However, in order to fully utilize the statistical and graphical capabilities of the R language and make the InterMine framework available to an even greater number of life scientists, the goals were set to:
- Further develop and publish the InterMineR package to Bioconductor, a widely used, open source software project based in R, which aims to facilitate the integrative analysis of biological data derived from high-throughput assays.
- Add visualisation capabilities, e.g. “What features are close to my feature of interest?”
- Add enrichment analysis in InterMineR, a feature that will provide R users with access to the InterMine enrichment analysis widgets and can be effectively combined with the graphical capabilities of R libraries.
InterMineR performs a call to the InterMine Registry to retrieve up-to-date information about the available Mines. The information retrieved are then used to connect the Mines with the R environment using the InterMine web services.
The InterMineR package can be used to perform complicated queries on a Mine. The process is facilitated by the retrieval of the data model and the ready-to-use template queries of the respective Mine. The R functions setConstraints and setQuery have been created along with the formal class InterMineR, to create new or modify existing queries, store them as Intermine-class objects and apply them to the Mine with the runQuery method.
Figure 1: Gene visualisation done via InterMineR AND GVIZ
InterMineR can retrieve genomic coordinates and gene expression analysis data which can be converted to:
with the R functions convertToGRanges and convertToRangedSummarizedExperiment respectively. This way an interaction layer between InterMineR and other Bioconductor packages (e.g. GenomicRanges and SummarizedExperiment) is established, allowing for rapid analysis of the retrieved InterMine data.
Enrichment + GeneAnswers
InterMineR also retrieves InterMine enrichment widgets and facilitates the enrichment analysis on an InterMine instance using the R functions getWidgets and doEnrichment, respectively. With the usage of the R function convertToGeneAnswers the results of the enrichment analysis are converted to a GeneAnswers-class object, therefore allowing the visualization of:
- Pie charts
- Bar plots
- Concept-gene networks
- Annotation category (e.g. GO terms, KEGG pathways) – interaction networks
- Gene interaction networks
by using R functions from the GeneAnswers R package.
Figure 2: GeneAnswers GO structure network, generated via InterMineR
Figure 3: GeneAnswers gene network generated using InterMineR
Final steps: Bioconductor & Vignettes
The updated InterMineR package complies to the instructions for submitting new packages to Bioconductor, has passed all automated checks (R CMD build, check and BiocCheck) and is currently under the process of manual review for Bioconductor submission.
Documentation of each function along with examples of its usage are available in the GitHub repo and as help files upon the installation of the package. Furthermore, a detailed vignette and tutorials concerning the new functionality of InterMineR package are currently available at the intermine/InterMineR/vignettes folder of the GitHub dev branch, and will be shortly available on the GitHub master branch as well.
This project is part of Google Summer of Code, still under development by me, Konstantinos Kyritsis, PhD student at the Aristotle University of Thessaloniki, under the mentoring of Julie Sullivan and Rachel Lyne. The GitHub repository of the InterMineR package can be found at https://github.com/intermine/InterMineR.
Commits made my Konstantinos can be found here: https://github.com/intermine/InterMineR/commits/master?author=kostaskyritsis