Identification of Fusion Transcripts from Unaligned RNA-Seq Reads Using ChimeRScope.

Clicks: 168
ID: 102046
2020
Article Quality & Performance Metrics
Overall Quality Improving Quality
0.0 /100
Combines engagement data with AI-assessed academic quality
AI Quality Assessment
Not analyzed
Abstract
Fusion transcripts that are frequent in cancer can be exploited to understand the mechanisms of malignancy and can serve as diagnostic or prognostic markers. Several algorithms have been developed to predict fusion transcripts from DNA or RNA data. The majority of these algorithms align sequencing reads to the reference transcriptome for predicting fusions; however, this results in several undetected fusions due to the highly perturbed nature of cancer genomes. Here, we describe a novel method that uses a k-mer based algorithm to predict fusion transcripts accurately using the unaligned reads from the regular RNA-seq data analysis pipelines.
Reference Key
vellichirammal2020identificationmethods Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Vellichirammal, Neetha Nanoth;Albahrani, Abrar;Li, You;Guda, Chittibabu;
Journal methods in molecular biology (clifton, nj)
Year 2020
DOI 10.1007/978-1-4939-9904-0_2
URL
Keywords

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.