Information Scale Correction for Varying Length Amplicons Improves Eukaryotic Microbiome Data Integration.

ABSTRACT: The integration and reanalysis of big data provide valuable insights into microbiome studies. However, the significant difference in information scale between amplicon data poses a key challenge in data analysis. Therefore, reducing batch effects is crucial to enhance data integration for large-scale molecular ecology data. To achieve this, the information scale correction (ISC) step, involving cutting different length amplicons into the same sub-region, is essential. In this study, we used the Hidden Markov model (HMM) method to extract 11 different 18S rRNA gene v4 region amplicon datasets with 578 samples in total. The length of the amplicons ranged from 344 bp to 720 bp, depending on the primer position. By comparing the information scale correction of amplicons with varying lengths, w

SUBMITTER: Zhou T 

PROVIDER: S-EPMC10146031 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature