<strong>Objective:</strong> <span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">DNA copy number alterati...<strong>Objective:</strong> <span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">DNA copy number alterations and difference expression are frequently observed in ovarian cancer. The purpose of this way was to pinpoint gene expression change that w</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">as</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"> associated with alterations in DNA copy number and could therefore enlighten some potential oncogenes and stability genes with functional roles in cancers, and investigated the bioinformatics significance for those correlated genes</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">. </span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><b><span style="font-family:Verdana;">Method: </span></b></span></span><span><span><span style="font-family:""><span style="font-family:Verdana;">We obtained the DNA copy </span><span style="font-family:Verdana;">number and mRNA expression data from the Cancer Genomic Atlas and</span><span style="font-family:Verdana;"> identified the most statistically significant copy number alteration regions using the GISTIC. Then identified the significance genes between the tumor samples within the copy number alteration regions and analyzed the correlation using a binary matrix. The selected genes were subjected to bio</span><span><span style="font-family:Verdana;">informatics analysis using GSEA tool. </span><b><span style="font-family:Verdana;">Results:</span></b><span style="font-family:Verdana;"> GISTIC analysis results</span></span><span style="font-family:Verdana;"> showed there were 45 significance copy number amplification regions in the ovarian cancer, SAM and Fisher’s exact test found there have 40 genes can affect the expressi展开更多
文摘<strong>Objective:</strong> <span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">DNA copy number alterations and difference expression are frequently observed in ovarian cancer. The purpose of this way was to pinpoint gene expression change that w</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">as</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"> associated with alterations in DNA copy number and could therefore enlighten some potential oncogenes and stability genes with functional roles in cancers, and investigated the bioinformatics significance for those correlated genes</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">. </span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><b><span style="font-family:Verdana;">Method: </span></b></span></span><span><span><span style="font-family:""><span style="font-family:Verdana;">We obtained the DNA copy </span><span style="font-family:Verdana;">number and mRNA expression data from the Cancer Genomic Atlas and</span><span style="font-family:Verdana;"> identified the most statistically significant copy number alteration regions using the GISTIC. Then identified the significance genes between the tumor samples within the copy number alteration regions and analyzed the correlation using a binary matrix. The selected genes were subjected to bio</span><span><span style="font-family:Verdana;">informatics analysis using GSEA tool. </span><b><span style="font-family:Verdana;">Results:</span></b><span style="font-family:Verdana;"> GISTIC analysis results</span></span><span style="font-family:Verdana;"> showed there were 45 significance copy number amplification regions in the ovarian cancer, SAM and Fisher’s exact test found there have 40 genes can affect the expressi
