This selection was motivated by the noise (outliers) of gene expression profiles.
In this study, outliers of microRNA expression in PCa microarray datasets were detected by using six statistical methods: LSOSS, COPA, MOST, ORT, OS and t-test.
Detection of outliers, relative expression levels of each gene-of-interest ([GOI]; Δ C q (GOI) = 20 – C q (GOI) + C q (CALM2) + C q (OAZ1) + C q (RPL37 A)]/3) as well as EP scores were calculated as described previously using a web-based implementation to process analytical PCR results into EP scores which can be found at: http://forschung.medizin.uni-mainz.de/epreport/[ 1].
Percentage Bend Correlation first detects outliers in expression values of each gene then reduces the effects of those outliers in the correlation calculation.
We note that our results are robust to the removal of outliers in gene expression variation (points with greater than three-fold variation; data not shown).
We propose that the combination of outlier expression with knowledge of possible approved or experimental drugs based on information available from DrugBank [29] will open a possibility to reposition known drugs to cancer types for which they have not been previously used.
Although appropriate preprocessing approaches such as the RMA (robust multichip average) [18] can be used to adjust the background noise and effects of outliers, identifying expression differences due to hybridization efficiency is critical.
Of 192 samples run, three cases (TCGA-02-0021, TCGA-12-0827 and TCGA-19-1386) were excluded from analysis as outliers with low expression of the 8 control genes (possibly representing under-loading or poor hybridization).
First, filtering was performed as per Jue et al. (2013) to remove outlier contigs from the distribution of expression levels.
57 Using an innovative approach of identifying "outlier kinase" expression through analysis of transcriptome sequencing data from a large number of cancers, polo-like kinases (PLKs) were noted to be overexpressed in a subset of KRAS mutant pancreatic cancers, and these cancers had specific sensitivity to the PLK-pan inhibitor, BI-6727.
This shifts the focus to a different type of analysis procedure: identification of a single sample or small subgroups that have divergent expression from the rest of the group (for example, the detection of candidate oncogenic chromosomal aberrations on the basis of outlier gene expression in prostate cancer [ 10]).
