11989 results for "cancer rna-seq"

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• Transcriptome analysis of iPSC-derived hepatocytes from Wilson's Disease patients and healthy controls

  To identify the differences in global gene expression patterns in WD-specific hepatocytes, we performed RNA-seq analysis. Six WD-specific hepatocytes and 6 healthy-donor (HD) hepatocytes were compared in total. The data suggested that our RNA-seq data were partially validated in the context of ATP7B deficiency and that these overlapped genes might be regulated by ATP7B deficiency among mammalian species in common.

  Study JGAS000382

• Transcriptomic subgroups in soft tissue tumors correlate with morphologic subtype, genomic features, and outcome

  We assessed gene expression (GGE) profiles and gene fusions as detected by transcriptome sequencing (RNA-seq) of 704 soft tissue tumors (STT) representing 56 different tumor types. Comparison with follow-up data identified transcriptional subclusters among sarcomas with complex genomes and among adipocytic tumors that correlated with metastasis-free survival and local recurrences, respectively. Thus, RNA-seq analysis of STT provides clinically important information.

  Study EGAS50000001472

• Discriminating Th17.1 cell driven sarcoidosis-like inflammation from relapse after anti-BCMA CAR T cells in multiple myeloma

  We present a case study on sarcoidosis-like flare-up after Idecabtagen Vicleucel (Ide-cel), a BCMA targeting CAR T cell therapy, and identified a Th17.1 driven autoimmune mechanism as the biological underpinning of this phenomenon using single-cell RNA-seq analysis. Furthermore, single-cell RNA-seq allowed to discriminate between immune-mediated changes and true relapse after CAR T cell treatment.

  Study EGAS00001006133

• Whole exome sequencing and RNA-seq of esophageal squamous cell carcinoma

  We perform integrative genome-wide analyses such as whole-exome sequencing, copy number variant(CNV) analysis, and gene expression analysis using next-generation sequencing and other methods to elucidate driver genes and signaling pathways causing tumorigenesis and cancer progression, leading novel molecular diagnostics and molecular therapies.

  Study JGAS000367

• microRNA-seq of human serum from a longitudinal study of 66 women with no history of cancer

  This dataset includes microRNA sequencing data from 198 human serum samples, representing a subset of 66 women with no history of cancer who participated in the UKCTOCS study and with serum samples collected at three timepoints over a period of up to 5 years. Small RNA libraries prepared from the serum samples were sequenced with 50-bp single end reads on an Illumina HiSeq 2000 instrument. Data is provided as FASTQ files.

  Dataset EGAD00001004348

• Single cell RNA-seq profiling of CD8 T cells from elder adults

  Single cell RNA-seq profiling of ~62k purified CD8+ T cell transcriptomes, from six healthy older adult donors using 10X genomics. Cells from each donor were separated based on their IL-7R protein expression (i.e. CD8+ IL7R+ and CD8+ IL7R- T cells).

  Study EGAS00001004255

• BLUEPRINT RNA-seq data for rare cells in the haematopoietic lineages, from adult and cord blood samples.

  RNA-seq data for rare cells in the haematopoietic lineages, from adult and cord blood samples.

  Study EGAS00001000284

• Indonesian RNA-seq dataset

  This dataset contains 4 batches of Indonesian RNA-seq data from Mentawai, New Guinea and Sumba islands. One RNA-seq batch was prepared without Globin depletion, and three batches were Globin depleted using the Illumina Globin-Zero Gold Kit. There are 179 runs in total, including 119 unique samples. Dataset includes multiple batch control samples.

  Dataset EGAD00001005053

• Systematic comparative analysis of single-nucleotide variants detection methods from single-cell RNA sequencing data

  Systematic interrogation of single nucleotide variations (SNVs) is one of the most promising approaches to delineate the cellular heterogeneity and phylogenetic relationships at the single cell level. While SNV detection from abundant single cell RNA sequencing (scRNA-seq) data is applicable and cost-effective in identifying expressed variants, inferring sub-clones, and deciphering genotype-phenotype linkages, there is a lack of computational methods specifically developed for SNV calling in scRNA-seq. Although variant callers for bulk RNA-seq have been sporadically used in scRNA-seq, the performances of different tools have not been assessed. Here, we performed a systematic comparison of seven tools including SAMtools, the GATK pipeline, CTAT, FreeBayes, MuTect2, Strelka2 and VarScan2, using both simulation and scRNA-seq datasets, and identified multiple elements influencing their performance. Our study provided the first benchmarking to evaluate the performances of different SNV detection tools for scRNA-seq data.

