Grinder

Features

• shotgun or amplicon (e.g. 16S rRNA) read libraries
• omics support to generate genomic, transcriptomic, proteomic, metagenomic, metatranscriptomic or metaproteomic datasets
• arbitrary read length distribution and number of reads
• simulation of PCR and sequencing errors (chimeras, point mutations, homopolymers)
• support for paired-end (mate pair) datasets
• specific rank-abundance settings or manually given abundance for each genome, gene or protein
• creation of datasets with a given richness (alpha diversity)
• related datasets can share a variable number of genomes (beta diversity)
• modeling of the bias created by varying genome lengths or gene copy number
• profile mechanism to store preferred options
• available to biologists or power users through multiple interfaces: GUI, CLI and API

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