USA flag logo/image

An Official Website of the United States Government

Computational tools to analyze SNP data from patients with mental illness

Award Information

Agency:
Department of Health and Human Services
Branch:
N/A
Award ID:
94027
Program Year/Program:
2009 / SBIR
Agency Tracking Number:
MH086192
Solicitation Year:
N/A
Solicitation Topic Code:
N/A
Solicitation Number:
N/A
Small Business Information
PARTEK, INC.
624 Trade Center Blvd, STE E Chesterfield, MO 63005-
View profile »
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
 
Phase 1
Fiscal Year: 2009
Title: Computational tools to analyze SNP data from patients with mental illness
Agency: HHS
Contract: 1R43MH086192-01
Award Amount: $243,011.00
 

Abstract:

DESCRIPTION (provided by applicant): The broad, long-term objective of the proposed research is to develop a software product that can be used to facilitate the analysis of genetic changes in order to elucidate chromosomal abnormalities that underlie disea ses such as autism spectrum disorder, bipolar disorder, and schizophrenia. Recent technological advances allow samples of DNA from patients to be analyzed on single nucleotide polymorphism (SNP) arrays, generating up to millions of data points from each sa mple. These data must be analyzed to identify chromosomal abnormalities (e.g. DNA mutations, hemizygous or homozygous deletions, or translocations) that confer risk for these diseases. Two main approaches to data analysis include copy number estimates (bas ed on the intensity of hybridization of samples to SNP arrays) and genotype analysis (revealing heterozygosity and homozygosity). Software such as Partek Genomics Suite (GS) exists to perform data analysis and visualization. A goal of this proposal is to a dd another dimension to the analysis of high density SNP data by incorporating information about the genetic relatedness of individuals into the data analysis repertoire of Partek GS. The specific aims are as follows. (1) Incorporate SNPtrio into a new Par tek GS module. This program analyzes genotype and copy number data from trios consisting of father, mother, and child and produces graphical and tabular descriptions of uniparental inheritance (e.g. uniparental isodisomy in which two copies of a chromosome or chromosomal segment are inherited from one parent; such a mechanism is known to cause a variety of mental retardation and other syndromes). (2) Incorporate SNPduo into PartekGS; this program performs pairwise analyses of SNP data sets, allowing the des cription of relatedness between individuals (by identity-by-state measurements). This is useful for a variety of purposes including identifying outliers, replicate samples, non-paternity, and confirming the genetic relatedness of members of a pedigree. (3) Incorporate a set of analytic tools that measure meiotic recombination in pedigrees consisting of one, two, or three generations. Such tools may be useful to exclude loci in association studies or to characterize mechanisms by which deletions or duplicati ons occur. The software tools described in aims (1) to (3) will be assembled into a new prototype version of Partek GS. In aim (4), this prototype will be used to analyze a set of 500,000 SNPs measured in 2,883 individuals from 700 families having two or m ore individuals affected with autism. This analysis will demonstrate the functionality of the Partek GS prototype, demonstrating the usefulness of incorporating new tools for genetic analysis to discover chromosomal abnormalities that may have roles in aut ism. PUBLIC HEALTH RELEVANCE: Newly available technologies allow the measurement of millions of variations in DNA sequence between samples from individuals with diseases (such as autism and schizophrenia) relative to unaffected individuals (control s). The proposed research is designed to create software analysis tools that will facilitate the discovery of chromosomal abnormalities in diseases. This may lead to treatments for these disorders, serving a large public health need.

Principal Investigator:

Thomas Downey

Business Contact:

Donald Meyer
Small Business Information at Submission:

PARTEK, INC.
PARTEK, INC. 12747 OLIVE BLVD, STE 205 SAINT LOUIS, MO 63141

EIN/Tax ID: 143164836
DUNS: N/A
Number of Employees: N/A
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No