NÚMERO DE REPETIÇÕES NA IDENTIFICAÇÃO DE GENES DIFERENCIALMENTE EXPRESSOS EM EXPERIMENTOS DE RNA-SEQ

Abstract

This work aimed to evaluate the effect of the number of repetitions, of two important statistical methodologies, BaySeq and DEseq, in the identification of differentially expressed genes (DEG). To carry out the analyses, we used four simulated scenarios, whose represents real experiments with two experimental conditions represented for different repetition numbers. TCC package of Bioconductor was used to simulated 1000 genes, which 200 were considered differentially expressed (DE). Initially, the data were analyzed for each method, comparing the influence of the number of repetitions in the identification of DGE. Then, the comparison was made between the results obtained by each method, taking into account the number of repetitions in each scenario. The power to detect DGE was affected negatively due the reducing the number of repetitions. baySeq presented better accuracies for scenarios with 5 and without repetitions. Therefore, baySeq presented higher sensibility, since the rates of true and false positives were, respectively, higher and lower compared to those obtained to DESeq under the evaluated conditions.