Here are some references related to filtering gene transcripts based on differential expression analysis:
Love, M. I., Huber, W., & Anders, S. (2014). Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome biology, 15(12), 550.
Robinson, M. D., McCarthy, D. J., & Smyth, G. K. (2010). edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics, 26(1), 139-140.
Ritchie, M. E., Phipson, B., Wu, D., Hu, Y., Law, C. W., Shi, W., & Smyth, G. K. (2015). limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic acids research, 43(7), e47-e47.
Soneson C et al.. Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences F1000Research; Volume 4
5.Genes differentially expressed in prostate cancer by microarray analysis RE Velho et al.; Journal of Clinical Oncology; February 2003
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