DTW4Omics: comparing patterns in biological time series.

ABSTRACT: When studying time courses of biological measurements and comparing these to other measurements eg. gene expression and phenotypic endpoints, the analysis is complicated by the fact that although the associated elements may show the same patterns of behaviour, the changes do not occur simultaneously. In these cases standard correlation-based measures of similarity will fail to find significant associations. Dynamic time warping (DTW) is a technique which can be used in these situations to find the optimal match between two time courses, which may then be assessed for its significance. We implement DTW4Omics, a tool for performing DTW in R. This tool extends existing R scripts for DTW making them applicable for "omics" datasets where thousands entities may need to be compared with a range o

SUBMITTER: Cavill R 

PROVIDER: S-EPMC3748037 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature