Main Article Content
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.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).