Abstract
<jats:p>Accurate calculation of nucleic acid melting temperature (Tm) underpins many molecular biology applications. Beyond single sequences, genome-wide Tm profiles capture intrinsic thermodynamic properties that can be leveraged to study biological processes at genomic scale. However, most existing Tm tools operate only at the sequence level and are incompatible with standardized Bioconductor data structures, such as GRanges, or with downstream multi-omics workflows. We developed TmCalculator, a Bioconductor-compatible R package that extends Tm analysis from individual sequences to genome-wide thermodynamic profiling. It accepts plain nucleotide sequences, FASTA files, genomic coordinates, and GRanges objects. TmCalculator implements a comprehensive set of nearest-neighbor thermodynamic models, the current standard for accurate Tm prediction, alongside widely used empirical GC-content models, both supporting salt and chemical corrections. Results are returned as GRanges objects, allowing Tm to integrate directly with multi-omics data such as ATAC-seq, RNA-seq, and ChIP-seq, supported by native utilities for multi-layer integration, statistical comparison, and visualization. We demonstrate TmCalculator on the Escherichia coli genome by revisiting a published map of MutL-associated replication error hotspots, reproducing and extending the reported link between reduced Tm and error-prone regions, and providing a reproducible route to investigate the physical properties underlying genome function and disease.</jats:p>