Basic Package Attributes
Short Description The Flux Simulator aims at providing a deterministic in silico reproduction of the experimental pipelines for RNA-Seq, employing a minimal set of parameters.
Long Description The FluxSimulator is the part of the FLUX project that aims at providing an in silico reproduction of the experimental pipelines for RNA-Seq, adopting a minimal set of parameters. Corresponding models were established after analyzing RNA-Seq experiments from different cell types, sample preparation protocols and sequencing platforms. The first step of the FLUX project is-in fact-a transcriptome simulator. Subsequently, common sources of systematic bias in the abundance and distribution of produced reads are mimicked-whether they incur during library construction, or, in the sequencing process. The FluxSimulator provides a flexible base to design benchmark experiments based on the new sequencing technologies, as for instance abundance predictions of the FluxCapacitor.
Version 1.1
Project Started 2010
Last Release 8 years, 1 month ago
Citations Griebel T, Zacher B, Ribeca P, Raineri E, Lacroix V, Guigó R, Sammeth M, Modelling and simulating generic RNA-Seq experiments with the flux simulator., Nucleic Acids Res, 11-01-2012 [ Abstract, cited in PMC ]
GSR CertificationGSR-certified


Last evaluated09-07-2017 (1135 days ago)
Detailed Attributes
Attribute CategoryAttribute
Type of Simulated DataGenotype at Genetic Markers (After version 1.1), Diploid DNA Sequence (After version 1.1), Haploid DNA Sequence, RNA (Simulating number of rna molecules in a simulated cell type, and location and abundance of rna-seq reads), Sex Chromosomes, Mitochondrial DNA, Protein Sequence,
VariationsBiallelic Marker (After version 1.1), Multiallelic Marker (After version 1.1), Single Nucleotide Variation (After version 1.1), Insertion and Deletion (After version 1.1), Alternative Splicing (Produces convoluted read stacks from overlapping regions of alternatively processed transcripts.), Missing Genotypes (After version 1.1), Genotype or Sequencing Error, Other (Variations of rna read abundances introduced by technical processes such as nebulization, hydrolysis, reverse transcription, and pcr),
Simulation MethodForward-time (Different molecule populations are produced generation-by-generation during each step of the library preparation.), Resample Existing Data (Sequencing error models are inferred empirically from read mappings.), Other (Rejection-acception subsampling and metropolis-hastings monte-carlo markov chain.),
Data TypeEmpirical (Read mappings to generate custom error models of the sequencing process, and empirical size distributions after gel segregation), Other (Input of annotated gene models (required) and the genomic sequence (optional).),
File formatProgram Specific (Par (parameter file) format with flux simulator specific parameters described by (key,value) pairs), Other (Gtf (gene transfer format), fasta format (genome reference sequence)),
Data TypeGenotype or Sequence, Phenotypic Trait (The simulated population of expressed rna sequences is a quantitative trait of the simulated cell.),
Sequencing ReadsOther (Chi-square and coefficient of variation for read coverage of each transcript (.pro file). statistics of molecule populations after each step),
File FormatFasta or Fastq, Program Specific (The flux simulator outputs intermediary fragments of simulated library (.lib).),
Sample TypeRandom or Independent,
Trait TypeQuantitative (The phenotype of the cell is reflected by the simulated read abundances of expressed transcripts.), Multiple (Read abundances are gene- and transcript-specific.),
Evolutionary Features
Population Size Changes
Gene Flow
Life Cycle
Mating System
Natural Selection
Mutation Models
Events Allowed
InterfaceCommand-line, Graphical User Interface,
Tested PlatformsWindows, Mac OS X, Linux and Unix, Solaris,
GSR CertificationAccessibility, Documentation, Application, Support,

The following 5 publications are selected examples of applications that used FLUX SIMULATOR.


Zhou J, Ma S, Wang D, Zeng J, Jiang T, FreePSI: an alignment-free approach to estimating exon-inclusion ratios without a reference transcriptome., Nucleic Acids Res, 01-25-2018 [Abstract]


Zhang C, Zhang B, Lin LL, Zhao S, Evaluation and comparison of computational tools for RNA-seq isoform quantification., BMC Genomics, 08-07-2017 [Abstract]

Liu Y, Wu P, Zhou J, Johnson-Pais TL, Lai Z, Chowdhury WH, Rodriguez R, Chen Y, XBSeq2: a fast and accurate quantification of differential expression and differential polyadenylation., BMC Bioinformatics, 10-03-2017 [Abstract]

Liu R, Dickerson J, Strawberry: Fast and accurate genome-guided transcript reconstruction and quantification from RNA-Seq., PLoS Comput Biol, 11-01-2017 [Abstract]

Pai AA, Henriques T, McCue K, Burkholder A, Adelman K, Burge CB, The kinetics of pre-mRNA splicing in the <i>Drosophila</i> genome and the influence of gene architecture., Elife, 12-27-2017 [Abstract]

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