Evaluate GSA extension on p53 data set
نویسنده
چکیده
The public p53 data set contains expression profile with 33 samples carrying mutated p53 and 17 samples classified as normal [4]. The aim is to find which processes are affected due to dysfunction of p53. We applied CePa and standard GSA method on NCI-Nature catalogue from PID database. For CePa, we used the absolute t-value as node-level statistic and mean as the pathway level transformation. For standard GSA, we also used the absolute t-value as the gene-level statistic and mean value as the pathway score. P-values are calculated from 1000 sample permutations and are adjusted (FDR) through BH method [1]. Cutoff of FDR was set to 0.1. Results from CePa and standard GSA are illustrated in figure 1.
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