Interaction Between Microarray Design Strategies And Data Pre-Processing Procedures In Gene Expression Differential Analysis: A Computational Statistical Survey

The purpose of this study is to assess the link between microarrays design strategies and gene expression data pre-processing systems dynamisms. High throughput RNA-seq analysis is nowadays fully used by researchers in their transcriptomic as well as genomic studies. However, microarray remains a reliable and stable tool in transcriptomic and genomic surveys. It is well documented that microarray performance in transcriptomic and/or genomic studies is conditioned by oligonucleotide probe features (microarray design strategies) as well as by data pre-processing procedures, in term of background correction (BC) and expressed genes intensity data standardization (DS). After showing microarray data pre-processing dynamism, in gene expression differential surveys outcome, we embarked here in evaluating the interaction between microarray design strategies based on single and/or multiple short and/or long probe set, per gene model transcript and 20 different data pre-processing arrangements (BC+DS or DS+BC).Findings show high performance in terms of results stability and sensitivity with regard to microarray design strategies based (i) on short multiple and long single probe set per gene transcript and (ii) long multiples oligonucleotides probes per gene model transcript respectively for background correction (BC) followed by expressed gene signal standardization (DS) (BC+DS) data pre-treatment procedure. Microarray data pre-treatment procedure based on gene expression data standardization followed by background correction (DS+BC), induced high variability in microarrays gene expression differential analysis outcome. R fitting curve analysis as well ANOVA test highlighted a good performances in terms of accuracy and sensitivity for microarray designs strategies based on short and long multiple oligonucleotide in gene expression differential analysis outcome respectively.In conclusion, presently processed microarray platforms exhibited stable attitude as well as high performance attitude, especially for microarray design strategies based on multiple oligonucleotide probe set per gene transcript model in differential analysis for the purpose of data pre-processed by standardization (BC+DS) as opposed to noise and/or background correction (DS+BC) procedures.