12068 results for "cancer rna-seq"

in 16.18 milliseconds.

• Whole Transcriptome Sequencing Data of prDLBCL

  We used sequenced 30 prDLBCL samples using RNA-seq to evaluate possible fusion events and to get expression profiles.

  Dataset EGAD50000000592

• Dataset for Stromal-induced epithelial-mesenchymal transition induces drug resistance in acute lymphoblastic leukemia

  RNA-seq was performed to compare gene expression profiles between 11 patient adherent ALL samples and nonadherent ALL samples.

  Dataset EGAD00001009056

• 20210729_EGA_BrainMet Saunus et al J Path (2015)

  Exome sequencing on HiSeq platform of 36 brain metastases with matched normal samples, 32 having matched RNA seq. Published Saunus et al J Path, (2015); https://doi.org/10.1002/path.4583

  Dataset EGAD00001007973

• Profiling human first-trimester neurodevelopment using scATAC-seq and multiomics

  116 single cell ATAC runs and 23 single cell multiome (ATAC+RNA) runs on various brain regions during human first-trimester development.

  Dataset EGAD00001011300

• Direct Comparative Analysis of 10X Genomics Chromium and Smart-seq2

  Single cell RNA sequencing (scRNA-seq) is widely used for profiling transcriptomes of individual cells. The droplet-based 10X Genomics Chromium (10X) approach and the plate-based Smart-seq2 full-length method are two frequently-used scRNA-seq platforms, yet there are only a few thorough and systematic comparisons of their advantages and limitations. Here, by directly comparing the scRNA-seq data by the two platforms from the same samples of CD45- cells, we systematically evaluated their features using a wide spectrum of analysis. Smart-seq2 detected more genes in a cell, especially low abundance transcripts as well as alternatively spliced transcripts, but captured higher proportion of mitochondrial genes. The composite of Smart-seq2 data also resembled bulk RNA-seq data better. For 10X-based data, we observed higher noise for mRNA in the low expression level. Despite the poly(A) enrichment, approximately 10-30% of all detected transcripts by both platforms were from non-coding genes, with lncRNA accounting for a higher proportion in 10X. 10X-based data displayed more severe dropout problem, especially for genes with lower expression levels. However, 10X-data can better detect rare cell types given its ability to cover a large number of cells. In addition, each platform detected different sets of differentially expressed genes between cell clusters, indicating the complementary nature of these technologies. Our comprehensive benchmark analysis offers the basis for selecting the optimal scRNA-seq strategy based on the objectives of each study.

  Dataset EGAD00001005448

• Differential Gene Expression in Cryptorchid Testes

  Differential Gene Expression in Cryptorchid Testes Study uses whole-genome RNA profiling of testicular biopsies to determine a potential causative role of isolated congenital cryptorchidism in azoospermia and/or infertility in the context of our previously published GeneChip data. Cryptorchid patients, aged 7 months to 5 years and otherwise healthy, were enrolled in this prospective study. During surgery, testicular tissue biopsies were obtained for histological examination and RNA-sequencing (RNA-seq). Fifteen patients were selected based on the histological results and were divided into two groups. Seven were classified as belonging to the high infertility risk (HIR) and eight to the low infertility risk (LIR) group. Cryptorchid boys in the high infertility risk group lacked transformation of gonocytes into Ad spermatogonia due to impaired mini puberty. This group of patients will be infertile despite successful surgery.

  Study phs001275

• PCA Atlas Chromium scRNA-seq and demultiplexing support (FASTQs, BAMs, capture-level VCFs and mapping tables)

  This dataset contains Chromium single-cell RNA-seq data and demultiplexing support for the PCA Atlas study EGAS00001008332. Included data objects: - 16 Chromium scRNA-seq FASTQ runs (EGAR accessions) for captures PCa1–PCa16. - 16 aligned BAM analyses (one Cell Ranger possorted_genome_bam.bam per capture). - 16 capture-level genotype VCF analyses derived from the Axiom UK Biobank array, used as demultiplexing panels. - demux_map.csv (EGAZ00001945520): donor–capture–sample mapping for genotype-based demultiplexing. - chromium.csv (EGAZ00001945537): run-level mapping linking captures, EGA samples, runs (EGAR), experiments (EGAX) and BAM analyses. Together these objects provide a complete view of the Chromium scRNA-seq data and the genotype-based demultiplexing support needed to reproduce donor assignment and downstream analyses.See also https://zenodo.org/records/17372603

  Dataset EGAD00001015795

• scRNA-seq and snRNA-seq of trophoblast stem cells (TSCs) differentiation into extravillous trophoblast organoids (EVTs)

  This dataset is part of a study that aims to compare in vivo human trophoblast differentiation into EVTs to different in vitro trophoblast organoids using single-cell and single-nuclei RNA sequencing. This specific dataset includes scRNA-seq and snRNA-seq data from trophoblast stem cells (TSCs). Trophoblast stem cell (TSC) lines BTS5 and BTS11 derived by Okae and colleagues were grown as described previously (Okae et al. 2018) together with EVT differentiation media. This study shows that the main regulatory programs mediating EVT invasion in vivo are preserved in in vitro models of EVT differentiation from primary trophoblast organoids and trophoblast stem cells. Data for primary trophoblast organoids is available under E-MTAB-12650.

  Dataset EGAD00001010017

• COVID-19 Multiomics Atlas

  We provide a single-nuclei RNA-sequencing (snRNA-seq) dataset derived from four COVID-19 patients, generated using the 10x Chromium Next GEM Single Cell v3.1 kit. For our study, these were integrated with snRNA-seq data with 12 publicly available sc/snRNA-seq datasets, comprising organ donor lung samples (n=89) and COVID-19 lung tissue samples (n=51). Additionally, we provide a spatial transcriptomic dataset characterizing different histopathological stages of diffuse alveolar damage, across a cohort of 33 COVID-19 patients. This was generated using the Nanostring Whole Transcriptome Assay (WTA) with regions of interest (ROIs) sized 400 µm² each. This integrated multi-omics analysis of snRNA-seq, histology, and spatial transcriptomics data, is available for exploration and download via our web portal: https://covid19-multiomicatlas.cellgeni.sanger.ac.uk/.

  Dataset EGAD00001015404

• Reference Profiles of ExRNAs in Normal Human Pregnancy

  In this study, we did a comprehensive exRNA profiling of plasma and serum specimens from healthy pregnant women, sampled at different gestational time points, and including subjects with diverse geographical and ethnic backgrounds. This study also contains samples from male and female healthy donors to provide a baseline. The aim of this study is to identify miRNAs that can predict the gestation age and to build a miRNA profile across gestation using small RNA-seq data.

  Study phs003182