A systematic bioinformatics tool to develop a new pathway-based gene panel for tumor mutational burden (TMB) assessment (pathway-based tumor mutational burden, PTMB), using somatic mutations files in an efficient manner from either The Cancer Genome Atlas sources or any in-house studies as long as the data is in mutation annotation file (MAF) format. Besides, we develop a multiple machine learning method using the sample's PTMB profiles to identify cancer-specific dysfunction pathways, which can be a biomarker of prognostic and predictive for cancer immunotherapy.
| Version: |
0.1.3 |
| Depends: |
R (≥ 4.1.0) |
| Imports: |
BiocGenerics, purrr, utils, glmnet, randomForest, stats, survival, survminer, caret, data.table, RColorBrewer, grDevices, pROC, graphics, maftools, clusterProfiler |
| Suggests: |
stringi, knitr, rmarkdown, testthat, BiocManager, xfun, e1071, qpdf, tinytex, spelling |
| Published: |
2022-08-09 |
| Author: |
Junwei Han [aut, cre, cph],
Xiangmei Li [aut] |
| Maintainer: |
Junwei Han <hanjunwei1981 at 163.com> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: |
no |
| Language: |
en-US |
| CRAN checks: |
pathwayTMB results |