Visualization of the small RNA transcriptome using seqclusterViz.

Clicks: 376
ID: 3510
2019
Article Quality & Performance Metrics
Overall Quality Improving Quality
0.0 /100
Combines engagement data with AI-assessed academic quality
AI Quality Assessment
Not analyzed
Abstract
The study of small RNAs provides us with a deeper understanding of the complexity of gene regulation within cells. Of the different types of small RNAs, the most important in mammals are miRNA, tRNA fragments and piRNAs. Using small RNA-seq analysis, we can study all small RNA types simultaneously, with the potential to detect novel small RNA types. We describe SeqclusterViz, an interactive HTML-javascript webpage for visualizing small noncoding RNAs (small RNAs) detected by Seqcluster. The SeqclusterViz tool allows users to visualize known and novel small RNA types in model or non-model organisms, and to select small RNA candidates for further validation. SeqclusterViz is divided into three panels: i) query-ready tables showing detected small RNA clusters and their genomic locations, ii) the expression profile over the precursor for all the samples together with RNA secondary structures, and iii) the mostly highly expressed sequences. Here, we show the capabilities of the visualization tool and its validation using human brain samples from patients with Parkinson's disease.
Reference Key
pantano2019visualizationf1000research Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Pantano, Lorena;Pantano, Francisco;Marti, Eulalia;Ho Sui, Shannan;
Journal F1000Research
Year 2019
DOI
ISCB Comm J-232
URL
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.