There are several challenges to accurately inferring levels of transcription using RNA-sequencing (RNA-seq) data, including detecting and correcting for reference genome mapping bias. One potential confounder of RNA-seq analysis results from the application of a standardized pipeline to samples of different sexes in species with chromosomal sex determination. The homology between the human X and Y chromosomes will routinely cause mismapping to occur, artificially biasing estimates of sex-biased gene transcription. For this reason we tested sex-specific mapping scenarios in humans on RNA-seq samples from the brains of 5 genetic females and 5 genetic males to assess how inferences of differential gene expression patterns change depending on the reference genome. We first applied a mapping protocol where we mapped all individuals to the entire human reference genome (complete), including the X and Y chromosomes, and computed differential expression between the set of genetic male and genetic female samples. We next mapped the genetic female samples (46,XX) to the human reference genome with the Y chromosome removed (Y-excluded) and the genetic male samples (46, XY) to the human reference genome (including the Y chromosome), but with the pseudoautosomal regions of the Y chromosome hard-masked (YPARs-masked) for the two sex-specific mappings. Using the complete and sex-specific mapping protocols, we compared the differential expression measurements of genetic males and genetic females from cuffDiff outputs. The second strategy called 33 additional genes as being differentially expressed between the two sexes when compared to the complete mapping protocol. This research provides a framework for a new standard of reference genome mappings to correct for sex-biased gene expression estimates that can be used in future studies.