This project seeks to continue the development and maintenance of the dChip software, which analyzes and visualizes oligonucleotide gene expression and SNP (single nucleotide polymorphism) microarray data. We have developed dChip as a software package to encapsulate many methods developed by us and others for microarray data analysis and visualization. dChip has been adopted as a major software package for analyzing expression and SNP microarray data. dChip has been continuously developed and enhanced since 2001, with more than 250 documented function updates. Its friendly user interface and diverse function modules has benefited many biomedical researchers. We are committed to maintain and develop dChip and propose the following specific aims in this application. (1) We will enhance the dChip infrastructure to extend dChip to analyze large number of arrays and probe sets, to automate preliminary analysis procedures to rapidly analyze one or multiple large datasets, to develop and maintain functions to support other microarray platforms, data formats and software packages, and to develop dChip versions running on Windows 64-bit system and Unix platform. (2) We will implement new function modules for expression, SNP and exon microarray data, including utilizing probe sequence information when computing expression or copy number signals, computing and visualizing SNP alternation scores and for clustering samples and chromosomal regions, integrating gene expression and SNP array data for same biological samples, and processing exon microarray data and visualizing array data with sub-gene level information. (3) We will provide proficient and timely user support on dChip usage through mailing list and web site, maintain the existing dChip codes and interact closely with local dChip users and microarray facilities. In summary, dChip is a tool that facilitates integrative genomics of large amount of microarray datasets arising from all fields of biomedical research. We are dedicated to maintain and develop dChip in the coming years to benefit thousands of dChip users. PUBLIC HEALTH Relevance: The gene expression and SNP microarrays will help to provide more tailored and effective treatment to patients in the future. To support biomedical research using these arrays it is important to create and maintain user-friendly software packages that are both freely available and capable of analyzing and integrating large expression and SNP microarray datasets. Through our endeavor to continue to maintain and develop dChip and provide dedicated user support, we make dChip an attractive alternative to commercial software packages for all biomedical scientists in the current competitive environment of NIH funding.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
3R01GM077122-02S1
Application #
7942613
Study Section
Special Emphasis Panel (ZRG1-BST-Q (01))
Program Officer
Remington, Karin A
Project Start
2009-09-30
Project End
2011-02-28
Budget Start
2009-09-30
Budget End
2011-02-28
Support Year
2
Fiscal Year
2009
Total Cost
$226,040
Indirect Cost
Name
Dana-Farber Cancer Institute
Department
Type
DUNS #
076580745
City
Boston
State
MA
Country
United States
Zip Code
02215
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Li, Yingxiang; Wang, Xujun; Zheng, Haiyang et al. (2013) Classify hyperdiploidy status of multiple myeloma patients using gene expression profiles. PLoS One 8:e58809
Sung, Chang Kyoo; Yim, Hyungshin; Gu, Hongcang et al. (2012) The polyoma virus large T binding protein p150 is a transcriptional repressor of c-MYC. PLoS One 7:e46486
Yan, Zhenyu; Shah, Parantu K; Amin, Samir B et al. (2012) Integrative analysis of gene and miRNA expression profiles with transcription factor-miRNA feed-forward loops identifies regulators in human cancers. Nucleic Acids Res 40:e135
Huang, Norman; Shah, Parantu K; Li, Cheng (2012) Lessons from a decade of integrating cancer copy number alterations with gene expression profiles. Brief Bioinform 13:305-16
Amin, Samir B; Shah, Parantu K; Yan, Aimin et al. (2011) The dChip survival analysis module for microarray data. BMC Bioinformatics 12:72
Chen, Min; Wang, Kai; Zhang, Liang et al. (2011) The discovery of putative urine markers for the specific detection of prostate tumor by integrative mining of public genomic profiles. PLoS One 6:e28552

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