Soft windowing application to improve analysis of high-throughput phenotyping data.

ABSTRACT:

Motivation

High-throughput phenomic projects generate complex data from small treatment and large control groups that increase the power of the analyses but introduce variation over time. A method is needed to utlize a set of temporally local controls that maximizes analytic power while minimizing noise from unspecified environmental factors.

Results

Here we introduce 'soft windowing', a methodological approach that selects a window of time that includes the most appropriate controls for analysis. Using phenotype data from the International Mouse Phenotyping Consortium (IMPC), adaptive windows were applied such that control data collected proximally to mutants were assigned the maximal weight, while data collected earlier or later had less weight. We applied this method to I

SUBMITTER: Haselimashhadi H 

PROVIDER: S-EPMC7115897 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature