MAPT and PAICE: Tools for time series and single time point transcriptional visualization and knowledge discovery

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Title	MAPT and PAICE: Tools for time series and single time point transcriptional visualization and knowledge discovery
Authors	Parsa Hosseini², Arianne Tremblay¹, Benjamin F Matthews¹ & Nadim W Alkharouf³*
Affiliation	¹U.S Department of Agriculture - Soybean Genomics / Improvement Laboratory, 10300 Baltimore Avenue, Beltsville, MD; ²Dept, Bioinformatics and Computational Biology, George Mason University, 10900 University Blvd, Manassas, VA; ³Dept, Computer and Information Science; Towson University, 8000 York Road, Towson, MD
Email	nalkharouf@towson.edu; *Corresponding author
Article Type	Software
Date	Received February 29, 2012; Accepted March 21, 2012, Published March 31, 2012
Abstract	With the advent of next-generation sequencing, -omics fields such as transcriptomics have experienced increases in data throughput on the order of magnitudes. In terms of analyzing and visually representing these huge datasets, an intuitive and computationally tractable approach is to map quantified transcript expression onto biochemical pathways while employing data-mining and visualization principles to accelerate knowledge discovery. We present two cross-platform tools: MAPT (Mapping and Analysis of Pathways through Time) and PAICE (Pathway Analysis and Integrated Coloring of Experiments), an easy to use analysis suite to facilitate time series and single time point transcriptomics analysis. In unison, MAPT and PAICE serve as a visual workbench for transcriptomics knowledge discovery, data-mining and functional annotation. Both PAICE and MAPT are two distinct but yet inextricably linked tools. The former is specifically designed to map EC accessions onto KEGG pathways while handling multiple gene copies, detection-call analysis, as well as UN/annotated EC accessions lacking quantifiable expression. The latter tool integrates PAICE datasets to drive visualization, annotation, and data-mining.
Availability	http://sourceforge.net/projects/paice/ and http://sourceforge.net/projects/mapt/
Citation	*Hosseini et al.* Bioinformation 8(6): 287-289(2012)
Edited by	P Kangueane
ISSN	0973-2063
Publisher	Biomedical Informatics
License	This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.