Table 3.
Gene selection using a machine learning approach.
| Gene name | Ensembl ID | Type of RNA |
|---|---|---|
| SNHG32orC6orf48 | ENSG00000204387 | ncRNA, small nuclear RNA |
| MT-ND4 | ENSG00000198886 | protein coding |
| MT-ND5 | ENSG00000198786 | protein coding |
| MT-ND2 | ENSG00000198763 | protein coding |
| lnc-IL17RA-36 or AC005301.9 | ENSG00000283633 | lncRNA |
| MT-CO1 | ENSG00000198804 | protein coding |
| TAOK3 | ENSG00000135090 | protein coding |
| REPS1 | ENSG00000135597 | protein coding |
| MT-CYB | ENSG00000198727 | protein coding |
| TPGS1 | ENSG00000141933 | protein coding |
| MMRN1 | ENSG00000138722 | protein coding |
| UBC | ENSG00000150991 | protein coding |
| MTATP6P1 | ENSG00000248527 | pseudogene |
| RP11-385D13.4 | ENSG00000266538 | lncRNA |
| REX1BDorC19orf60 | ENSG00000006015 | protein coding |
| CCDC85B | ENSG00000175602 | protein coding |
| HCG4P12 | ENSG00000225864 | pseudogene |
| RNU6-238P | ENSG00000200183 | pseudogene |
| AC009303.2 | ENSG00000279227 | lncRNA |
Genes identified by Random Forest to predict leprosy progression amongst household contacts of leprosy patients. In bold genes that were included in the final RNA-Seq signature and tested by reverse transcription quantitative PCR (RT-qPCR). Underlined the genes present in the final RT-qPCR RISK4LEP signature.