GSR: Simulator - CAMISIM

Basic Package Attributes
AttributeValue
Title CAMISIM
Short Description Simulating metagenomes and microbial communities
Long Description CAMISIM is a software to model abundance distributions of microbial communities and to simulate corresponding shotgun metagenome datasets. It was mainly developed for the Critical Assessment of Metagenome Annotation (CAMI) challenge, but should be suitable for general use. Please don't hesitate to open a new issue if you run into problems or need help.
Project Started 2019
Last Release 5 years, 2 months ago
Homepagehttps://github.com/CAMI-challenge/CAMISIM
Citations Fritz A, Hofmann P, Majda S, Dahms E, Dröge J, Fiedler J, Lesker TR, Belmann P, DeMaere MZ, Darling AE, et al., CAMISIM: simulating metagenomes and microbial communities., Microbiome, 02-08-2019 [ Abstract, cited in PMC ]
GSR CertificationGSR-certified

Accessibility
Documentation
Application
Support

Last evaluated10-28-2021 (876 days ago)
Author verificationThe 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.
Detailed Attributes
Attribute CategoryAttribute
Target
Type of Simulated DataSequencing Reads,
VariationsOther,
Simulation MethodOther,
Input
Data Type
File formatOther,
Output
Data Type
Sequencing ReadsOther,
File FormatSAM 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
Development
Tested Platforms
LanguagePython,
LicenseOther,
GSR CertificationAccessibility, Documentation, Application, Support,

Number of Primary Citations: 1

Number of Non-Primary Citations: 2

The following 2 publications are selected examples of applications that used CAMISIM.

2023

Gabrielli M, Dai Z, Delafont V, Timmers PHA, van der Wielen PWJJ, Antonelli M, Pinto AJ, Identifying Eukaryotes and Factors Influencing Their Biogeography in Drinking Water Metagenomes., Environ Sci Technol, 03-07-2023 [Abstract]

Xu R, Rajeev S, Salvador LCM, The selection of software and database for metagenomics sequence analysis impacts the outcome of microbial profiling and pathogen detection., PLoS One, 04-07-2023 [Abstract]


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