Tag Archives: R

use clusterProfiler as an universal enrichment analysis tool

clusterProfiler supports enrichment analysis of both hypergeometric test and gene set enrichment analysis. It internally supports Gene Ontology analysis of about 20 species, Kyoto Encyclopedia of Genes and Genomes (KEGG) with all species that have annotation available in KEGG database, DAVID annotation (only hypergeometric test supported), Disease Ontology and Network of Cancer Genes (via DOSE for human) and Reactome Pathway (via ReactomePA for several species). This is still not enough for users may want to analyze their data with unsupported organisms, slim version of GO, novel functional annotation (eg GO via blastgo and KEGG via KAAS), unsupported ontology/pathway or customized annotation.

clusterProfiler provides enricher function for hypergeometric test and GSEA function for gene set enrichment analysis that are designed to accept user defined annotation. They accept two additional parameters TERM2GENE and TERM2NAME. As indicated in the parameter names, TERM2GENE is a data.frame with first column of term ID and second column of corresponding mapped gene and TERM2NAME is a data.frame with first column of term ID and second column of corresponding term name. TERM2NAME is optional.
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using GOSemSim to rank proteins obtained by co-IP

Co-IP is usually used to identified interactions among specific proteins. It is widely used in detecting protein complex. Unfortunately, an identified protein may not be an interactor, and sometimes can be a background contaminant. Ranking proteins can help us to focus a study on a few high quality candidates for subsequent interaction investigation. My R package GOSemSim has been used in many studies to investigate protein protein interaction, see 1, 2, 3, 4 and more.

In the study, Proteomic investigation of the interactome of FMNL1 in hematopoietic cells unveils a role in calcium-dependent membrane plasticity, we investigate the interactors of FMNL1 by co-IP followed by LC-MS/MS analysis.

In this study, we defined functional similarity as the geometric mean of semantic similarities in molecular function and cellular component. Functional similarity is designed for measuring the strength of the relationship between each protein and its partners by considering function and location of proteins. The similarities were calculated through GOSemSim package. The distributions of the functional similarities were demonstrated in the following figure.

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[Bioc 3.1] NEWS of my BioC packages

GOSemSim

GOSemSim was first implemented in 2008 and published in Bioinformatics in 2010. It's now a mature package with no bugs found in the past half year. Only vignette and Information content data were updated.

clusterProfiler

clusterProfiler was developed in 2011 and published in OMICS in 2012.

I am very glad to find that clusterProfiler was presented in the book 'Bioinformatics with R Cookbook':

In this release, KEGG enrichment analysis (both hypergeometric and GSEA) now supports using latest online data and DAVID functional analysis is also supported. In addition, compareCluster function now supports formula interface like x ~ y + z; this feature was contributed by @dalloliogm.

Considering that many new users have problem of converting biological IDs, clusterProfiler contains a new function bitr, stands for Biological Id TranslatoR.
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an example of drawing beast tree using ggtree

FigTree is designed for viewing beast output as demonstrated by their example data:

BEAST output is well supported by ggtree and it's easy to reproduce such a tree view. ggtree supports parsing beast output by read.beast function. We can visualize the tree directly by using ggtree function. Since this is a time scale tree, we can set the parameter time_scale = TRUE and ggtree will parse the time and use it as branch length.
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DAVID functional analysis with clusterProfiler

clusterProfiler was used to visualize DAVID results in a paper published in BMC Genomics.

Some users told me that they may want to use DAVID at some circumstances. I think it maybe a good idea to make clusterProfiler supports DAVID, so that DAVID users can use visualization functions provided by clusterProfiler.
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