The paper introduces xCell, a novel gene signature-based method for inferring cellular heterogeneity in tissues. xCell aims to overcome the limitations of existing methods, which often rely on limited training data and provide only a partial portrayal of the full cellular landscape. By harmonizing 1822 pure human cell type transcriptomes from various sources and employing a curve fitting approach, xCell linearly compares cell types and introduces a spillover compensation technique to separate them. Extensive in silico analyses and comparisons with cytometry immunophenotyping show that xCell outperforms other methods. xCell is available as an R package and a web tool (http://xCell.ucsf.edu/). The method is validated through simulated mixtures and real-world data, demonstrating its reliability in identifying cell type enrichments in mixed samples. xCell is particularly useful for studying the tumor microenvironment, where it can accurately infer the cellular composition of tumors, including immune and stromal cell types. The authors provide a comprehensive collection of gene expression enrichment scores for 64 cell types and hope that this resource will aid in the discovery of novel biomarkers and therapeutic targets.The paper introduces xCell, a novel gene signature-based method for inferring cellular heterogeneity in tissues. xCell aims to overcome the limitations of existing methods, which often rely on limited training data and provide only a partial portrayal of the full cellular landscape. By harmonizing 1822 pure human cell type transcriptomes from various sources and employing a curve fitting approach, xCell linearly compares cell types and introduces a spillover compensation technique to separate them. Extensive in silico analyses and comparisons with cytometry immunophenotyping show that xCell outperforms other methods. xCell is available as an R package and a web tool (http://xCell.ucsf.edu/). The method is validated through simulated mixtures and real-world data, demonstrating its reliability in identifying cell type enrichments in mixed samples. xCell is particularly useful for studying the tumor microenvironment, where it can accurately infer the cellular composition of tumors, including immune and stromal cell types. The authors provide a comprehensive collection of gene expression enrichment scores for 64 cell types and hope that this resource will aid in the discovery of novel biomarkers and therapeutic targets.