Different tissues and diseases have distinct transcriptional profilings with specifically expressed genes (SEGs). So, the identification of SEGs is an important issue in the studies of gene function, biological development, disease mechanism and biomarker discovery. However, few accurate and easy-to-use tools are available for RNA sequencing (RNA-seq) data to detect SEGs.
A web-based server for on-line detection of gene expression patterns from serial transcriptomic data generated by high-throughput technologies like microarray or next-generation sequencing. Three particular parameters, the specificity measure, the dispersion measure and the contribution measure, were introduced and implemented in PaGeFinder to help quantitative and interactive identification of pattern genes like housekeeping genes, specific (selective) genes and repressed genes.
Leverages the relationships between tissues and cell-types. URSA is able to identify specific tissue/cell-type signals present in a given gene expression profile. It permits to automatically annotate samples in public gene expression repositories where most samples are currently lacking tissue/cell-type-specific information. The tool can be used to test and identify possible sample contaminations or resolve cancer samples of unknown primary origin.
Proposes a set of methods for both RNA-seq and single-cell RNA-seq analysis. BBrowser supplies interactive visualizations as well as multiple analytics such as quality control, enrichment analysis, sub-clustering or differential expression. The platform includes a set of precomputed datasets encompassing research studies and sequencing samples or allows users to submit their own data.