Supplementary Material for: Leveraging Online Resources to Prioritize Candidate Genes for Functional Analyses: Using the Fetal Testis as a Test Case
McClelland K.S.
Yao H.H.-C.
10.6084/m9.figshare.4649866.v1
https://karger.figshare.com/articles/dataset/Supplementary_Material_for_Leveraging_Online_Resources_to_Prioritize_Candidate_Genes_for_Functional_Analyses_Using_the_Fetal_Testis_as_a_Test_Case/4649866
<p>With each new microarray or RNA-seq experiment, massive quantities of
transcriptomic information are generated with the purpose to produce a
list of candidate genes for functional analyses. Yet an effective
strategy remains elusive to prioritize the genes on these candidate
lists. In this review, we outline a prioritizing strategy by taking a
step back from the bench and leveraging the rich range of public
databases. This in silico approach provides an economical, less biased,
and more effective solution. We discuss the publicly available online
resources that can be used to answer a range of questions about a gene.
Is the gene of interest expressed in the system of interest (using
expression databases)? Where else is this gene expressed (using
added-value transcriptomic resources)? What pathways and processes is
the gene involved in (using enriched gene pathway analysis and mouse
knockout databases)? Is this gene correlated with human diseases (using
human disease variant databases)? Using mouse fetal testis as an
example, our strategies identified 298 genes annotated as expressed in
the fetal testis. We cross-referenced these genes to existing microarray
data and narrowed the list down to cell-type-specific candidates (35
for Sertoli cells, 11 for Leydig cells, and 25 for germ cells). Our
strategies can be customized so that they allow researchers to
effectively and confidently prioritize genes for functional analysis.</p>
2017-02-14 11:49:08
Candidate gene
Databases
Data mining
Enrichment
Expression atlas
Gene prioritization
GO terms
Knowledgebases
Ontology
Ovary
Sex determination
Testis
Transcriptomics