7199 results for "({!join from=dataset_studies to=id v=$q1}) OR ("transcriptome" OR "RNA-seq" OR "rna sequencing" OR "rna-sequencing")"

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• AHA Uganda Study RNAseq Dataset

  This dataset was generated as part of the AHA Uganda Study, an Acute Rheumatic Fever case-control prospective study conducted in Uganda. This dataset consists of raw fastqs from RNA sequencing for 266 samples (226 cases, 40 controls) from 162 individuals over five timepoints. RNA was extracted from Paxgene blood samples using the Sureselect HS2 library preparation kit. Sequencing was performed on Illumina NovaSeq 6000, yielding ~30-40 million raw paired reads per sample.

  Dataset EGAD00001015810

• Analysis of chromosomal background of cancerous mutations using a long-read sequencer

  In our previous study detecting cancerous complex SVs, we performed whole-genome sequencing of lung cancer clinical samples using PromethION. In this study, its depth and quality was substantially enriched and we conducted the phasing analysis in human lung cancer genomes. In addition, long read and short read RNA-seq was performed for transcriptome analysis.

  Study JGAS000349

• RNA-Seq data of hepatoma (Huh7 derived) and Ph5CH cells and primary hepatocytes

  The innate immune response of cells of hepatic origin (Huh7, Huh7.5, PH5CH and primary human hepatocytes (PHH), 66 samples) was analyzed by transcriptome analysis (RNAseq) upon supernatant delivery or transfection of synthetic dsRNA (poly(I:C)). Expression of TLR3 and RIG-I was reconstituted by lentiviral transduction in Huh7 and Huh7.5 cells. The sequencing is single RNA-Seq on an Illumina HiSeq 4000 with the Illumina TruSeq stranded mRNA kit.

  Dataset EGAD00001007083

• RNA sequencing of undifferentiated sarcomas

  Dac EGAC00001001055

• Controlling cell differentiation with precision through understanding the structure and dynamics of gene regulatory networks

  We established a set of transgenic human ES cell lines that carry inducible expression gene cassette for singe transcriptional factor induction with Tet-ON system. Transcriptome data was obtained 48h after transgene induction by Microarray. We established inducible human ES lines about more than 700 genes, and achieved microarray analysis on 115 genes. Our data set has multiple characteristic properties; 1) the same platform across data set, 2) analyzed with dynamic cell status, 3) pre-determined initiation point on gene perturbation, 4)inducible in different cell status. In parallele, we also performed RNA sequenncig analysis on 435 transgene induced ES lines as well. 32 transgene induced transcriptome data were obtained from both Microarray and RNA sequencing, normalizing technical gaps between them. We hope those systematic data set to reveal transcriptional network structure and molecular mechanisms of cell differentiation.

  Study JGAS000121

• Cell-type, allelic and genetic signatures in the human pancreatic beta cell transcriptome

  Pancreatic beta cells within the islets of Langerhans are centrally involved in the pathogenesis of both type 1 and type 2 diabetes. Describing the differentiated state of the human beta cell has been hampered so far by technical (low resolution microarrays) and biological limitations (whole islet preparations rather than isolated beta cells). We circumvent these by deep RNA sequencing of purified beta cells from 11 individuals, presenting here the first characterization of the human beta cell transcriptome. Additionally, we perform the first comparison of gene expression profiles between beta cells, whole islets (N=7) and beta cell depleted islet preparations (N=5), revealing thus beta cell specific expression signatures. Finally, we combine this with whole-genome sequencing data for 7 of our donors, describing here the first set of genetic variants controlling inter-individual variability in beta cell gene expression.

  Study EGAS00001000442

• 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

• Identifying the role of ID3 in DNA repair and maintenance of genome integrity (RNA-seq)

  Dataset EGAD00001008198

• RNA-Seq of kidney cancer organoid biobank

  Dataset EGAD00001005318

• scRNA PDX

  Single cell RNA-seq for PT1-derived PDX samples

  Dataset EGAD00001006134