BCC2020

→ Abstract


The presenter(s) will be available for live Q&A in this session (BCC East).

Sangram Keshari Sahu

Independent Researcher, Banglore, India.

Email: sangramsahu15@gmail.com
Project Website: https://github.com/sk-sahu/sig-bio-shiny
Source Code: https://github.com/sk-sahu/sig-bio-shiny
Licence: MIT Licence

Detecting biological significance is an essential step for any high-throughput sequence analysis.
Once sequence reads are mapped and assembled, this is fol owed by different quantification
analysis which ends up with a set of features (transcript/gene). Quickly exploring those features
together from different angles along with statistical inference gives a good idea about the
biology they are involved.
Doing these kinds of exploration for a particular organism requires an up to date annotation
database. Currently available online/API platforms support either very few or only model
organisms. Apart from that, reproducibility is a primary issue as databases continual y updated.
To tackle these problems I am presenting SigBio-Shiny, a standalone interactive application
based on R-Shiny which supports more than just model organisms with no requirement of
manual database maintenance. It leverages available open-source resources such as
Bioconductor's AnnotationHub to col ect the organism's updated database in real-time with
keeping track of what version of the database used. On top of this database, it helps with
detecting biological significance on a set of genes by doing gene mapping, enrichment analysis
of Gene Ontology (GO) and Pathway analysis.
Keywords: Interactive application, Significant biology, Non-model Organism, Annotation
database, Gene mapping, Gene Ontology (GO), Pathway, Enrichment analysis