NCBI-generated Mouse raw gene counts from SRA RNA-seq data. Mus musculus

A major barrier to fully exploiting and reanalyzing the massive volumes of public RNA-seq data is the cost and high level of effort and expertise required to process raw RNA-seq reads into concise formats that summarize the expression results. To circumvent those challenges NCBI built a pipeline that performs the common first steps in any RNA-seq analysis, including precomputing RNA-seq genome alignments, gene expression counts, and quality metrics on all existing and incoming mouse SRA RNA-seq data in the cloud. These uniformly pre-processed RNA-seq expression counts can be readily incorporated into existing commonly used differential expression analysis and visualization software. In this way, we lower the bar for analyzing public RNA-seq data, add value to existing public data sets, contribute to the ecosystem of FAIR data resources in the cloud and generate new opportunities to mine and reuse public RNA-seq data.