Integrated analysis of pharmacologic, clinical and SNP microarray data using Projection Onto the Most Interesting Statistical Evidence with Adaptive Permutation Testing.

Int J Data Min Bioinform 2011 ;5(2):143-57

Department of Biostatistics, St. Jude Children's Research Hospital, Memphis, TN 38105, USA.

We recently developed the Projection Onto the Most Interesting Statistical Evidence (PROMISE) procedure that uses prior biological knowledge to guide an integrated analysis of gene expression data with multiple biological and clinical endpoints. Here, PROMISE is adapted to the integrated analysis of pharmacologic, clinical and genome-wide genotype data. An efficient permutation-testing algorithm is introduced so that PROMISE is computationally feasible in this higher-dimension setting. In the analysis of a paediatric leukaemia data set, PROMISE effectively identifies genomic features that exhibit a biologically meaningful pattern of association with multiple endpoint variables.

Download full-text PDF

Source
http://dx.doi.org/10.1504/IJDMB.2011.039174DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3080017PMC
June 2011
6 Reads

Publication Analysis

Top Keywords

integrated analysis
12
projection interesting
8
statistical evidence
8
pharmacologic clinical
8
interesting statistical
8
analysis pharmacologic
8
analysis gene
4
exhibit biologically
4
gene expression
4
algorithm introduced
4
expression data
4
introduced promise
4
effectively identifies
4
promise computationally
4
prior biological
4
biological knowledge
4
biologically meaningful
4
guide integrated
4
knowledge guide
4
data multiple
4

Similar Publications