The xCell website was down for a while, but should be working now. If you still experience problems, please let us know at xcell@technion.ac.il.
*** xCell is intended for use with bulk gene expression, for single-cell RNA-seq we recommend using SingleR: https://github.com/dviraran/SingleR ***
Tissues are a complex milieu consisting of numerous cell types. In cancer, understanding the cellular heterogeneity in the tumor microenvironment is an emerging field of research. Numerous methods have been published in recent years for the enumeration of cell subsets from tissue expression profiles. However, the available methods suffer from three major problems: inferring cell subset based on gene sets learned and verified from limited sources; displaying only partial portrayal of the full cellular heterogeneity; and insufficient validation in mixed tissues.
xCell is a webtool that performs cell type enrichment analysis from gene expression data for 64 immune and stroma cell types. xCell is a gene signatures-based method learned from thousands of pure cell types from various sources. xCell applies a novel technique for reducing associations between closely related cell types. xCell signatures were validated using extensive in-silico simulations and also cytometry immunophenotyping, and were shown to outperform previous methods. xCell allows researchers to reliably portray the cellular heterogeneity landscape of tissue expression profiles. For more informations please refer to the xCell manuscript.
To use xCell simply upload human gene expression data file in tab delimited text format or csv (up to 1Gb). The expression matrix should be a matrix with genes in rows and samples in columns. The rownames should be gene symbols. If the data contains non-unique gene symbols, rows with same gene symbols will be averaged. xCell uses the expression levels ranking and not the actual values, thus normalization does not have an effect, however normalizing to gene length (RPKM/FPKM/TPM/RSEM) is required.
Importantly, xCell performs best with heterogenous dataset. Thus it is recommended to use all data combined in one run, and not break down to pieces (especially not cases and control in different runs).
Mark if the data is RNA-seq gene expression profile, and choose the xCell signature set (or other signature sets). The analysis may take a while to complete, therefore please provide an email address. A link to download the results in a tab delimited file format will be sent once the analysis is done.
An example of a gene expression data file can be downloaded here.
Pre-calculated TCGA data by xCell is available here. Please do not run TCGA data using the webtool.
*** We do not save any files. All uploaded data is immediately deleted after the analysis. Analysis results are immediately deleted after first download. ***