XC-ID: De novo identification of the active X chromosome in single-cell RNA-seq

Abstract

MotivationX chromosome inactivation (XCI) is an epigenetic process that equalizes X-linked gene dosage between females (XX) and males (XY). During early development, one X chromosome in each cell is randomly silenced and clonally inherited, producing a stable mosaic of two epigenetically distinct cell lineages. This mosaicism provides a natural internal control for studying cell-intrinsic regulatory differences between X lineages. However, identifying the active X chromosome in single cells remains difficult due to sparse allelic coverage, dependence on pre-phased references, and biological variability from XCI escape and skew. ResultsWe present XC-ID (X Chromosome inactivation IDentifier), a scalable computational framework for de novo identification of the active X chromosome from single-cell RNA-seq data. XC-ID employs a simulated-annealing algorithm to infer X-linked haplotype structure directly from allelic counts, followed by bootstrap-based confidence estimation to filter uncertain cell assignments. Applied to single-nucleus RNA-seq data from a female Mus musculus hybrid with known genotype, XC-ID achieved >99% accuracy in predicting the active X chromosome. The method remains robust to allelic noise, sequencing errors, and sparsity, and differential expression between inferred X lineages reveals biologically coherent dosage-compensation patterns. AvailabilityXC-ID is available as a Python package with both API and command-line support at https://github.com/jlhjiang/XC-ID.