Description Usage Arguments Details Value Author(s) See Also Examples
This is a generic function.
When implemented as the S4 method for objects of class GSCA
or NWA
,
this function filters out invalid data, removes duplicated genes,
converts annotations to Entrez identifiers, etc.
To use this function for objects of class GSCA
:
preprocess(object, species="Dm", initialIDs="FlybaseCG", keepMultipleMappings =TRUE, duplicateRemoverMethod="max", orderAbsValue=FALSE, verbose=TRUE)
To use this function for objects of NWA
:
preprocess(object, species="Dm", initialIDs="FlybaseCG", keepMultipleMappings =TRUE, duplicateRemoverMethod="max", verbose=TRUE)
1 | preprocess(object, ...)
|
object |
an object. When this function is implemented as the S4 method of class |
... |
other arguments depending on class (see below for the arguments supported by
class |
a single character value specifying the species for which the data should be read. The current version supports one of the following species: "Dm" ("Drosophila_melanogaster"), "Hs" ("Homo_sapiens"), "Rn" ("Rattus_ norvegicus"), "Mm" ("Mus_musculus"), "Ce" ("Caenorhabditis_elegans"). This is an optional argument here. If it is provided, then the labels of nodes of the identified subnetwork will be mapped from Entrez IDs to gene symbols; otherwise, Entrez IDs will be used as labels for those nodes.
a single character value specifying the type of initial identifiers for input 'geneList'. Current version can take one of the following types: "Ensembl.transcript", "Ensembl.prot", "Ensembl.gene", "Entrez.gene", "RefSeq", "Symbol" and "GenBank" for all supported species; "Flybase", "FlybaseCG" and "FlybaseProt" in addition for Drosophila Melanogaster; "wormbase" in addition for Caenorhabditis Elegans.
a single logical value. If 'TRUE', the function keeps the entries with multiple mappings (first mapping is kept). If 'FALSE', the entries with multiple mappings will be discarded.
a single character value specifying the method to remove the duplicates (should the minimum, maximum or average observation for a same construct be kept). Current version provides "min" (minimum), "max" (maximum), "average" and "fc.avg" (fold change average). The minimum and maximum should be understood in terms of absolute values (i.e. min/max effect, no matter the sign). The fold change average method converts the fold changes to ratios, averages them and converts the average back to a fold change.
a single logical value indicating whether the values should be converted
to absolute values and then ordered (if TRUE), or ordered as they are (if
FALSE). This argument is only for class GSCA
.
a single logical value suggesting to display detailed messages (when verbose=TRUE) or not (when verbose=FALSE)
This function will do the following preprocessing steps:
filter out p-values (the slot pvalues
of class NWA
),
phenotypes (the slot phenotypes
of class NWA
) and data for
enrichment (the slot geneList
of class GSCA
) with NA values
or without valid names, and invalid gene names (the slot hits
of class
GSCA
);
invoke function duplicateRemover
to remove duplicated genes
in the slot pvalues
, phenotypes
of class NWA
, and the
slot geneList
and hits
of class GSCA
;
invoke function annotationConvertor
to convert annotations from
initialIDs
to Entrez identifiers. Please note that the slot hits
and
the names of the slot geneList
of class GSCA
, the names of the slot
pvalues
and the names of the slot phenotypes
of class NWA
must
have the same type of gene annotation specified by initialIDs
;
order the data for enrichment decreasingly for objects of
class GSCA
.
See the function duplicateRemover
for more details about how to remove duplicated
genes.
See the function annotationConvertor
for more details about how to convert
annotations.
In the end, this function will return an updated object of class GSCA
or NWA
.
Xin Wang xw264@cam.ac.uk
duplicateRemover
, annotationConvertor
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | ## Not run:
library(org.Dm.eg.db)
library(KEGG.db)
##load data for enrichment analyses
data("KcViab_Data4Enrich")
##select hits
hits <- names(KcViab_Data4Enrich)[which(abs(KcViab_Data4Enrich) > 2)]
##set up a list of gene set collections
PW_KEGG <- KeggGeneSets(species = "Dm")
gscList <- list(PW_KEGG = PW_KEGG)
##create an object of class 'GSCA'
gsca <- new("GSCA", listOfGeneSetCollections=gscList, geneList =
KcViab_Data4Enrich, hits = hits)
##print gsca
summarize(gsca, what = c("GeneList", "Hits"))
##do preprocessing (KcViab_Data4Enrich has already been preprocessed)
gsca <- preprocess(gsca, species="Dm", initialIDs = "Entrez.gene",
keepMultipleMappings = TRUE, duplicateRemoverMethod = "max",
orderAbsValue = FALSE)
##print updated object
summarize(gsca, what = c("GeneList", "Hits"))
## End(Not run)
|
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