snoHUB2: Predicted biological functions for small nucleolar RNAs

Small nucleolar RNAs are non-coding RNAs involved in RNA modification, processing, and regulation. snoHUB2 uses co-expression correlations from ARCHS4 RNA-seq samples to identify biological processes, pathways, and other gene-set terms associated with each snoRNA.

For example SNORD116-1 , SNORD115-12 , SNORD64 , or a valid Ensembl gene ID from the snoHUB2 database.

snoRNA report for

This report summarizes co-expression-based evidence for . These associations are predictions and should be interpreted as hypotheses for experimental follow-up.

Overview of

snoRNA symbol
Ensembl gene ID

Overall highest correlated terms for

These are the terms with the largest positive mean Pearson correlations across all included gene-set libraries.

Overlapping genes for the highest correlated terms

For each term, up to 25 overlapping genes are ranked by correlation distance. Correlation distance is calculated as 1 minus the Pearson correlation, so smaller values indicate stronger positive correlations with the snoRNA.

Predicted functions by library

For each gene-set library, the highest and lowest correlated terms are shown separately. Bar length represents the mean Pearson correlation between the snoRNA and the genes overlapping each term.

References

[1] Lachmann A, et al. Massive mining of publicly available RNA-seq data from human and mouse. Nature Communications. 2018.

[2] Xie Z, et al. Gene Set Knowledge Discovery with Enrichr. Current Protocols. 2021.

[3] Chen EY, et al. Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool. BMC Bioinformatics. 2013.

[4] Kuleshov MV, et al. Enrichr: a comprehensive gene set enrichment analysis web server 2016 update. Nucleic Acids Research. 2016.