NeSSM: A Next-Generation Sequencing Simulator for Metagenomics

Abstract

BackgroundMetagenomics can reveal the vast majority of microbes that have been missed by traditional cultivation-based methods. Due to its extremely wide range of application areas, fast metagenome sequencing simulation systems with high fidelity are in great demand to facilitate the development and comparison of metagenomics analysis tools.ResultsWe present here a customizable metagenome simulation system: NeSSM (Next-generation Sequencing Simulator for Metagenomics). Combining complete genomes currently available, a community composition table, and sequencing parameters, it can simulate metagenome sequencing better than existing systems. Sequencing error models based on the explicit distribution of errors at each base and sequencing coverage bias are incorporated in the simulation. In order to improve the fidelity of simulation, tools are provided by NeSSM to estimate the sequencing error models, sequencing coverage bias and the community composition directly from existing metagenome sequencing data. Currently, NeSSM supports single-end and pair-end sequencing for both 454 and Illumina platforms. In addition, a GPU (graphics processing units) version of NeSSM is also developed to accelerate the simulation. By comparing the simulated sequencing data from NeSSM with experimental metagenome sequencing data, we have demonstrated that NeSSM performs better in many aspects than existing popular metagenome simulators, such as MetaSim, GemSIM and Grinder. The GPU version of NeSSM is more than one-order of magnitude faster than MetaSim.ConclusionsNeSSM is a fast simulation system for high-throughput metagenome sequencing. It can be helpful to develop tools and evaluate strategies for metagenomics analysis and it’s freely available for academic users at http://cbb.sjtu.edu.cn/~ccwei/pub/software/NeSSM.php.

Quality Control of Expression Profiling Data

“…While quality control methods were previously suggested, they only focussed on the genome (potentially missing alternatively spliced variants that would have been detected by studying the transcriptome) [80,81], or on the proteome (potentially missing mRNAs whose translation is downregulated by microRNAs [83,84] or covered aspects of the data such as GC content [40], noise [12,13] source material quality [62,63,67,70,86], different experimental methods [64][65][66][71][72][73][74][76][77][78][79] or read quality [87][88][89][90][91][92][93][94][95], with few investigations focusing on the tissuespecificity issues [75,96], even when two or more methods were used in the same study [97][98][99][100][101]. A common shortcoming of many previous attempts is that tissue specificity of the genes was reported [102][103][104][105][106][1...…”

IMP: a pipeline for reproducible reference-independent integrated metagenomic and metatranscriptomic analyses

“…A complementary metagenome was simulated using the same set of 73 bacterial genomes used for the aforementioned simulated MT [12]. Simulated reads were obtained using the NeSSM MG simulator (default settings) [79]. The simulated mock community is designated as SM within this article [79].…”

“…Simulated reads were obtained using the NeSSM MG simulator (default settings) [79]. The simulated mock community is designated as SM within this article [79]. The simulated data along with the corresponding reference genomes used to generate the MG data are made available via LCSB WebDav (https://webdav-r3lab.uni.lu/public/R3lab/IMP/datasets/) and is archived on Zenodo [80].…”

Sim3C: simulation of HiC and Meta3C proximity ligation sequencing technologies

“…It offers the possibility to explore data characteristics as a near 16 continuum and subject software to a previously unavailable degree of testing 17 thoroughness.…”

“…From read simulation in isolation, field advancements such as 22 metagenomics have been accompanied soon after by simulators reflecting their specific 23 data characteristics and evolving experimental methodology [2,16,34]. 24 We introduce Sim3C, a software package designed to simulate data generated by HiC 25 and other 3C-based proximity ligation (PL) sequencing protocols.…”