chromVAR is an R package designed to analyze sparse chromatin accessibility data from single-cell epigenomic studies. It estimates the gain or loss of accessibility within peaks sharing the same motif or annotation while controlling for technical biases. chromVAR enables accurate clustering of scATAC-seq profiles and characterization of known and de novo sequence motifs associated with chromatin accessibility variation. The method works by computing a "raw accessibility deviation" for each motif and cell, representing the difference between the total number of fragments mapping to peaks containing the given motif and the expected number based on the average of all input cells. This deviation is then corrected for technical biases using background peak sets, which are matched for GC content and average accessibility. The corrected deviations and z-scores are used for downstream analyses, including clustering of cells and identification of key regulators. chromVAR is applied to single-cell and bulk epigenomic data, enabling unbiased characterization of cell types and trans-regulators. It has been tested on various datasets, including hematopoietic cell types and AML samples, where it successfully identified known master regulators of hematopoiesis. The package also allows for the discovery of de novo motifs by analyzing the variability of kmers and their association with chromatin accessibility. chromVAR is robust to low sequencing depth and can scale to hundreds or thousands of cells or samples. It provides a powerful input for existing algorithms to infer spatial and temporal relationships between cells. The package includes tools for visualizing motif and kmer similarity, as well as for analyzing chromatin variability across regions. chromVAR is freely available under the MIT license and includes a collection of tools for downstream analysis.chromVAR is an R package designed to analyze sparse chromatin accessibility data from single-cell epigenomic studies. It estimates the gain or loss of accessibility within peaks sharing the same motif or annotation while controlling for technical biases. chromVAR enables accurate clustering of scATAC-seq profiles and characterization of known and de novo sequence motifs associated with chromatin accessibility variation. The method works by computing a "raw accessibility deviation" for each motif and cell, representing the difference between the total number of fragments mapping to peaks containing the given motif and the expected number based on the average of all input cells. This deviation is then corrected for technical biases using background peak sets, which are matched for GC content and average accessibility. The corrected deviations and z-scores are used for downstream analyses, including clustering of cells and identification of key regulators. chromVAR is applied to single-cell and bulk epigenomic data, enabling unbiased characterization of cell types and trans-regulators. It has been tested on various datasets, including hematopoietic cell types and AML samples, where it successfully identified known master regulators of hematopoiesis. The package also allows for the discovery of de novo motifs by analyzing the variability of kmers and their association with chromatin accessibility. chromVAR is robust to low sequencing depth and can scale to hundreds or thousands of cells or samples. It provides a powerful input for existing algorithms to infer spatial and temporal relationships between cells. The package includes tools for visualizing motif and kmer similarity, as well as for analyzing chromatin variability across regions. chromVAR is freely available under the MIT license and includes a collection of tools for downstream analysis.