Metastats Analysis

What is Metastats Analysis?

Differentially abundant features analysis is based on the obtained community abundance data, using rigorous statistical methods to detect the two groups of microbial communities that show differences in abundance, and perform multiple hypothesis testing and false discovery rate (FDR) analysis of rare frequency data. The significance of the observed difference can be assessed. Different taxonomic levels such as phylum, class, order, family and genera can be selected for analysis. Differentially abundant features analysis was performed on the two sets of samples at different taxonomic levels, and the significant differences of the low taxonomic level species included in the high taxonomic level were sorted out. Metastats is a statistical method whose main purpose is to identify the richly differentiated features in metagenomic and 16S rRNA sequence data sets. The program uses non-parametric t-test, Fisher's exact test and false discovery rate (FDR) to provide users with a prioritized list of interesting features.

Overall solutions

CD ComputaBio provides differential abundance analysis of taxa, designed to detect differences in taxa composition between samples or conditions. The results of this method are important in many areas of microbiology: in ecology, to detect differences between samples with different conditions; in medicine, to prove the efficacy of antibiotic drugs.

All differential abundance analyses can be divided into three steps:

• Functional Annotation or Taxonomic Classification.
• Quantifying the abundance for each feature.
• Evaluating the statistical significance with an appropriate test.

Software and algorithm

Matastats

Our services

CD ComputaBio' metastats analysis service can significantly reduce the cost and labor of the subsequent experiments. Metastats analysis service is a personalized and customized innovative scientific research service. Each project needs to be evaluated before the corresponding analysis plan and price can be determined. If you want to know more about service prices or technical details, please feel free to contact us.

Reference:

1. Tingting Wang, Guoxiang Cai, et al. Structural segregation of gut microbiota between colorectal cancer patients and healthy volunteers. The ISME Journal advance online publication. 2011.

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