Temporal ordering of omics and multiomic events inferred from time-series data

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作者：
Sandeep Kaur
Timothy J. Peters
Pengyi Yang
Laurence Don Wai Luu
Jenny Vuong
James R. Krycer
Seán I. O’Donoghue
机构：
[1] Garvan Institute of Medical Research,
[2] University of New South Wales,undefined
[3] School of Mathematics and Statistics,undefined
[4] The University of Sydney,undefined
[5] Children’s Medical Research Institute,undefined
[6] Commonwealth Scientific and Industrial Research Organisation,undefined
[7] School of Life and Environmental Sciences,undefined
[8] The University of Sydney,undefined
来源：
npj Systems Biology and Applications | / 6卷
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摘要：
Temporal changes in omics events can now be routinely measured; however, current analysis methods are often inadequate, especially for multiomics experiments. We report a novel analysis method that can infer event ordering at better temporal resolution than the experiment, and integrates omic events into two concise visualizations (event maps and sparklines). Testing our method gave results well-correlated with prior knowledge and indicated it streamlines analysis of time-series data.
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