Setup of a LowMACA object

Description

A wrapper around alignSequences , getMutations and mapMutations in order to execute all these methods at once.

Usage

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setup(object, repos = NULL, clustalo_filename=NULL 
	, mail=NULL , perlCommand="perl", use_hmm=FALSE, datum=FALSE)

Arguments

object

an object of class LowMACA

repos

a data.frame containing mutations for the specified genes in the LowMACA object in case of custom mutation data. Default NULL

clustalo_filename

a character string that contains the file name where clustal omega alignment file will be stored. In case it's NULL no file will be written. Default=NULL

mail

a character string indicating the email address where error report should be sent in web mode. Default is NULL, to use a local clustalo installation

perlCommand

a character string containing the path to Perl executable. if missing, "perl" will be used as default

use_hmm

When analysing Pfam sequences, it is possible to use the Hidden Markov Model (HMM) of the specific Pfam to align the sequences. Default is FALSE.

datum

When analysing Pfam sequences, use all the genes that belong to the Pfam to generate the alignment. This creates a unique mapping between individual residues and consensus sequence, disregarding the set of sequences that are selected for the analysis. Default is FALSE.

Details

If mail is not NULL, a local installation of clustal omega is no longer required and the alignment is performed using clustal omega EBI web service. A limit of 2000 sequences is set in this case and perl is required with XML::Simple and LWP modules installed

Value

An object of class LowMACA with all the updates provided by alignSequences , getMutations and mapMutations methods.

Author(s)

Stefano de Pretis , Giorgio Melloni

References

Trident Score Clustal Omega Clustal Omega Web Service

See Also

alignSequences getMutations mapMutations

Examples

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#Create an object of class LowMACA for RAS domain family
lm <- newLowMACA(pfam="PF00071" , genes=c("KRAS" , "NRAS" , "HRAS"))
#Select a few tumor types
lmParams(lm)$tumor_type <- c("skcm" , "brca" , "coadread")
#Align sequences, get mutation data and map them on consensus
lm <- setup(lm)
#Same as above, but using web service
lm <- setup(lm , mail="lowmaca@gmail.com")
#Use HMM to align
lm <- setup(lm , use_hmm=TRUE)
#Use "datum"
lm <- setup(lm , datum=TRUE)