Reptile

Description

reptile website  

Reptile is a software developed in C++ for correcting sequencing errors in short reads from next-gen sequencing platforms. Reptile has several favorable properties:

• Memory efficiency. Reptile can process input data with sizes larger than main memory. For instance, to process a 160x coverage (3.8GB) Illumina data for E. coli it requires only ~1GB memory, which is easily available in a desktop computer.
• High speed. Processing Illumina data for a microbe typically takes 0.5hr ~ 2hrs, depending on the number and the quality of reads.
• Can handle reads containing non-acgt characters and reads with non-equal length.
• Makes simple use of quality score information.
• Reptile has been developed by Xiao Yang, Karin Dorman and Srinivas Aluru.

Upstream documentation for reptile. Template:App Location

Available Versions

• 1.1 (serial, and parallelized OMP and Intel/OMP versions)

Running the application using modules

To use reptile with the environment modules system at HPC the following commands are available:

Get module information for reptile:

$module spider reptile

Load the default application module:

$module load reptile

The modulefile for this software adds the directory with executable files to the shell execution PATH and sets the following environment variables:

• HPC_REPTILE_DIR - directory where reptile is located.
• HPC_REPTILE_BIN - Executable directory
• HPC_REPTILE_CONF - Sample configuration files

How To Run

Make sure that the environmental variable OMP_NUM_THREADS is set to the number of threads you wish to use when executing Reptile when using the reptile-omp binary.

There is a reptile tutorial written by Daniel S. Standage.

The available binaries and scripts include:

fastq-converter reptile_merger reptile-omp reptile-omp-intel reptile-v1.1 seq-analy.

Sample configuration files are in $HPC_REPTILE_CONF

Citation

If you publish research that uses reptile you have to cite it as follows: X. Yang, K. Dorman and S. Aluru, “Reptile: Representative tiling for short read error correction”, Bioinformatics, 26(20), 2526-2533, 2010.