DRAMS: A tool to detect and re-align mixed-up samples for integrative studies of multi-omics data.

ABSTRACT: Studies of complex disorders benefit from integrative analyses of multiple omics data. Yet, sample mix-ups frequently occur in multi-omics studies, weakening statistical power and risking false findings. Accurately aligning sample information, genotype, and corresponding omics data is critical for integrative analyses. We developed DRAMS (https://github.com/Yi-Jiang/DRAMS) to Detect and Re-Align Mixed-up Samples to address the sample mix-up problem. It uses a logistic regression model followed by a modified topological sorting algorithm to identify the potential true IDs based on data relationships of multi-omics. According to tests using simulated data, the more types of omics data used or the smaller the proportion of mix-ups, the better that DRAMS performs. Applying DRAMS to real data f

SUBMITTER: Jiang Y 

PROVIDER: S-EPMC7179940 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature