Transcription termination is a critical stage for the production of legitimate mRNAs, and consequently functional proteins. However, the transcription machinery can ignore the stop signs and continue elongating beyond gene boundaries, invading downstream neighboring genes. Such phenomenon, designated transcription readthrough, can trigger the expression of pseudogenes usually silenced or lacking the proper regulatory signals. Due to the sequence similarity to parental genes, readthrough transcribed pseudogenes can regulate relevant protein-coding genes and impact biological functions. Here, we describe a computational pipeline that employs already existent bioinformatic tools to detect readthrough transcribed pseudogenes from expression profiles. We also unveil that combining strand-specific transcriptome data and epigenetic profiles can enhance and corroborate the results. By applying such approach to renal cancer biopsies, we show that pseudogenes can be readthrough transcribed as part of unspliced transcripts or processed RNA chimeras. Overall, our pipeline allows us to scrutinize transcriptome profiles to detect a diversity of readthrough events leading to expression of pseudogenes.