We found that the results were rela tively insensitive to the cut off value and we set this to Palbociclib solubility be 10% of the average expression value. All sample expression profiles within a series were scaled to the, where sk is the expression level of the kth probe set database to be searchable with cross platform response profiles and gene lists it has to be rewritten as a data base of expression profiles over non redundant gene lists. The EF profiles across the probe sets were there fore mapped onto expression profiles for a non redun dant gene list. In general each gene is represented by multiple probe sets. For each platform we generated the EF statistics for each probe set across the totality of samples. The probe set with the most robust response across the samples was chosen to represent the gene.
Explicitly, the probe set with the highest root mean square deviation form zero was chosen to represent the given gene. The number of genes defined on each plat form were as follows GPL96 11,807, GPL570 15,983 genes, GPL1261 13,202 genes, GPL85 chip with 3,844 genes, GPL1355 chip with 6,341 genes. The database totals 106,101 samples and is searchable on a reasonably fast desktop PC in 10 minutes per query. Searching the database The query profile is a statistically thresholded non redun dant list of genes and associated fold values. Statistical significance is assigned to a fold change based on a sim ple Students t test between multiple control and treat ment sample expression values. This is compared to each profile in the database by means of a simple Pearson regression analysis, with a correlation coefficient r.
The experiments are ranked according to the significance. The significance is measured by scaling the correlation to the normal by a Fisher transformation and measuring the number of standard deviations from the mean. The tion coefficient and N is the number of genes making up the correlation. The final ranking score is CMAP combined profiles The CMAP contains ranked lists of probes for 6,100 separate perturbagen treatments of four different human cell lines, with the ranking based on response level rela tive to control. The treatments are various multiples of 1,306 different drug like compounds. To generate responder sets that can be used to search SPIED we combined rankings for each separate compound treat ment and converted these into pseudo fold values with associated statistics.
The pseudo fold value is defined by gene and min max are the minimal maximal ranks. Remembering that the highest rank corresponds to the most up regulated gene. The SPIED was searched with CMAP profiles corresponding Drug_discovery to folds with a p 0. 05 threshold and with at least three replicates. This left 1,218 separate perturbagen probes. We sought to cluster the perturbagens based on predicted target and response profile similarity.