Targeted next-generation sequencing of a cancer transcriptome enhances detection of sequence variants and novel fusion transcripts

By J. Levin, Michael F Berger, Xian Adiconis, P. Rogov, A. Melnikov, Tim Fennell, Chad Nusbaum, Levi A. Garraway, Andreas Gnirke. Genome Biology, 2009

4,613 citations recorded by the source corpus.

Targeted RNA-Seq combines next-generation sequencing with capture of sequences from a relevant subset of a transcriptome. When testing by capturing sequences from a tumor cDNA library by hybridization to oligonucleotide probes specific for 467 cancer-related genes, this method showed high selectivity, improved mutation detection enabling discovery of novel chimeric transcripts, and provided RNA expression data. Thus, targeted RNA-Seq produces an enhanced view of the molecular state of a set of "high interest" genes.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/c5b775209edbd402ac081752106023d1ffe56fbf

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Citations in the corpus

Data quality aware analysis of differential expression in RNA-seq with NOISeq R/Bioc package (2015, methodology): “A functional enrichment analysis was performed by comparing the DEG called by each method to the rest of the genome using GOseq (21).”
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Interrogation of the Microenvironmental Landscape in Brain Tumors Reveals Disease-Specific Alterations of Immune Cells (2020, methodology): “Over-representation was assessed with the goseq R package (Young et al., 2010) for differentially expressed genes to correct for gene length bias, otherwise the hypergeometric test was employed.”
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