Evaluating replicability in microbiome data.

ABSTRACT: High-throughput sequencing is widely used to study microbial communities. However, choice of laboratory protocol is known to affect the resulting microbiome data, which has an unquantified impact on many comparisons between communities of scientific interest. We propose a novel approach to evaluating replicability in high-dimensional data and apply it to assess the cross-laboratory replicability of signals in microbiome data using the Microbiome Quality Control Project data set. We learn distinctions between samples as measured by a single laboratory and evaluate whether the same distinctions hold in data produced by other laboratories. While most sequencing laboratories can consistently distinguish between samples (median correct classification 87% on genus-level proportion data), these d

SUBMITTER: Clausen DS 

PROVIDER: S-EPMC9566336 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature