Interpreting the prevalence of regulatory SNPs in cancers and protein-coding SNPs among non-cancer diseases using GWAS association studies
作者： Uğur Sezerman , Zoya Khalid
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摘要: Biological mechanisms underlying diseases are quite challenging to understand, as there exists a complex relationship between human genetics and disease traits. Genome-wide association studies potent methods in identifying single nucleotide polymorphisms (SNPs) which linked with large number of phenotypes. Even though GWAS list down the statistically significant SNPs found be associated phenotype interest, still is need look for direct evidence regarding biological processes better understand development mechanism since it may differ different depending on nature disease. From previous few years, above 11 million that have been labelled databases specifically dbSNP. Among them, can categorized coding or non-coding their location genome. Lethal changes parts genes might play role by directly affecting functionality protein. Similarly those present at regulatory regions splice regions, micro RNA binding sites epigenetic affect level gene expression ultimately contributes formation. We designed our study performing statistical analysis dataset. Seventeen cancer types non-cancer (autoimmune, Neurodegenerative metabolic diseases) has selected order major factors involved progression impact development. The includes chi squared hypothesis testing null hypotheses H0: areas not significantly alternate H1: They different.The results revealed Complex like Cancer mostly caused mutations occurring non thus causing levels involved, such over oncogenes under tumor suppressor expected, whereas other diseases, more determinative role. These change protein product having autoimmune response. This future taken reference analysing genome divulging involving diseases.
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