We further evaluate the performance of its choice, and exhibit applications for metagenomics, metaproteomics and metabolomics samples. Moreover, MetaComp is capable to automatically choose an appropriate two-group sample test based upon the traits of input abundance profiles. Here, regression analysis regards meta-omic features as independent variable and environmental factors as dependent variables. 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. This software is capable to read files generated by a variety of upstream programs. We 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. 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. 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. 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. Zhai, Peng Yang, Longshu Guo, Xiao Wang, Zhe Guo, Jiangtao Wang, Xiaoqi Zhu, HuaiqiuÄuring 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. MetaComp: comprehensive analysis software for comparative meta-omics including comparative metagenomics.
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