Open AccessComprehensive simulation of metagenomic sequencing data with non‐uniform sampling distribution
Author(s) -
Liu Shansong,
Hua Kui,
Chen Sijie,
Zhang Xuegong
Publication year - 2018
Publication title -
quantitative biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.707
H-Index - 15
eISSN - 2095-4697
pISSN - 2095-4689
DOI - 10.1007/s40484-018-0142-9
Subject(s) - metagenomics , software , computer science , benchmarking , microbiome , computational biology , genome , data mining , sampling (signal processing) , flexibility (engineering) , biology , bioinformatics , genetics , statistics , gene , mathematics , filter (signal processing) , marketing , business , programming language , computer vision
Background Metagenomic sequencing is a complex sampling procedure from unknown mixtures of many genomes. Having metagenome data with known genome compositions is essential for both benchmarking bioinformatics software and for investigating influences of various factors on the data. Compared to data from real microbiome samples or from defined microbial mock community, simulated data with proper computational models are better for the purpose as they provide more flexibility for controlling multiple factors. Methods We developed a non‐uniform metagenomic sequencing simulation system (nuMetaSim) that is capable of mimicking various factors in real metagenomic sequencing to reflect multiple properties of real data with customizable parameter settings. Results We generated 9 comprehensive metagenomic datasets with different composition complexity from of 203 bacterial genomes and 2 archaeal genomes related with human intestine system. Conclusion The data can serve as benchmarks for comparing performance of different methods at different situations, and the software package allows users to generate simulation data that can better reflect the specific properties in their scenarios.