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Grinder specifications


Unique identifier OMICS_01508
Name Grinder
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages Perl
License GNU General Public License version 2.0
Computer skills Advanced
Stability Stable
Maintained Yes




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Publication for Grinder

Grinder citations


Using 16S rRNA gene as marker to detect unknown bacteria in microbial communities

BMC Bioinformatics
PMCID: 5751639
PMID: 29297282
DOI: 10.1186/s12859-017-1901-8

[…] enting different unknown bacteria.These mock communities were synthetically created to evaluate various aspects of our method. In our experiments, short reads from 16S rRNA genes were generated using Grinder [] using parameters for the Illumina sequencing platform. Mean read length was 150 with a standard deviation of 20. Read coverage was between 10x to 100x and the percentage of unknown bacteria […]


EnSVMB: Metagenomics Fragments Classification using Ensemble SVM and BLAST

Sci Rep
PMCID: 5573435
PMID: 28842700
DOI: 10.1038/s41598-017-09947-y

[…] errors may alter reads and make the classification problem more difficult. To evaluate the robustness of EnSVM and EnSVMB, we generate a simulated dataset with sequencing errors and mutations.We use Grinder read simulation software to generate simulated validation set with median error rate of 2%. The simulated validation set is generated based on the validation set used in Subsection Results on […]


PhylOligo: a package to identify contaminant or untargeted organism sequences in genome assemblies

PMCID: 5860033
PMID: 28637232
DOI: 10.1093/bioinformatics/btx396

[…] We evaluated the performances of PhylOligo by generating artificial contaminations on 32 contig datasets generated by GRINDER () from real Refseq genome data (see section 6.1 of for detailed protocol). The species were chosen to cover the main domain of life (archea, bacteria, fungi, protozoa and vertebrate) and dif […]


Assessment of Common and Emerging Bioinformatics Pipelines for Targeted Metagenomics

PLoS One
PMCID: 5215245
PMID: 28052134
DOI: 10.1371/journal.pone.0169563

[…] erial taxa []. Those two pairs of primers cover 82.1% and 83% of the bacterial domain for 200(V3) and 400(V4-V5) respectively, according to TestPrime (Klindworth, 2012) on the SILVA SSU r122 database.Grinder [] was used to extract amplicons from complete genomic sequences. This software fetches amplicons randomly across the several potential 16S rDNA copies within a genome sequence. Simulated ampl […]


MetaCRAST: reference guided extraction of CRISPR spacers from unassembled metagenomes

PMCID: 5592083
PMID: 28894651
DOI: 10.7717/peerj.3788
call_split See protocol

[…] ionship between CRISPR spacer detection and read length or sequencing technology, simulated acid mine drainage (AMD) and enhanced biological phosphorus removal (EBPR) metagenomes were generated using Grinder (). We generated simulated metagenomes over a range of average read lengths (100 to 600 base pairs) using models of 454 () and Illumina () errors. Following previous studies, we used a fourth- […]


Metabarcoding of Fecal Samples to Determine Herbivore Diets: A Case Study of the Endangered Pacific Pocket Mouse

PLoS One
PMCID: 5112926
PMID: 27851756
DOI: 10.1371/journal.pone.0165366

[…] th of the longest reference for the corresponding genus, unless no other reference sequence was available. This trimming resulted in 1,899 sequences representing 1,624 species and 667 genera. We used Grinder 0.5.3 [] to generate realistic sequence reads from this slightly reduced reference database. Reads were simulated with a linearly increasing error rate from 0.1 to 4.0 percent, comparable to t […]

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Grinder institution(s)
Australian Centre for Ecogenomics, School of Chemistry and Molecular Biosciences, The University of Queensland, St Lucia, QLD, Australia

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