Logicome Profiler: Exhaustive detection of statistically significant logic relationships from comparative omics data.

ABSTRACT: Logic relationship analysis is a data mining method that comprehensively detects item triplets that satisfy logic relationships from a binary matrix dataset, such as an ortholog table in comparative genomics. Thanks to recent technological advancements, many binary matrix datasets are now being produced in genomics, transcriptomics, epigenomics, metagenomics, and many other fields for comparative purposes. However, regardless of presumed interpretability and importance of logic relationships, existing data mining methods are not based on the framework of statistical hypothesis testing. That means, the type-1 and type-2 error rates are neither controlled nor estimated. Here, we developed Logicome Profiler, which exhaustively detects statistically significant triplet logic relationships from

SUBMITTER: Fukunaga T 

PROVIDER: S-EPMC7194410 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature