Tissue-adjusted pathway analysis of cancer (TPAC): A novel approach for quantifying tumor-specific gene set dysregulation relative to normal tissue.
Hildreth Robert FrostPublished in: PLoS computational biology (2024)
We describe a novel single sample gene set testing method for cancer transcriptomics data named tissue-adjusted pathway analysis of cancer (TPAC). The TPAC method leverages information about the normal tissue-specificity of human genes to compute a robust multivariate distance score that quantifies gene set dysregulation in each profiled tumor. Because the null distribution of the TPAC scores has an accurate gamma approximation, both population and sample-level inference is supported. As we demonstrate through an analysis of gene expression data for 21 solid human cancers from The Cancer Genome Atlas (TCGA) and associated normal tissue expression data from the Human Protein Atlas (HPA), TPAC gene set scores are more strongly associated with patient prognosis than the scores generated by existing single sample gene set testing methods.
Keyphrases
- papillary thyroid
- genome wide
- endothelial cells
- gene expression
- copy number
- genome wide identification
- squamous cell
- single cell
- electronic health record
- dna methylation
- childhood cancer
- induced pluripotent stem cells
- big data
- machine learning
- data analysis
- healthcare
- squamous cell carcinoma
- poor prognosis
- genome wide analysis
- health information
- young adults
- case report
- deep learning
- bioinformatics analysis