Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1)
Tensorial blind source separation for improved analysis of multi-omic data
Julkaisun tekijät: Teschendorff AE, Jing H, Paul DS, Virta J, Nordhausen K
Kustantaja: BIOMED CENTRAL LTD
Julkaisuvuosi: 2018
Journal: Genome Biology
Tietokannassa oleva lehden nimi: GENOME BIOLOGY
Lehden akronyymi: GENOME BIOL
Volyymi: 19
Sivujen määrä: 18
ISSN: 1474-760X
DOI: http://dx.doi.org/10.1186/s13059-018-1455-8
Rinnakkaistallenteen osoite: https://research.utu.fi/converis/portal/detail/Publication/32116144
Tiivistelmä
There is an increased need for integrative analyses of multi-omic data. We present and benchmark a novel tensorial independent component analysis (tICA) algorithm against current state-of-the-art methods. We find that tICA outperforms competing methods in identifying biological sources of data variation at a reduced computational cost. On epigenetic data, tICA can identify methylation quantitative trait loci at high sensitivity. In the cancer context, tICA identifies gene modules whose expression variation across tumours is driven by copy-number or DNA methylation changes, but whose deregulation relative to normal tissue is independent of such alterations, a result we validate by direct analysis of individual data types.
There is an increased need for integrative analyses of multi-omic data. We present and benchmark a novel tensorial independent component analysis (tICA) algorithm against current state-of-the-art methods. We find that tICA outperforms competing methods in identifying biological sources of data variation at a reduced computational cost. On epigenetic data, tICA can identify methylation quantitative trait loci at high sensitivity. In the cancer context, tICA identifies gene modules whose expression variation across tumours is driven by copy-number or DNA methylation changes, but whose deregulation relative to normal tissue is independent of such alterations, a result we validate by direct analysis of individual data types.
Ladattava julkaisu This is an electronic reprint of the original article. |  |
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