maelstRom

maelstRom models allele-specific expression (ASE) phenomena and enables statistical tests for detection and differential occurrence of allelic dispersion using regular RNA-Seq data.

Key Features:

• Differential Allelic Dispersion (AD) Analysis: Detects consistent differences in expression between the two alleles of a gene that are independent of normal genetic variation, unlike cis-expression quantitative trait loci.
• RNA-Seq Data Utilization: Performs (differential) AD analysis solely requiring large-scale RNA sequencing data without additional experimental requirements.
• Random Monoallelic Expression Detection: Identifies increased AD for loci featuring normal random monoallelic expression, including the X chromosome, with minimal interference with cancer-specific AD detection.
• Genome-wide Mapping: Generates genome-wide maps of allele-specific dysregulation during early carcinogenesis.

Scientific Applications:

• Early Carcinogenesis Detection: Identifies allele-specific dysregulation in early carcinogenesis, complementing basic differential expression analysis in cancer transcriptomics.
• Renal Clear Cell Carcinoma Analysis: Detects early dysregulated genes (e.g., FBP1, CCDC8, ECHS1, CLDN7) and pathways, often related to metabolism (e.g., pentose phosphate pathway), in renal cancer.
• Copy Number Alteration Benchmarking: Validates AD modeling using known copy number alterations as demonstrated with The Cancer Genome Atlas renal clear cell carcinoma cohort.
• Random Monoallelic Expression Studies: Applicable to studying random monoallelic expression and allele-specific (dys)regulation during early development or in noncancer diseases.

Methodology:

maelstRom implements differential allelic dispersion modeling in an R/C++ software package.