Universität zu Köln

Lehmann, Kjong-van, Kahles, Andre ORCID: 0000-0002-3411-0692, Murr, Magdalena and Raetsch, Gunnar (2022). RNA Instant Quality Check: Alignment-Free RNA-Degradation Detection. J. Comput. Biol., 29 (8). S. 857 - 867. NEW ROCHELLE: MARY ANN LIEBERT, INC. ISSN 1557-8666

Full text not available from this repository.

Abstract

With the constant increase of large-scale genomic data projects, automated and high-throughput quality assessment becomes a crucial component of any analysis. Whereas small projects often have a more homogeneous design and a manageable structure allowing for a manual per-sample analysis of quality, large-scale studies tend to be much more heterogeneous and complex. Many quality metrics have been developed to assess the quality of an individual sample on the raw read level. Degradation effects are typically assessed based on the RNA integrity (RIN) score, or on postalignment data. In this study, we show that single commonly used quality criteria such as the RIN score alone are not sufficient to ensure RNA sample quality. We developed a new approach and provide an efficient tool that estimates RNA sample degradation by computing the 5 '/3 ' bias based on all genes in an alignment-free manner. That enables degradation assessment right after data generation and not during the analysis procedure allowing for early intervention in the sample handling process. Our analysis shows that this strategy is fast, robust to annotation and differences in library size, and provides complementary quality information to RIN scores enabling the accurate identification of degraded samples.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Lehmann, Kjong-van UNSPECIFIED UNSPECIFIED UNSPECIFIED Kahles, Andre UNSPECIFIED orcid.org/0000-0002-3411-0692 UNSPECIFIED Murr, Magdalena UNSPECIFIED UNSPECIFIED UNSPECIFIED Raetsch, Gunnar UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-686556
DOI:	10.1089/cmb.2021.0603
Journal or Publication Title:	J. Comput. Biol.
Volume:	29
Number:	8
Page Range:	S. 857 - 867
Date:	2022
Publisher:	MARY ANN LIEBERT, INC
Place of Publication:	NEW ROCHELLE
ISSN:	1557-8666
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language Biochemical Research Methods; Biotechnology & Applied Microbiology; Computer Science, Interdisciplinary Applications; Mathematical & Computational Biology; Statistics & Probability Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/68655