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GSR: Simulator - NeSSM
| Attribute | Value |
|---|---|
| Title | NeSSM |
| Short Description | A Next-Generation Sequencing Simulator for Metagenomics |
| Long Description | NeSSM is a tool to generate Next-Generation Sequencing (NGS) reads with parameters set by users. The goal of NeSSM is to generate metagenome sequencing reads close to the reality. Currently, 454, Illumina sequencing platforms are supported. It can help develop methods or systems for metagenomics analysis. |
| Last Release | 11 years, 10 months ago |
| Homepage | http://cbb.sjtu.edu.cn/~ccwei/pub/software/NeSSM.php |
| Citations | Jia B, Xuan L, Cai K, Hu Z, Ma L, Wei C, NeSSM: a Next-generation Sequencing Simulator for Metagenomics., PLoS One, Oct. 4, 2013 [ Abstract, cited in PMC ] |
| GSR Certification | Accessibility |
| Last evaluated | May 13, 2021 (1561 days ago) |
| Author verification | The basic description provided was derived from a website or publications by the GSR team and has not yet been verified by the simulation author. To modify this entry or add more information, propose changes to this simulator. |
| Attribute Category | Attribute |
|---|---|
| Target | |
| Type of Simulated Data | Sequencing Reads, |
| Variations | |
| Simulation Method | Resample Existing Data, |
| Input | |
| Data Type | |
| File format | |
| Output | |
| Data Type | |
| Sequencing Reads | |
| File Format | SAM or BAM, |
| Sample Type | |
| Phenotype | |
| Trait Type | |
| Determinants | |
| Evolutionary Features | |
| Demographic | |
| Population Size Changes | |
| Gene Flow | |
| Spatiality | |
| Life Cycle | |
| Mating System | |
| Fecundity | |
| Natural Selection | |
| Determinant | |
| Models | |
| Recombination | |
| Mutation Models | |
| Events Allowed | |
| Other | |
| Interface | Command-line, |
| Development | |
| Tested Platforms | |
| Language | C or C++, Perl, |
| License | |
| GSR Certification | Documentation, Application, |
Number of Primary Citations: 1
Number of Non-Primary Citations: 2
The following 2 publications are selected examples of applications that used NeSSM.
2023
Satoh S, Tanaka R, Yokono M, Endoh D, Yabuki T, Tanaka A, Phylogeny analysis of whole protein-coding genes in metagenomic data detected an environmental gradient for the microbiota., PLoS One, Feb. 2, 2023 [Abstract]
2022
Gupta VK, Bakshi U, Chang D, Lee AR, Davis JM 3rd, Chandrasekaran S, Jin YS, Freeman MF, Sung J, TaxiBGC: a Taxonomy-Guided Approach for Profiling Experimentally Characterized Microbial Biosynthetic Gene Clusters and Secondary Metabolite Production Potential in Metagenomes., mSystems, Dec. 20, 2022 [Abstract]