MetaComp: comprehensive analysis software for comparative meta-omics including comparative metagenomics

Abstract

BackgroundDuring the past decade, the development of high throughput nucleic sequencing and mass spectrometry analysis techniques have enabled the characterization of microbial communities through metagenomics, metatranscriptomics, metaproteomics and metabolomics data. To reveal the diversity of microbial communities and interactions between living conditions and microbes, it is necessary to introduce comparative analysis based upon integration of all four types of data mentioned above. Comparative meta-omics, especially comparative metageomics, has been established as a routine process to highlight the significant differences in taxon composition and functional gene abundance among microbiota samples. Meanwhile, biologists are increasingly concerning about the correlations between meta-omics features and environmental factors, which may further decipher the adaptation strategy of a microbial community.ResultsWe developed a graphical comprehensive analysis software named MetaComp comprising a series of statistical analysis approaches with visualized results for metagenomics and other meta-omics data comparison. This software is capable to read files generated by a variety of upstream programs. After data loading, analyses such as multivariate statistics, hypothesis testing of two-sample, multi-sample as well as two-group sample and a novel function—regression analysis of environmental factors are offered. Here, regression analysis regards meta-omic features as independent variable and environmental factors as dependent variables. Moreover, MetaComp is capable to automatically choose an appropriate two-group sample test based upon the traits of input abundance profiles. We further evaluate the performance of its choice, and exhibit applications for metagenomics, metaproteomics and metabolomics samples.ConclusionMetaComp, an integrative software capable for applying to all meta-omics data, originally distills the influence of living environment on microbial community by regression analysis. Moreover, since the automatically chosen two-group sample test is verified to be outperformed, MetaComp is friendly to users without adequate statistical training. These improvements are aiming to overcome the new challenges under big data era for all meta-omics data. MetaComp is available at: http://cqb.pku.edu.cn/ZhuLab/MetaComp/ and https://github.com/pzhaipku/MetaComp/.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-017-1849-8) contains supplementary material, which is available to authorized users.

Comparative Metagenomic Profiling of Viromes Associated with Four Common Mosquito Species in China

“…The extraction for the information of assigned reads, which classified them to a viral family and species, together with other statistical analyses, were conducted in R, version 3.2.5 (https://www.r-project.org/). Metagenomic comparative analysis was conducted through MetaComp (http:// cqb.pku.edu.cn/ZhuLab/MetaComp/) under the multisample statistic method (Zhai et al 2017).…”

Characteristic dysbiosis of gut microbiota of Chinese patients with diarrhea-predominant irritable bowel syndrome by an insight into the pan-microbiome

“…The phylotypes or functional taxa with significantly different abundance between two groups of HC and IBS-D were found by the Wilcoxon rank-sum test (non-parametric test, also referred to as Mann-Whitney U test) via MetaComp (Peking University, Beijing, China). [31] In the Wilcoxon rank-sum test, we first calculated the minimum of the sum of ranks of HC and IBS-D groups as …”

WHAM!: a web-based visualization suite for user-defined analysis of metagenomic shotgun sequencing data

“…can be applied to metagenomics data to easily identify and visualize biologically relevant relationships and to generate novel hypotheses. Recently developed tools, Metaviz [ 31 ], BURRITO [ 32 ] and MetaComp [ 33 ], address similar challenges, however, WHAM! has several important differences.…”

“…[ 32 ]. MetaComp has robust statistics and accepts a range of inputs, but it requires an external download and installation, which can lead to unexpected issues depending on the user’s compute platform [ 33 ]. WHAM!…”