A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä
ROTS: An R package for reproducibility-optimized statistical testing
Tekijät: Tomi Suomi, Fatemeh Seyednasrollah, Maria K. Jaakkola, Thomas Faux,
Laura L. Elo
Kustantaja: PUBLIC LIBRARY SCIENCE
Julkaisuvuosi: 2017
Journal: PLoS Computational Biology
Tietokannassa oleva lehden nimi: PLOS COMPUTATIONAL BIOLOGY
Lehden akronyymi: PLOS COMPUT BIOL
Artikkelin numero: ARTN e1005562
Vuosikerta: 13
Numero: 5
Sivujen määrä: 10
ISSN: 1553-734X
DOI: https://doi.org/10.1371/journal.pcbi.1005562
Verkko-osoite: http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005562
Rinnakkaistallenteen osoite: https://research.utu.fi/converis/portal/detail/Publication/25088184
Differential expression analysis is one of the most common types of analyses performed on various biological data (e.g. RNA-seq or mass spectrometry proteomics). It is the process that detects features, such as genes or proteins, showing statistically significant differences between the sample groups under comparison. A major challenge in the analysis is the choice of an appropriate test statistic, as different statistics have been shown to perform well in different datasets. To this end, the reproducibility-optimized test statistic (ROTS) adjusts a modified t-statistic according to the inherent properties of the data and provides a ranking of the features based on their statistical evidence for differential expression between two groups. ROTS has already been successfully applied in a range of different studies from transcriptomics to proteomics, showing competitive performance against other state-of-the-art methods. To promote its widespread use, we introduce here a Bioconductor R package for performing ROTS analysis conveniently on different types of omics data. To illustrate the benefits of ROTS in various applications, we present three case studies, involving proteomics and RNA-seq data from public repositories, including both bulk and single cell data. The package is freely available from Bioconductor (https://www.bioconductor.org/packages/ROTS).
Ladattava julkaisu This is an electronic reprint of the original article. |  |
