%0 Journal Article %1 Gatter2021-wr %A Gatter, Thomas %A Stadler, Peter F %D 2021 %I Oxford University Press (OUP) %J Bioinformatics %K %N 23 %P 4307--4313 %T Ry\=ut\=o: improved multi-sample transcript assembly for differential transcript expression analysis and more %V 37 %X Abstract Motivation Accurate assembly of RNA-seq is a crucial step in many analytic tasks such as gene annotation or expression studies. Despite ongoing research, progress on traditional single sample assembly has brought no major breakthrough. Multi-sample RNA-Seq experiments provide more information than single sample datasets and thus constitute a promising area of research. Yet, this advantage is challenging to utilize due to the large amount of accumulating errors. Results We present an extension to Ry\=ut\=o enabling the reconstruction of consensus transcriptomes from multiple RNA-seq datasets, incorporating consensus calling at low level features. We report stable improvements already at three replicates. Ry\=ut\=o outperforms competing approaches, providing a better and user-adjustable sensitivity-precision trade-off. Ry\=ut\=o's unique ability to utilize a (incomplete) reference for multi sample assemblies greatly increases precision. We demonstrate benefits for differential expression analysis. Ry\=ut\=o consistently improves assembly on replicates of the same tissue independent of filter settings, even when mixing conditions or time series. Consensus voting in Ry\=ut\=o is especially effective at high precision assembly, while Ry\=ut\=o's conventional mode can reach higher recall. Availability and implementation Ry\=ut\=o is available at https://github.com/studla/RYUTO. Supplementary information Supplementary data are available at Bioinformatics online.

@article{Gatter2021-wr, abstract = {Abstract Motivation Accurate assembly of RNA-seq is a crucial step in many analytic tasks such as gene annotation or expression studies. Despite ongoing research, progress on traditional single sample assembly has brought no major breakthrough. Multi-sample RNA-Seq experiments provide more information than single sample datasets and thus constitute a promising area of research. Yet, this advantage is challenging to utilize due to the large amount of accumulating errors. Results We present an extension to Ry{\=u}t{\=o} enabling the reconstruction of consensus transcriptomes from multiple RNA-seq datasets, incorporating consensus calling at low level features. We report stable improvements already at three replicates. Ry{\=u}t{\=o} outperforms competing approaches, providing a better and user-adjustable sensitivity-precision trade-off. Ry{\=u}t{\=o}'s unique ability to utilize a (incomplete) reference for multi sample assemblies greatly increases precision. We demonstrate benefits for differential expression analysis. Ry{\=u}t{\=o} consistently improves assembly on replicates of the same tissue independent of filter settings, even when mixing conditions or time series. Consensus voting in Ry{\=u}t{\=o} is especially effective at high precision assembly, while Ry{\=u}t{\=o}'s conventional mode can reach higher recall. Availability and implementation Ry{\=u}t{\=o} is available at https://github.com/studla/RYUTO. Supplementary information Supplementary data are available at Bioinformatics online.}, added-at = {2024-09-10T11:56:37.000+0200}, author = {Gatter, Thomas and Stadler, Peter F}, biburl = {https://puma.scadsai.uni-leipzig.de/bibtex/2f2dbdb62965ba3733319a335a662bc8f/scadsfct}, copyright = {https://academic.oup.com/journals/pages/open\_access/funder\_policies/chorus/standard\_publication\_model}, interhash = {62e171dd8ff326e0a186b7ce4a68464c}, intrahash = {f2dbdb62965ba3733319a335a662bc8f}, journal = {Bioinformatics}, keywords = {}, language = {en}, month = jul, number = 23, pages = {4307--4313}, publisher = {Oxford University Press (OUP)}, timestamp = {2024-09-10T15:15:57.000+0200}, title = {Ry{\=u}t{\=o}: improved multi-sample transcript assembly for differential transcript expression analysis and more}, volume = 37, year = 2021 }