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
Reader Engagement
Emerging Content
0.3
/100
1 views
1 readers
Trending
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
Comments
No comments yet. Be the first to comment on this article.