@inbook{93a2dbddae3440cc8224fb53d09c1c51,
title = "Identification of Fusion Transcripts from Unaligned RNA-Seq Reads Using ChimeRScope",
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.",
keywords = "ChimeRScope, Fusion detection algorithm, Fusion transcripts, Oncogenic fusions, RNA-seq, k-mers",
author = "Vellichirammal, {Neetha Nanoth} and Abrar Albahrani and You Li and Chittibabu Guda",
note = "Funding Information: This work was supported by the development funds to CG from UNMC and partial support from National Institutes of Health grants [P20GM103427, 1P30GM110768, P30CA036727, and 2P01AG029531]. Publisher Copyright: {\textcopyright} 2020, Springer Science+Business Media, LLC, part of Springer Nature.",
year = "2020",
doi = "10.1007/978-1-4939-9904-0_2",
language = "English (US)",
series = "Methods in Molecular Biology",
publisher = "Humana Press Inc.",
pages = "13--25",
booktitle = "Methods in Molecular Biology",
}