TargetRanger

TargetRanger analyzes gene and protein expression by comparing user RNA-seq data to processed atlases of normal human cell types, tissues, and cell lines to identify candidate molecular targets.

Key Features:

• Integration of Multiple Atlases: Aggregates processed gene and protein expression data from multiple atlases and from the GeneRanger platform into a unified resource accessible via an application programming interface (API) for uniform analysis and download.
• RNA-seq Data Analysis: Accepts RNA-seq input and compares experimental expression levels against atlas-derived expression profiles.
• Identification of Highly Expressed Genes: Detects genes that are highly expressed in the uploaded dataset but have low expression across normal human cell types, tissues, and cell lines.
• Filtering Options: Filters and prioritizes identified targets by attributes such as transmembrane or secreted proteins.
• Data Visualization: Produces box plots, scatter plots, and interactive tables to visualize and interpret expression patterns.

Scientific Applications:

• Target discovery: Identification and prioritization of candidate therapeutic targets based on differential expression relative to normal human tissues and cell types.
• Comparative expression profiling: Comparison of experimental RNA-seq datasets to atlas-derived normal expression for studies of normal physiology, development, and disease.
• Membrane and secreted protein prioritization: Selection of transmembrane and secreted proteins for downstream functional validation or therapeutic development.

Methodology:

Processes user RNA-seq data and compares gene expression levels to a comprehensive database derived from multiple atlases to identify genes with high expression in the input and low expression across normal samples; identified genes and differential-expression results are presented via box plots, scatter plots, and interactive tables.