Publication details
Generovanie simulovaných testovacích dát pre genómové asociačné štúdie
| Title in English | Generating simulated testing data for genome-wide association studies |
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| Authors | |
| Year of publication | 2013 |
| Type | Article in Proceedings |
| Conference | ITAT 2013: Information Technologies - Applications and Theory (Workshops, Posters, and Tutorials) |
| MU Faculty or unit | |
| Citation | |
| web | https://www.researchgate.net/publication/255963204_Generovanie_simulovanch_testovacch_dt_pre_genmov_asocian_tdie?ev=prf_pub |
| Field | Informatics |
| Keywords | GWAS |
| Description | Recently human disease studies began to rely more and more on genotyping and genomic sequencing of individuals and a subsequent mass detection of genetic associations between variation (mostly SNPs) and diagnosis. These techniques are now called genome-wide association studies (GWAS). In GWAS we search for relationships between variations and the phenotype in the entire genomes. Detection of associations between single SNPs and a particular phenotype is now common. Unfortunately, the majority of biologicaly relevant relationships involve more than one SNP. These kinds of associations are still problematic to detect. We are looking for ways to solve this problem and efficiently detect compound associations with interacting SNPs. In testing methods applicable to interacting SNPs we often do not have appropriate data with information about all existing interactions and associations. However, the use of simulated data can help. Existing approaches to simulating genomic variation data often do not allow complicated relationships. Here we try to address this problem by designing a data simulator allowing for relatively complex and arbitrary interactions and associations to be embedded into simulated data. We designed a program with a graphical interface allowing the user to specify various parameters used to simulate artificial data. Users can freely specify functions for interactions and associations of several SNPs. Data simulated with our program was tested with GWAS association detection software. In this paper we present the program and its use. |
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