arXiv subjects

Andrey I. Buyan

Publications and source records attributed to Andrey I. Buyan.

2 recordsLinked to original sources

arXiv2026

MARADONER: Motif Activity Response Analysis Done Right

Inferring the activities of transcription factors from high-throughput transcriptomic or open chromatin profiling, such as RNA-/CAGE-/ATAC-Seq, is a long-standing challenge in systems biology. Identification of highly active master regulators enables mechanistic interpretation of differential gene expression, chromatin state changes, or perturbation responses across conditions, cell types, and diseases. Here, we describe MARADONER, a statistical framework and its software implementation for motif activity response analysis (MARA), utilizing the sequence-level features obtained with pattern matching (motif scanning) of individual promoters and promoter- or gene-level activity or expression estimates. Compared to the classic MARA, MARADONER (MARA-done-right) employs an unbiased variance parameter estimation and a bias-adjusted likelihood estimation of fixed effects, thereby enhancing goodness-of-fit and the accuracy of activity estimation. Further, MARADONER is capable of accounting for heteroscedasticity of motif scores and activity estimates.

stat.CO↗

arXiv2024

MIXALIME: MIXture models for ALlelic IMbalance Estimation in high-throughput sequencing data

Modern high-throughput sequencing assays efficiently capture not only gene expression and different levels of gene regulation but also a multitude of genome variants. Focused analysis of alternative alleles of variable sites at homologous chromosomes of the human genome reveals allele-specific gene expression and allele-specific gene regulation by assessing allelic imbalance of read counts at individual sites. Here we formally describe an advanced statistical framework for detecting the allelic imbalance in allelic read counts at single-nucleotide variants detected in diverse omics studies (ChIP-Seq, ATAC-Seq, DNase-Seq, CAGE-Seq, and others). MIXALIME accounts for copy-number variants and aneuploidy, reference read mapping bias, and provides several scoring models to balance between sensitivity and specificity when scoring data with varying levels of experimental noise-caused overdispersion.

stat.AP↗