Background: Open data sharing is instrumental for the advance of biological sciences. Gene expression is the primary molecular phenotype, usually estimated through RNA-Seq experiments. Large scope interpretation of RNA-Seq results is complicated by the extensive gene expression range, as well as by the diversity of biological sources and experimental treatments. Here we present "Salsa", an auto-contained R package for extracting useful knowledge about gene expression during the development of

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... ili pepper fruit. Methods and Results: Data from 168 RNA-Seq libraries, comprising more than 3.4 billion reads, were analyzed and curated to represent standardized expression profiles (SEPs) for all genes expressed during fruit development in 12 chili pepper accessions. Accessions have representatives of domesticated varieties, wild ancestors and crosses, covering a broad spectrum of genotypes. Data are organized in a relational way, and functions allow data mining from the level of single genes up to whole genomes, grouping profiles by different criteria. Those include any combination of expression model, accession, protein description and gene ontology (GO) term, among others. Also, GO enrichment analysis can be performed over any set of genes. Conclusions: "Salsa" opens endless possibilities for mining the transcriptome of chili pepper during fruit development.