  Study EGAS00001003883

• TIRE-seq: an Integrated Sample Extraction and Transcriptomics Workflow for High Throughput Perturbation Studies

  TIRE-seq is a novel RNA sequencing method that integrates mRNA purification directly into library preparation, eliminating separate RNA extraction. The technique demonstrated utility across three biological applications, including capturing transcriptional changes in human T cells, identifying genes driving murine dendritic cell differentiation, and analyzing the dose-response effects of temozolomide on patient-derived neurospheres. With its simplified approach and high sequencing efficiency, TIRE-seq offers a cost-effective solution for large-scale gene expression studies.

  Study EGAS50000000867

• STAR outputs from RNA-seq

  STAR outputs from RNA-seq of 84 pancreatic neuroendocrine neoplasms, 10 normal islet samples and 4 cell line samples.

  Dataset EGAD00001006991

• WGS and RNA-Seq data from a GBM patient PT-BM8772

  WGS and RNA-Seq data from a GBM patient PT-BM8772

  Dataset EGAD00001008516

• WGS and RNA-Seq data from a GBM patient PT-WR7927

  WGS and RNA-Seq data from a GBM patient PT-WR7927

  Dataset EGAD00001008531

• WGS and RNA-Seq data from a GBM patient PT-GE7528

  WGS and RNA-Seq data from a GBM patient PT-GE7528

  Dataset EGAD00001008519

• WGS and RNA-Seq data from a GBM patient PT-RV2286

  WGS and RNA-Seq data from a GBM patient PT-RV2286

  Dataset EGAD00001008527

• WGS and RNA-Seq data from a GBM patient PT-GI2070

  WGS and RNA-Seq data from a GBM patient PT-GI2070

  Dataset EGAD00001008520

• WGS and RNA-Seq data from a GBM patient PT-JR9883

  WGS and RNA-Seq data from a GBM patient PT-JR9883

  Dataset EGAD00001008521

• WGS and RNA-Seq data from a GBM patient PT-ML9537

  WGS and RNA-Seq data from a GBM patient PT-ML9537

  Dataset EGAD00001008523

• Intellance-2: TruSight Tumor 170 panel based RNA-seq

  Intellance-2: TruSight Tumor 170 panel based RNA-seq

  Dataset EGAD00001007944

• RNA-Seq datasets in human islets cultured in high glucose conditions

  7 RNA-Seq datasets in human pancreatic islets from 7 donors, where islets were treated in high (11mM) glucose conditions

  Dataset EGAD00001005207

• RNA-Seq of pancreatic neuroendocrine tumors mutated in MEN1/DAXX/ ATRX

  RNA-Seq of of 11 primary pancreatic neuroendocrine tumors mutated in MEN1/DAXX/ ATRX used to identify molecular subtypes

  Dataset EGAD00001015695

• Smart-seq2 single-cell RNA-seq of human liver non-parenchymal cells

  Smart-seq2 single-cell RNA-seq of human liver non-parenchymal cells from lean and obese individuals

  Dataset EGAD00001010301

• WGS and RNA-Seq data from a GBM patient PT-HO0394

  WGS and RNA-Seq data from a GBM patient PT-HO0394

  Dataset EGAD00001004243

• WGS and RNA-Seq data from a GBM patient PT-CA2271

  WGS and RNA-Seq data from a GBM patient PT-CA2271

  Dataset EGAD00001004230

• WGS and RNA-Seq data from a GBM patient PT-TM5196

  WGS and RNA-Seq data from a GBM patient PT-TM5196

  Dataset EGAD00001004262