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GSR: Simulator - rlsim
| Attribute | Value |
|---|---|
| Title | rlsim |
| Short Description | A package for simulating RNA-seq library preparation with parameter estimation |
| Long Description | The rlsim package is a collection of tools for simulating RNA-seq library construction, aiming to reproduce the most important factors which are known to introduce significant biases in the currently used protocols: hexamer priming, PCR amplification and size selection. It allows for a systematic exploration of the effects of the individual biasing factors and their interactions on downstream applications by simulating data under a variety of parameter sets. The implicit simulation model implemented in the main tool (rlsim) is inspired by the actual library preparation protocols and it is more general than the models used by the bias correction methods hence it allows for a fair assessment of their performance. Although the simulation model was kept as simple as possible in order to aid usability, it still has too many parameters to be inferred from data produced by standard RNA-seq experiments. However, simulating datasets with properties similar to specific datasets is often useful. To address this, the package provides a tool (effest) implementing simple approaches for estimating the parameters which can be recovered from standard RNA-seq data (GC-dependent amplification efficiencies, fragment size distribution, relative expression levels). |
| Version | 1.0 |
| Project Started | 2013 |
| Last Release | 11 years ago |
| Homepage | http://bit.ly/rlsim-git |
| Citations | Botond Sipos, Greg Slodkowicz, Tim Massingham, Nick Goldman, Realistic simulations reveal extensive sample-specificity of RNA-seq biases, Quantitative Biology. Genomics, 08-14-2013 |
| GSR Certification | ✔ Accessibility |
| Last evaluated | 03-12-2020 (1493 days ago) |
| Attribute Category | Attribute |
|---|---|
| Target | |
| Type of Simulated Data | RNA (Rna-seq fragments), |
| Variations | |
| Simulation Method | Other (Input transcriptome fragmentation, priming, pcr, size selection. parameter estimation from reads mapped to transcriptome.), |
| Input | |
| Data Type | |
| File format | Other (Fasta (input transcriptome). sam files (for estimating parameters). json file with empirical estimates (for simulation).), |
| Output | |
| Data Type | |
| Sequencing Reads | |
| File Format | Fasta or Fastq (Simulated rna-seq fragments.), Other (Report in json format), |
| 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 | Linux and Unix (X86_64), |
| Language | Python (Estimation tool and additional tools ), Other (Go), |
| License | GNU Public License (V3.0), |
| GSR Certification | Accessibility, Documentation, |
Number of Primary Citations: 1
Number of Non-Primary Citations: 0
No example publication using rlsim has been provided.
Please propose new citations if you are aware of publications that use this software.