Abstract
MOCAT is a highly configurable, modular pipeline for fast, standardized processing of single or paired-end sequencing data generated by the Illumina platform. The pipeline uses state-of-the-art programs to quality control, map, and assemble reads from metagenomic samples sequenced at a depth of several billion base pairs, and predict protein-coding genes on assembled metagenomes. Mapping against reference databases allows for read extraction or removal, as well as abundance calculations. Relevant statistics for each processing step can be summarized into multi-sheet Excel documents and queryable SQL databases. MOCAT runs on UNIX machines and integrates seamlessly with the SGE and PBS queuing systems, commonly used to process large datasets. The open source code and modular architecture allow users to modify or exchange the programs that are utilized in the various processing steps. Individual processing steps and parameters were benchmarked and tested on artificial, real, and simulated metagenomes resulting in an improvement of selected quality metrics. MOCAT can be freely downloaded at http://www.bork.embl.de/mocat/.
| Original language | English |
|---|---|
| Journal | PLOS ONE |
| Volume | 7 |
| Issue number | 10 |
| Pages (from-to) | e47656 |
| ISSN | 1932-6203 |
| DOIs | |
| Publication status | Published - 17 Oct 2012 |
| Externally published | Yes |
Keywords
- Computational Biology
- Computer Simulation
- Databases, Genetic
- Gastrointestinal Tract
- Genes
- Humans
- Metagenome
- Metagenomics
- Reference Standards
- Sequence Analysis, DNA
- Software
- Statistics as Topic