3743 results for "RNA AND sequencing OR transcriptome"

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• Patient-tailored design for selective co-inhibition of leukemic cell subpopulations

  Single-cell RNA sequencing was performed on bone marrow mononuclear cells of 2 acute myeloid leukemia patients at refractory stage. The profiling was performed using 10x Genomics Chromium Single Cell 3ʹ Gene Expression platform. The raw data are available as fastq files.

  Dataset EGAD00001006360

• Identification of molecule relationship between intravenous leiomyomatosis and uterus myoma

  Up to now, there are two hypothesis about the pathogenesis of the relationship of intravenous leiomyomatosis and uterine myoma. One theory suggests that the IVL comes from the smooth muscle cell in the vessel wall.The other theory indicates that the IVL derives from the uterine myometrium. However, limited to the technology, few studies have been deeply explore the underlying relation. In this study, we employ the RNA sequencing to explore the molecule relationship between IVL and uterus myoma. In order to identify the molecule relationship between IVl and uterine myoma we conducted transcriptome sequencing and bioinformaitc analysis

  Dataset EGAD00001003356

• Single-cell transcriptome landscape of developing fetal gonads defines somatic cell lineage specification in humans

  Single-cell RNA-seq dataset recovering the gene expression programs of around 128,000 single cells derived from 17 fetal testes and 16 fetal ovaries from 5 to 12 postconceptional weeks.

  Dataset EGAD00001009811

• Transcriptome data of WS patients and controls

  Fibroblasts of 4 WS patients and 4 sex matched controls were transformed into iPSCs, which were then differentiated to Neuroepithelial Stem Cells (NESCs), and further differentiated into neurons. RNA sequencing was performed at the NESC stage and after 4 and 8 weeks of neural development for 3 replicates per individual using the Illumina TruSeq stranded library polyA method on the NovaSeq6000 platform at NGI Stockholm. The data was preprocessed using the nf-core/rnaseq (https://nf-co.re/rnaseq) that includes quality control, data cleaning, and read alignment to GRCh38 (STAR, v2.6.1d)

  Dataset EGAD50000001728

• 79 Human Hearts snRNAseq

  Using single-nucleus RNA sequencing, we characterized the transcriptome of 880,000 nuclei from 18 control and 61 failing, nonischemic human hearts with pathogenic variants in DCM and ACM genes or idiopathic disease.

  Dataset EGAD00001009292

• Transcriptome sequencing of hepatocellular carcinoma biopsies (TACE study)

  Illumina-based RNA-Seq analysis of 93 liver samples. Biopsies of tumors and non-tumor tissues are included. Samples are stratified by response and non-response to TACE treatment.

  Dataset EGAD00001008158

• Tumor gene expression profiles for the study "TGF-β attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells"

  RNA was extracted from formalin-fixed and paraffin embedded tumors of a large cohort of bladder cancer patients before treatment with anti-PD-L1. RNA was sequenced using a capture based approach (exome capture, RNA access).

  Dataset EGAD00001003977

• Single-Cell Analysis of Human Adipogenesis

  The data in this study consists of RNA sequencing reads and read counts from single-cell and single-nuclei RNA sequencing experiments performed on two cell lines to investigate the transcriptional landscape of human adipogenesis in both the brown and white adipose tissue lineage. The two cell lines are human preadipocytes collected and isolated from a defined anatomical location in the neck of a single individual. This depot is known to harbor white adipose tissue (WAT) and brown adipose tissue (BAT). These white and brown preadipocytes were immortalized for the purposes of studying human adipogenesis in vitro. In this study we induced differentiation of these two preadipocyte lines and performed RNA sequencing on over 135,000 single cells spanning a 20-day time course from unperturbed preadipocytes to mature adipocytes from both brown and white lineages. Additionally, we performed both single-cell and single-nuclei RNA sequencing to comprehensively compare the advantages and disadvantages of either technique.

  Study phs002461

• RNA-seq as a tool for evaluating human embryo competence

  The majority of embryos that are created through IVF do not implant. One possibility for this inefficiency is an incomplete understanding of the molecular factors affecting embryo competence. Currently, the process of selecting an embryo for uterine transfer utilizes an ad-hoc combination of morphological criteria, the kinetics of development, and genetic testing for aneuploidy. However, no single criterion can ensure selection of a viable embryo. In contrast, RNA-sequencing of embryos could yield highly dimensional data, which may provide additional insight and illuminate the discrepancies among current selection criteria. Indeed, recent advances enabling the production of RNA-sequencing (RNA-seq) libraries from single cells have facilitated the application of this technique to the study of some transcriptional events in early human development. However, these studies have not assessed the quality of their constituent embryos relative to commonly used embryological criteria. Here, we perform proof-of-principle advancement to clinical selection procedures by generating high quality RNA-seq libraries from a trophectoderm biopsy as well as the remaining whole embryo. We combine state-of-the-art embryological methods with low-input RNA-seq to develop the first transcriptome-wide approach for use in future predictive embryology studies. Specifically, we demonstrate the capacity of RNA-seq as a promising tool in preimplantation screening by showing that biopsies of an embryo can capture valuable information content available in the whole embryo from which they are derived. Furthermore, we show that this technique can be used to generate a RNA-based digital karyotype, and to develop a foundational dataset for identifying candidate competence-associated genes. Together, these data establish the foundation for a future RNA-based diagnostic in IVF.

  Study EGAS00001003667

• Genomics of enteropathy-associated T cell lymphoma (EATL)

  Whole exome sequencing of enteropathy-associated T cell lymphoma (EATL) tumors and paired normals, as well as RNA-sequencing of EATL tumors: including (1) 69 exome capture, paired-end Illumina Hiseq sequencing, BAM files from EATL tumor samples, (2) 36 exome capture, paired-end Illumina Hiseq sequencing, BAM files from EATL paired normal samples, and (3) 32 RNAseq, paired-end Illumina Hiseq sequencing, BAM files from EATL tumor samples.

  Dataset EGAD00001003284