Title

pkDACLASS: Open source software for analyzing MALDI-TOF data  

Authors

Juliet Ndukum¹, Mourad Atlas^{1, 2}, Susmita Datta¹* 

Affiliation

¹Department of Bioinformatics and Biostatistics, School of Public Health and Information Sciences, University of Louisville, Louisville, KY 40202; ²FDA/CDRH, Building 66, Room 3223, 10903 New Hampshire Avenue, Silver Spring, MD 20993-0002 

Email

susmdatta@gmail.com; *Corresponding author

Article Type

Software

Date

Received February 07, 2011; Accepted February 11, 2011; Published March 02, 2011

In recent years, mass spectrometry has become one of the core technologies for high throughput proteomic profiling in biomedical research. However, reproducibility of the results using this technology was in question. It has been realized that sophisticated automatic signal processing algorithms using advanced statistical procedures are needed to analyze high resolution and high dimensional proteomic data, e.g., Matrix-Assisted Laser Desorption/Ionization Time-of-Flight (MALDI-TOF) data. In this paper we present a software package-pkDACLASS based on R which provides a complete data analysis solution for users of MALDI-TOF raw data. Complete data analysis comprises data preprocessing, monoisotopic peak detection through statistical model fitting and testing, alignment of the monoisotopic peaks for multiple samples and classification of the normal and diseased samples through the detected peaks. The software provides flexibility to the users to accomplish the complete and integrated analysis in one step or conduct analysis as a flexible platform and reveal the results at each and every step of the analysis.  

Keywords

MALDI-TOF, proteome research, complete data analysis, R package

Availability

http://cran.r-project.org/web/packages/pkDACLASS/index.html

Citation

Ndukum et al. Bioinformation 6(1): 45-47 (2011)

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.