and 150 bp paired-end reads were generated.

  Study EGAS50000000338

• Ancestry and somatic profile predict acral melanoma origin and prognosis – RNA

  Acral melanoma, which is not ultraviolet (UV)-associated, is the most common type of melanoma in several low- and middle-income countries including Mexico. Latin American samples are significantly underrepresented in global cancer genomics studies, which directly affects patients in these regions as it is known that cancer risk and incidence may be influenced by ancestry and environmental exposures. To address this, we characterise the genome and transcriptome of 123 acral melanoma tumours from 92 Mexican patients, a population notable because of its genetic admixture. Compared with other studies of melanoma, we found fewer frequent mutations in classical driver genes such as BRAF, NRAS or NF1. While most patients had predominantly Amerindian genetic ancestry, those with higher European ancestry had increased frequency of BRAF mutations and a lower median number of structural variants. The tumours with activating BRAF mutations have a transcriptional profile more similar to cutaneous non-volar melanocytes, suggesting that acral melanomas in these patients may arise from a distinct cell of origin compared to other tumours arising in these locations. KIT mutations were found in a subset of these tumours, and quadruple wild-type samples (non BRAF/NRAS/NF1/KIT) differed from mutated samples in their structural genomic profile and overall and recurrence-free survival patterns. Transcriptional profiling defined three expression clusters; these characteristics were associated with recurrence-free and overall survival. We highlight potential novel low-frequency drivers, such as PTPRJ, NF2 and RDH5. Our study enhances knowledge of this understudied disease and underscores the importance of including samples from diverse ancestries in cancer genomics studies.

  Dataset EGAD00001015756

• IBMsnRNAseq

  snRNA-seq and spatial transcriptomic data and analysis of healthy (CTRL) and inflamed (immune-mediated necrotizing myopathy (IMNM) and inclusion body myositis (IBM)) human quadriceps muscle. This data set includes 19 snRNA-seq (7 CTRL, 4 IMNM, 8 IBM) and 8 ST samples (3 CTRL, 2 IMNM, 3 IBM).

  Dataset EGAD50000000449

• scRNA seq Data set

  This data set contains the raw FASTq files and processed files of scRNA seq experiment which were conducted on 3 EMD samples. The libraries were generated using 10x genomics Dual index Single Cell 3' v3.1. The processed files are TSV files of features, barcodes, and gene expression matrix

  Dataset EGAD50000000334

• Human T-bet governs innate and innate-like adaptive IFN-g immunity against mycobacteria.

  We report a patient with mycobacterial disease due to inherited deficiency of the transcription factor T-bet. PBMCs from the patient was analyzed with scRNA-seq.

  Study EGAS00001004504

• Histone Acetylome-wide Association Study of Autism Spectrum Disorder

  H3K27ac ChIP-seq were performed on postmortem samples from autism spectrum disorder and matched control brains. Tissues were chosen from three brain regions: prefrontal cortex, temporal cortex and cerebellum.

  Study EGAS00001001943

• Single-Cell Protein Expression via scTAMseq Cite-seq

  This dataset contains single-cell surface marker expression profiles generated by integrating the Cite-seq protocol with scTAMseq. Samples were stained with an antibody panel targeting 45 (donor A.6 & A.7) and 56 (donors A.1-A.5, B.1-B.5, and X.2 ) surface proteins to enable robust phenotypic characterization.

  Dataset EGAD00001015497

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

  ChIP-Seq data for 2 macrophage - T=6days untreated 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 EGAD00001002458

• Peripheral Blood Leukocytes 10x Genomics scRNA-seq

  This dataset contains 10x Genomics Single Cell 3’ Solution (version 2) scRNA-seq data from peripheral blood leukocytes of a single healthy donor. Data from 20939 cells were collected over 8 lanes and 2 sequencing runs.

  Dataset EGAD00001008590

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

  ChIP-Seq data for 2 macrophage - T=6days LPS 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 EGAD00001002498

• BLUEPRINT September 2016, ATAC-seq for venous blood, on Genome GRCh38

  ATAC-seq data for 136 sample(s) from venous blood, on Genome GRCh38. 141 run(s), 139 experiment(s), 139 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002709

• BLUEPRINT September 2016, ATAC-seq for monocyte RPMI_BG_T=24hrs_RPMI_T=5days_LPS_T=4hrs from venous blood, on Genome GRCh38

  ATAC-seq data for 1 sample(s) for monocyte RPMI_BG_T=24hrs_RPMI_T=5days_LPS_T=4hrs from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002915

• Single-Cell Mitochondrial Variant Profiling via TAMITO-seq

  This dataset focuses on mitochondrial variant detection using the TAMITO-seq protocol. A pre-designed mitochondrial panel (https://designer.missionbio.com/catalogpanels/Virtual-mtDNA) was spiked into the scTAMseq workflow targeting 200 CpGs and 167 genotyping loci. Data were generated from a peripheral blood sample of a healthy donor, donor X.2, multiplexed with data from another donor.

  Dataset EGAD00001015494

• PhIP-Seq Serum 1000IBD

  PhIP-Seq experiment conducted in Eran Sigal's group at WIS.

  Dataset EGAD00001010118

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

  ChIP-Seq data for 2 macrophage - T=6days B-glucan 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 EGAD00001002314

• BLUEPRINT September 2016, ATAC-seq for class switched memory B cell from venous blood, on Genome GRCh38

  ATAC-seq data for 2 sample(s) for class switched memory B cell from venous blood, on Genome GRCh38. 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002908