View source: R/top.discriminator.R
top.discriminator | R Documentation |
Detects top discriminators that contribute to group separation based on the fixation index (Fst).
top.discriminator( cluster.obj = NULL, group1, group2, bim.file, use.node.number = FALSE, num.top = 100, percentile = 0.9, use.percentile = FALSE, use.path = FALSE, result.path = NULL )
cluster.obj |
The object which is returned from |
group1 |
To specify the first group number to be compared. (also see
|
group2 |
To specify the second group number to be compared. (also see
|
bim.file |
Option: In case that SNP information is not provided to
|
use.node.number |
To specify whether a group number or a node number is be used. If TRUE, a node nubmer is used instead. Default = FALSE. |
num.top |
A number of top Fst SNPs to be returned. This parameter is
used when |
percentile |
A percentile for top Fst SNPs to be returned. This parameter
is used when |
use.percentile |
A logical value to indicate whether |
use.path |
A logical value to indicate whether |
result.path |
A path to an result directory of IPCAPS2. This parameter is
used when |
The returned value is a data.frame of SNP information sorting by Fst in descending order, which contains 7 columns, chr, SNP, centimorgans, position, allele1, allele2, and Fst. The column 1-6 are SNP information from the bim file. The column Fst contains estimated Fst between group1 and group2.
# Importantly, bed file, bim file, and fam file are required # Use the example files embedded in the package BED.file <- system.file("extdata","ipcaps_example.bed",package="IPCAPS2") LABEL.file <- system.file("extdata","ipcaps_example_individuals.txt.gz",package="IPCAPS2") my.cluster <- ipcaps2(bed=BED.file, label.file=LABEL.file, lab.col=2, out=tempdir(), silence=TRUE, no.rep=1) table(my.cluster$cluster$label,my.cluster$cluster$group) # 1 2 3 4 5 6 # outlier4 5 4 1 0 0 0 # pop1 0 0 0 0 250 0 # pop2 0 0 0 0 0 250 # pop3 0 0 0 250 0 0 #Identify top discriminators between groups, for example, group 4 and group 5 top.snp <-top.discriminator(my.cluster,4,5) #or, specify the bim file #top.snp <-top.discriminator(my.cluster,4,5,bim.file="ipcaps_example.bim") head(top.snp) # chr SNP centimorgans position allele1 allele2 Fst #V5452 1 marker5452 0 54520000 A T 0.11337260 #V2348 1 marker2348 0 23480000 A T 0.11194490 #V8244 1 marker8244 0 82440000 A T 0.09556580 #V5972 1 marker5972 0 59720000 A T 0.08747794 #V3561 1 marker3561 0 35610000 A T 0.08725860 #V8419 1 marker8419 0 84190000 A T 0.08293494 #Alternatively, specify the previous result directory of IPCAPS and identify #top discriminators between groups, for example, group 4 and group 5 previous.res.path <- my.cluster$output.dir top.snp <-top.discriminator(result.path = previous.res.path, use.path = TRUE, group1 = 4, group2 = 5) head(top.snp) #Identify top discriminators between groups, for example, group 4 and group 5 top.snp <-top.discriminator(my.cluster,4,5) #or, specify the bim file #top.snp <-top.discriminator(my.cluster,4,5,bim.file="ipcaps_example.bim") dim(top.snp) head(top.snp) #Here, it is possible to select the top Fst SNPs based on a percentile. top.snp <-top.discriminator(my.cluster,4,5, percentile = 0.9, use.percentile = TRUE) dim(top.snp) head(top.snp) #Identify top discriminators between groups, for example, node 7 and node 8 top.snp2 <-top.discriminator(my.cluster,7,8,use.node.number=TRUE) head(top.snp2) # chr SNP centimorgans position allele1 allele2 Fst #V5452 1 marker5452 0 54520000 A T 0.11337260 #V2348 1 marker2348 0 23480000 A T 0.11194490
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