Computational tools to analyze SNP data from patients with mental illness

描述（由申请人提供）：拟议研究的广泛、长期目标是开发和销售一种商业软件产品，该产品可用于促进遗传变化的分析，以阐明导致自闭症谱系障碍、双相情感障碍和精神分裂症等疾病的染色体异常。最近的技术进步允许对患者的DNA样本进行单核苷酸多态性（SNP）阵列分析，从每个样本中产生多达数百万个数据点。与此同时，全基因组（或全外显子组）的下一代测序（NGS）允许确定来自患有精神健康（或其他）疾病的个体的序列数据，以及来自受影响和未受影响的家庭成员的序列数据。必须对这些数据进行分析，以确定导致这些疾病风险的染色体异常（例如DNA突变、半合子或纯合子缺失或易位）。Partek Genomics Suite （GS）等软件提供了一套强大的工具来执行数据分析和可视化。该提案的目标是通过引入创新的、实用的软件模块来增强Partek GS和Partek Flow的商业产品，这些软件模块可以在基于SNP和/或NGS数据的研究中定义遗传相关性。具体目标1是开发和纳入基于SNP数据（包括系谱和大群体数据集）的遗传相关性测定方法。这些方法允许以高精度确定数据集中所有个体对之间的关系（即使对于具有数千个样本的大型研究）。具体目标2是开发和纳入基于NGS数据（包括个体全基因组序列）确定遗传相关性的方法。这些方法将为基因组序列数据的分析提供一个重要的新维度，促进与疾病相关的变异的识别。为

DESCRIPTION (provided by applicant): The broad, long-term objective of the proposed research is to develop and market a commercial software product that can be used to facilitate the analysis of genetic changes in order to elucidate chromosomal abnormalities that underlie diseases 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 sample. In parallel, next- generation sequencing (NGS) of whole genomes (or whole exomes) allows the determination of sequence data from individuals with mental health (or other) diseases, as well as sequence data from affected and unaffected family members. 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. Software such as Partek(R) Genomics Suite" (GS) offers a robust set of tools to perform data analysis and visualization. A goal of this proposal is to enhance the Partek GS and Partek Flow" commercial products by introducing innovative, practically useful software modules that define genetic relatedness in studies based on SNP and/or NGS data. Specific Aim 1 is to develop and incorporate methods for the determination of genetic relatedness based on SNP data (including data sets of pedigrees and large populations). These methods allow the relationship between all pairs of individuals in a data set to be determined with high accuracy (even for large studies with thousands of samples). Specific Aim 2 is to develop and incorporate methods for the determination of genetic relatedness based on NGS data, including whole genome sequences of individuals. These methods will provide a significant new dimension to the analysis of genome sequence data, facilitating the identification of variants that are relevant to disease. For Specific Aim 3 we will apply these novel methods to two data sets: whole exome sequence data from individuals with autism (data from over 800 trios obtained from dbGaP), and SNP and whole genome or whole exome sequences from quintets of father/mother/child1/child2/child3 in which at least one child is diagnosed with autism. These studies will demonstrate the utility of the novel software methods and demonstrate how they can facilitate the discovery of genetic variants that underlie autism and other mental health disorders.