pIRS statistics

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pIRS specifications


Unique identifier OMICS_00254
Name pIRS
Alternative name profile based Illumina pair-end Reads Simulator
Software type Application/Script, Package/Module
Interface Command line interface
Restrictions to use None
Biological technology Illumina
Operating system Unix/Linux
Programming languages C++, Perl
License BSD 2-clause “Simplified” License, GNU General Public License version 2.0
Computer skills Advanced
Version 2.0.2
Stability Stable
Source code URL https://codeload.github.com/galaxy001/pirs/tar.gz/v2.0.2
Maintained Yes



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  • person_outline Wei Fan <>

Publication for profile based Illumina pair-end Reads Simulator

pIRS in pipelines

PMCID: 5587753
PMID: 28666376
DOI: 10.1093/nar/gkx574

[…] (similar to the requirements imposed for our analyses with real datasets) before calculation of performance metrics. in each of these simulations, illumina short-read sequences were simulated using pirs (). the average coverage of the sequences was varied between 5-fold to 39-fold, and baitstr was run using k-mer lengths between 9 and 31 bps for each of those coverage values. […]

PMCID: 3610916
PMID: 23555231
DOI: 10.1371/journal.pcbi.1003000

[…] heterozygous loci contain only two nucleotide variants . the heterozygosity had to be supported by ≥4 reads and located >250 bp from contig ends., simulated reads were generated using the program pirs v.1.1.0 with the settings ‘-a 0 -m 100 -l 100 -x 100 -v 10’. simulated reads were aligned with the masked genome using bowtie2 with the setting ‘--very-sensitive’. rna-seq data of gs […]

PMCID: 3667578
PMID: 23741619
DOI: 10.7554/eLife.00731.027

[…] sites is 1/2, while we expect two modes for triploid genomes, at 1/3 and 2/3, and four modes for tetraploid genomes, at 1/4, 1/2 and 3/4 (). we simulated genomes with different ploidy levels using pirs (), based on two strains, p. infestans t30-4 and ec3527. the snps used for the construction of two simulated chromosomes were determined with samtools v0.1.8 mpileup and bcftools v0.1.17 (). […]

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pIRS in publications

PMCID: 5125660
PMID: 27893777
DOI: 10.1371/journal.pone.0167047

[…] of existing software packages available for generating synthetic ngs read data, each tending to specialize on a particular attribute of a dataset. for example, art [], curesim [], gemsim [], and pirs [] focus on realistically emulating the biases inherent in the base calling of various next-generation sequencing (ngs) platforms. other simulators seek to incorporate more sophisticated models […]

PMCID: 4937318
PMID: 27095193
DOI: 10.1093/nar/gkw284

[…] depth for each clone was set as 30× to guarantee that more than 99% of base pairs in the clone were covered by at least 15 sequence reads. after generating artificial reads for each pool by running pirs, we pooled together all the sequencing data and called the variants using gatk 3.4–46 () (supplementary figure s10). the results of 24 and 560 pools were very similar, because variant calling […]

PMCID: 4493402
PMID: 26217378
DOI: 10.3389/fgene.2015.00235

[…] (), celsim (), and gensim (). alternatively, fixed quality values are generated by grinder (). correct bases are assigned a quality score of 30 and error positions are assigned a score of 10. the pirs by uses quality scores from an existing sequence dataset. while this approach is more representative of the distribution of quality scores in a sequencing dataset, it assumes the quality scores […]

PMCID: 4476701
PMID: 26098299
DOI: 10.1371/journal.pone.0129059

[…] genome coverage and viral classes (see )., a database of 62 human virus chromatids from 35 distinct viruses were used to generate simulated illumina read pairs (10x coverage depth) with the use of pirs (methods). these paired reads (167,004) were combined with 16.7 million illumina paired sequence reads from a ‘clean’ healthy liver sample (methods). using the mapping algorithms clc, bwa […]

PMCID: 4059239
PMID: 24531727
DOI: 10.1534/g3.114.010264

[…] under project accession number srp031655., to generate sequences that incorporate known error tendencies of the illumina technology, reads from all individuals were simulated using the program pirs (). these simulated data include nucleotide errors, indel errors, variance in the mean insert size of paired-end sequences, and the gc-bias in read-depth typical of illumina data (). although […]

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pIRS institution(s)
BGI-Shenzhen, Shenzhen, China; Biodynamic Optical Imaging Center, Peking University, Beijing, China; Medical Population Genetics Program, Broad Institute, Cambridge, MA, USA
pIRS funding source(s)
Supported by Basic Research Program of Shenzhen City (grants JC2010526019); Key Laboratory Project of Shenzhen City (grants CXB200903110066A and CXB201108250096A); Shenzhen Key Laboratory of Gene Bank for National Life Science.

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