SEA (also SEAweb) is a searchable database for the expression of small RNA (miRNA, piRNA, snoRNA, snRNA, siRNA) and pathogens. Publically available sRNA sequencing datasets were analysed with Oasis 2 pipelines and the results are stored here for easy and comparable search. Our curated, ontology connected metadata enables powerful searches within this database. Learn more in the documentation and publication.
Several studies have shown tissue-specificity for miRNAs. Recently, Ludwig et al. analyzed 61 human tissue biopsies of different organs to define the distribution of miRNAs using tissue specificity index (TSI) and found several groups of miRNAs with tissue-specific expression. In particular, high expression of hsa-miR-124-3p and hsa-miR-9-5p was detected in brain and hsa-miR-133a-3p and hsa-miR-1-3p were detected in muscle. Click on the links for examining these examples with SEA and confirm that expression is highest in brain tissue samples or in heart and skeletal muscle tissue samples, respectively.
We validated our approach of pathogen detection using seven datasets with known infection status. Samples in GSE72769 and GSE69837 are known to be infected by Mycobacterium abscessus and Chlamydia trachomatis bacteria, respectively. Search Example
In-house sRNA-seq data from well-characterised 47 Parkinson disease (PD) and 53 frequency-matched healthy controls is presented as User Demo Data. It is baseline data from the longitudinal de novo Parkinson disease (DeNoPa) cohort. SEA gives us a unique opportunity to identify PD-specific biomarkers associated with early-stage PD that can eventually help us in early diagnosis, therefore, better treatment of the disease. For detailed results, please see the SEA manuscript. Search Example
Krishnan et al. explored piRNA as biomarkers for breast cancer. We can confirm this kind of study with SEA. In this example, we search their top differentially expressed piRNA hsa_piR_008114 in our cancer datasets and indeed find it differentially expressed in various different conditions in various cancer datasets. Similarly, Baral et al. examined the role of snoRNA in hepatocellular carcinoma. SNORD126 is on top of their list of the upregulated ones and again, we can confirm this in several cancer datasets.
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