NASP is a pipeline for analysis of genomic data. It is a suite of tools meant to collect and report on statistically-relevant high-confidence positions in a collection of genomes, with emphasis on variant positions, especially single nucleotide polymorphisms (SNPs). NASP expects some combination of files in FASTA, FASTQ, SAM, BAM, and VCF format as input, and will produce output files also in those formats. As NASP is a pipeline, it expects to link a set of external tools (usually installed separately) to complete specific analysis tasks.

Usage depends upon the installation method used on your system, and the user interface you select. For standard installations with the command-line interface, you would collect (or symbolically link) all of your input files into a folder, and then invoke the command-line interface from that folder. Expected usage for the command-line interface is:

nasp.py [output_folder]

You will then be prompted to answer a few questions about your analysis.

Optionally, if you are re-running a previous analysis with the same (or similar) options, you can pass in an xml-based configuration file (this is written out to your output_folder after running the command-line interface) using the format:

nasp.py --config

See the main page for documentation (http://tgennorth.github.io/NASP/).

For information about external tools that are required, or can be utilized, and those versions that have been tested to work with NASP, refer to the main NASP page (http://tgennorth.github.io/NASP/)

Copyright © The Translational Genomics Research Institute See the included "LICENSE" document.

PUBLICATION: --------

Please read our paper for more information:

Jason W. Sahl, Darrin Lemmer, Jason Travis, James M. Schupp, John D. Gillece, Maliha Aziz, Elizabeth M. Driebe, Kevin P. Drees, Nathan D. Hicks, Charles Hall Davis Williamson, Crystal M. Hepp, David Earl Smith, Chandler Roe, David M. Engelthaler, David M. Wagner, Paul Keim

"NASP: an accurate, rapid method for the identification of SNPs in WGS datasets that supports flexible input and output formats". Published Ahead of Print: 21 June, 2016 Microbial Genomics doi: 10.1099/mgen.0.000074 (http://mgen.microbiologyresearch.org/content/journal/mgen/10.1099/mgen.0.000074)