A computer analysed the data and classified them using ML, generating the hypothesis that four of the fusion transcripts (MAN2A1-FER ≤ 40, CCNH-C5orf30 ≤ 38, SLC45A2-AMACR ≤ 41, and PTEN-NOLC1 ≤ 40) were associated with a high probability of cancer. This evidence concerns the gene SLC45A2 and cancer.