DASHR (Database of small human non-coding RNAs) v2.0 provides a complete catalog of annotation, expression, processing, conservation, tissue-specificity and other biological features for all human small non-coding (sncRNA) genes, full sncRNA transcripts and mature products derived from all major small RNA classes, including miRNAs, piRNAs, sc-, sn-, sno- RNAs, tRNAs, tRFs (https://lisanwanglab.org/DASHRv2 ).

DASHR 2.0 is an extremely useful resource and reference for the community studying non-coding RNAs and their diverse roles in often tissue-specific cellular processes related to human diseases.

Some of the DASHR v2.0 highlights include:

1) Integration of the largest collection of >180 tissues and cell types from ENCODE and curated GEO/SRA experiments (>22 billion reads) across multiple RNA-seq protocols for both GRCh38/hg38 and GRCh37/hg19 (http://dashr2.lisanwanglab.org/search.php );

2) The first database to profile both known sncRNA loci and novel, previously un-annotated sncRNA loci identified by de novo by genome-wide unsupervised segmentation (>1,600,000 small RNA loci; http://dashr2.lisanwanglab.org/search.php ) ;

3) Integration of >3,200,000 annotations for non-small RNA genes and other genomic features (e.g., long-noncoding RNAs, promoters) (http://dashr2.lisanwanglab.org/download.php );

4) Introduction of an enhanced user interface, interactive experiment-by-locus table views for easy sorting and filtering of small RNA loci data (http://dashr2.lisanwanglab.org/browse.php );

5) Access to genome wide expression tracks and called small RNA peaks freely downloadable (http://dashr2.lisanwanglab.org/download.php) and viewable in the UCSC Genome Browser (http://dashr2.lisanwanglab.org/browse.php ).

DASHR v2.0 database is freely available at https://lisanwanglab.org/DASHRv2.

DASHR v2.0 has been published in Bioinformatics.

Kuksa, Pavel P., Amlie-Wolf, A., Katanic, Z., Valladares, O., Wang, L., Leung, Y. DASHR v2.0: database of small human noncoding RNAs in human tissues and cell types. Bioinformatics, 2018. https://doi.org/10.1093/bioinformatics/bty709