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Statistical Assessment of MSigDB Gene Sets in Colon Cancer

机译:结肠癌MSIGDB基因集的统计评估

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Gene expression profiling offers a great opportunity for understanding the key role of genes in alterations which drive a normal cell to a cancer state. A deep understanding of the mechanisms of tumorige-nesis can be reached focusing on deregulation of gene sets or pathways. We measure the amount of deregulation and assess the statistical significance of predefined pathways belonging to MSigDB collection in a colon cancer data set. To measure the relevance of the pathways we use two well-established methods: Gene Set Enrichment Analysis (GSEA) [7] and Gene List Analysis with Prediction Accuracy (GLAPA) [8]. We found that pathways associated to different diseases are strictly connected with colon cancer. Our study highlights the importance of using gene sets genes for understanding the main biological processes and pathways involved in colorectal cancer. Our analysis shows that many of the genes involved in these pathways are strongly associated to colorectal tumorigenesis.
机译:基因表达分析提供了理解基因在驱动正常细胞到癌症状态的改变中的关键作用的绝佳机会。可以达到对肿瘤患者的机制的深刻理解,重点关注基因套或途径的放松管制。我们测量放松管制量,并评估属于结肠癌数据集中的预定义路径的统计学意义。为了测量途径的相关性,我们使用两种完整的方法:基因设定富集分析(GSEA)[7]和基因列表分析,具有预测精度(GLAPA)[8]。我们发现与不同疾病相关的途径与结肠癌严格连接。我们的研究突出了使用基因套基因以了解结直肠癌中涉及的主要生物过程和途径的重要性。我们的分析表明,这些途径中涉及的许多基因与结直肠肿瘤鉴定强烈相关。

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