CoreProbe: A Novel Algorithm for Estimating Relative Abundance Based on Metagenomic Reads.

Dongmei Ai,Hongfei Pan,Li C Xia,Ruocheng Huang

doi:10.3390/genes9060313

Abstract

With the rapid development of high-throughput sequencing technology, the analysis of metagenomic sequencing data and the accurate and efficient estimation of relative microbial abundance have become important ways to explore the microbial composition and function of microbes. In addition, the accuracy and efficiency of the relative microbial abundance estimation are closely related to the algorithm and the selection of the reference sequence for sequence alignment. We introduced the microbial core genome as the reference sequence for potential microbes in a metagenomic sample, and we constructed a finite mixture and latent Dirichlet models and used the Gibbs sampling algorithm to estimate the relative abundance of microorganisms. The simulation results showed that our approach can improve the efficiency while maintaining high accuracy and is more suitable for high-throughput metagenomic data. The new approach was implemented in our CoreProbe package which provides a pipeline for an accurate and efficient estimation of the relative abundance of microbes in a community. This tool is available free of charge from the CoreProbe’s website: Access the Docker image with the following instruction: sudo docker pull panhongfei/coreprobe:1.0.

Highlights

Microbial organisms are ubiquitous in virtually all the natural environments of the earth’s biosphere
We introduce CoreProbe, a relative abundance estimation framework for microbes that employs microbial core-genomes as references for metagenomic analysis
Our method was applied to the actual data obtained from Human Microbiome Project (HMP), and a preliminary analysis was made to support the practicability of our method

Summary

Introduction

Microbial organisms are ubiquitous in virtually all the natural environments of the earth’s biosphere. They play integral and unique roles in ecosystems [1], they are involved in the biogeochemical cycling of the earth [2], and they have a great impact on human health. Composition, and function of the microbiota cause alterations in the metabolites of the intestinal microbiota, there can be host diseases such as obesity [3], malnutrition [4] and diabetes [5]; intestinal flora disorders and irritable bowel syndrome [6], ulcerative colitis and Crohn’s disease [7,8]. Profiling the taxonomic composition using the microbial abundances of related communities is critical for understanding the microbial ecology of the environment and for human health.

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Conclusion