GeneRanger and TargetRanger: processed gene and protein expression levels across cells and tissues for target discovery

Abstract

Several atlasing efforts aim to profile human gene and protein expression across tissues, cell types and cell lines in normal physiology, development and disease. One utility of these resources is to examine the expression of a single gene across all cell types, tissues and cell lines in each atlas. However, there is currently no centralized place that integrates data from several atlases to provide this type of data in a uniform format for visualization, analysis and download, and via an application programming interface. To address this need, GeneRanger is a web server that provides access to processed data about gene and protein expression across normal human cell types, tissues and cell lines from several atlases. At the same time, TargetRanger is a related web server that takes as input RNA-seq data from profiled human cells and tissues, and then compares the uploaded input data to expression levels across the atlases to identify genes that are highly expressed in the input and lowly expressed across normal human cell types and tissues. Identified targets can be filtered by transmembrane or secreted proteins. The results from GeneRanger and TargetRanger are visualized as box and scatter plots, and as interactive tables. GeneRanger and TargetRanger are available from https://generanger.maayanlab.cloud and https://targetranger.maayanlab.cloud, respectively.

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“…It is also possible to use these data resources as a baseline to identify novel drug targets. For example, gene expression data collected by RNA-seq from tumor samples, can be compared to all normal tissue to identify genes that are only highly expressed in the tumor using the TargetRanger API [60].…”

“…The RNA-seq samples are the columns of the matrix, and the rows are the raw expression gene counts for all human coding genes. This data matrix is fed into TargetRanger [60] to screen for targets that are highly expressed in the tumor but lowly expressed across most healthy human tissues based on gene expression data collected from postmortem patients with RNA-seq by the GTEx CF program [52]. Based on this analysis, the gene Insulin-like growth factor II m-RNA-binding protein 3 (IMP3) was selected because it was the top candidate returned from the TargetRanger analysis (Table 1).…”