geneSim: Similarity score genes based on pathways similarity

In BioCor: Functional similarities

Description

Given two genes, calculates the Dice similarity between each pathway which is combined to obtain a similarity between the genes.

Usage

geneSim(gene1, gene2, info, method = "max", ...)

## S4 method for signature 'character,character,GeneSetCollection'
geneSim(gene1, gene2, info, method = "max", ...)

Arguments

gene1, gene2	Ids of the genes to calculate the similarity, to be found in genes.
info	A GeneSetCollection or a list of genes and the pathways they are involved.
method	one of c("avg", "max", "rcmax", "rcmax.avg", "BMA", "reciprocal"), see Details.
...	Other arguments passed to combineScores

Details

Given the information about the genes and their pathways, uses the ids of the genes to find the Dice similarity score for each pathway comparison between the genes. Later this similarities are combined using combineScoresPar.

Value

The highest Dice score of all the combinations of pathways between the two ids compared if a method to combine scores is provided or NA if there isn't information for one gene. If an NA is returned this means that there isn't information available for any pathways for one of the genes. Otherwise a number between 0 and 1 (both included) is returned. Note that there isn't a negative value of similarity.

Methods (by class)

• gene1 = character,gene2 = character,info = GeneSetCollection: Calculates all the similarities of the GeneSetCollection and combine them using combineScoresPar

Author(s)

Llu<c3><ad>s Revilla

See Also

mgeneSim, conversions help page to transform Dice score to Jaccard score. For the method to combine the scores see combineScoresPar.

Examples

if (require("org.Hs.eg.db") & require("reactome.db")) {
    # Extract the paths of all genes of org.Hs.eg.db from KEGG
    # (last update in data of June 31st 2011)
    genes.kegg <- as.list(org.Hs.egPATH)
    # Extracts the paths of all genes of org.Hs.eg.db from reactome
    genes.react <- as.list(reactomeEXTID2PATHID)
    geneSim("81", "18", genes.react)
    geneSim("81", "18", genes.kegg)
    geneSim("81", "18", genes.react, NULL)
    geneSim("81", "18", genes.kegg, NULL)
} else {
    warning('You need reactome.db and org.Hs.eg.db package for this example')
}

Example output

If you use BioCor in published research, please cite:
Loading required package: org.Hs.eg.db
Loading required package: AnnotationDbi
Loading required package: stats4
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, sd, var, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colMeans, colSums, colnames, do.call,
    duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
    lapply, lengths, mapply, match, mget, order, paste, pmax, pmax.int,
    pmin, pmin.int, rank, rbind, rowMeans, rowSums, rownames, sapply,
    setdiff, sort, table, tapply, union, unique, unsplit, which,
    which.max, which.min

Loading required package: Biobase
Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

Loading required package: IRanges
Loading required package: S4Vectors

Attaching package: 'S4Vectors'

The following object is masked from 'package:base':

    expand.grid

Loading required package: reactome.db
      00250 00280 00410 00640 00650       01100
04510     0     0     0     0     0 0.001503759
04520     0     0     0     0     0 0.000000000
04530     0     0     0     0     0 0.000000000
04670     0     0     0     0     0 0.003210273
04810     0     0     0     0     0 0.004467610
05146     0     0     0     0     0 0.011326861
05322     0     0     0     0     0 0.000000000
05412     0     0     0     0     0 0.000000000

BioCor documentation built on Nov. 8, 2020, 4:56 p.m.