7190 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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• Chordoma_Sequencing_Project_Whole_Genome

  This is a continuation of the Chordoma Sequencing Project, prelim #G0175-122-CF. All cancers arise due to somatically acquired abnormalities in DNA sequence. Systematic sequencing of cancer genomes allows acquisition of complete catalogues of all classes of somatic mutation present in cancer. These mutation catalogues will allow identification of the somatically mutated cancer genes that are operative and characterise patterns of somatic mutation that may reflect previous exogenous and endogenous mutagenic exposures. In this application, we aim to perform whole genome sequencing on 10 chordoma matched genome pairs. The Chordoma Foundation will fund the RNA Sequencing/Methylation and SNP6 costs for this project while the whole genome and library sequencing will be covered under the CGP, 2012-2013 core WTSI internal funding. An additional sequencing of three cancer cell lines will be added to this work, financed by the Chordoma Foundation. In this project, the Chordoma foundation will pay for the additional costs of methylation, RNA Seq,

  Study EGAS00001000409

• Whole Genome Sequencing of HCC

  The French ICGC project on liver tumors is coordinated by Pr Jessica Zucman-Rossi and funded by Inca (French Institute for Cancer). The aim of the present project is to identify the catalog of somatic and germline mutations in liver tumors using whole genome (WGS) and whole exome sequencing (WGS), integrated with DNA methylation and RNA sequencing (RNA-seq) data. The present series corresponds to 24 whole genome sequencing (12 Tumoral/Non-tumoral pairs). Hepatocellular carcinoma (HCC) accounts for more than 90% of liver cancers, and is a major health problem. It is the 3rd cause of cancer-related mortality. Advances in genomic analyses have formed a comprehensive understanding of different underlying pathobiological layers resulting in hepatocarcinogenesis. Thus, the development of next-generation sequencing technologies has made it possible to generate more comprehensive catalogues of somatic alteration events (single nucleotide substitutions, structural variations, and epigenetic changes) in liver cancer genome than ever before.

  Study EGAS00001002888

• RNA-seq Phase Ib of olaparib and capivasertib

  RNA-seq Phase Ib of olaparib and capivasertib

  Dataset EGAD00001006840

• RNA-seq from melanoma biopsies

  RNA-seq data for melanoma biopsies at baseline and after treatment

  Dataset EGAD00001009059

• RNA-seq reads

  Cancer RNA-seq consisting of FASTQ paired-end reads from ovary samples

  Dataset EGAD00001003918

• RNA-seq from normal human tissues

  RNA-seq from normal human tissues (2 x 75 bp)

  Dataset EGAD00001001057

• RNA-seq from normal human tissues

  RNA-seq from normal human tissues (2 x 250 bp)

  Dataset EGAD00001001922

• Host pathogen interaction long read transcriptome

  Our incomplete knowledge of the human transcriptome impairs the detection of disease-causing variants, in particular in transcripts only expressed under certain conditions. These transcripts are often lacking from reference transcript sets, such as Ensembl/GENCODE and RefSeq, and could be relevant for establishing genetic diagnoses. We present SUsPECT (Solving Unsolved Patient Exomes/gEnomes using Custom Transcriptomes), a pipeline based on the Ensembl Variant Effect Predictor (VEP) to predict variant impact on custom transcript sets, such as those generated by long-read RNA-sequencing, for downstream prioritization. Our pipeline predicts the functional consequence and likely deleteriousness scores for missense variants in the context of novel open reading frames predicted from any transcriptome. We demonstrate the utility of SUsPECT by uncovering potential mutational mechanisms of pathogenic variants in ClinVar that are predicted to be benign using the reference transcript annotation. In further support of SUsPECT’s utility, we identified an enrichment of immune-related variants predicted to have a more severe molecular consequence when annotating with a newly generated transcriptome from stimulated immune cells instead of the reference transcriptome. Our pipeline outputs crucial information for further prioritization of potentially disease-causing variants for any disease and will become increasingly useful as more long-read RNA sequencing datasets become available.

  Study EGAS00001006779

• Transcriptome profiling (RNA-seq) of human acute leukemias

  Total RNA-seq of blasts derived from 131 adult T-ALL cases, 7 AML cases and 1 mixed myeloid/lymphoid leukemia with CpG Island Methylator Phenotype (CIMP). The other RNA-seq data used in this study has been previously published and is available at EGAD00001007581 (AML) and EGAD00001007646 (CD34+ cells).

  Dataset EGAD00001011054

• Significant and pervasive effects of RNA degradation on Nanopore direct RNA sequencing

  Abstract Oxford Nanopore direct RNA sequencing (DRS) is capable of sequencing complete RNA molecules and accurately measuring gene and isoform expression. However, as DRS is designed to profile intact RNA, expression quantification may be more heavily dependent upon RNA integrity than alternate RNA-seq methodologies. It is currently unclear how RNA degradation impacts DRS or if it can be corrected for. To assess the impact of RNA integrity on DRS we performed a degradation time-series using SH-SY5Y neuroblastoma cells. Our results demonstrate that degradation is a significant and pervasive factor that can bias DRS measurements, including a reduction in library complexity resulting in an overrepresentation of short genes and isoforms. Degradation also biases differential expression analyses; however, we find explicit correction can almost fully recover meaningful biological signal. In addition, DRS provided less biased profiling of partially degraded samples than nanopore cDNA-PCR sequencing. Overall, we find samples with RIN > 9.5 can be treated as undegraded and samples with RIN > 7 can be utilised for DRS with appropriate correction. These results establish the suitability of DRS for a wide range of samples, including partially degraded in-vivo clinical and post-mortem samples, whilst limiting the confounding effect of degradation on expression quantification.

  Study EGAS00001006542