GRAMMy Genome Relative Abundance using Mixture Models
Download

GRAMMy Ranking & Summary

GRAMMy Tags

Python library genome metagenomic abundance Mixture Models metagenomic abundance

GRAMMy Description

Genome Relative Abundance using Mixture Models GRAMMy is a Python module that provides tools for metagenomic abundance estimation based on read probability partitions (alignment or composition based).GRAMMy is a computational framework developed for Genome Relative Abundance using Mixture Model theory (GRAMMy) based estimation. Accurate estimation of microbial community composition based on metagenomic sequencing data is fundamental for metagenomics analysis.Prevalent estimation methods are mainly based on directly summarizing alignment results or its variants; often result in biased and/or unstable estimates. We developed the Genome Relative Abundance using Mixture Model theory (GRAMMy) approach estimate genome relative abundance based on shotgun reads.GRAMMy has been demonstrated to give estimates that are accurate and robust across both simulated and real read benchmark datasets. Requirements: · Python

GRAMMy Related Software