Plots "check.marker" object, as returned by
check.marker
Usage
## S3 method for class 'check.marker'
plot(x, y, ...)
Arguments
x
Object of class "check.marker", as returned by check.marker
or snp.subset
y
this argument is not used
...
other arguments to be passed to plot
Details
In this plot, along the X axes, you can see colour representation of
markers which did not pass (pass – black) the QC. The diagonal
shows redundant markers. If for some marker there exist markers,
which show exactly the same (or some minimum concordance)
genotypic distribution, such
markers are depicted as crosses an solid line is dropped on
the X axes from it. Other solid line connects the original
SNP with the redundant ones (depicted as circles). From each
redundant SNP, a dashed line is dropped on X. Normally, one
expects that redundant markers are positioned very closely and
redundancy appears because of linkage disequilibrium.
Value
No value returned. Explanatory note is shown on the screen.
Author(s)
Yurii Aulchenko
See Also
check.marker,
snp.subset
Examples
require(GenABEL.data)
data(srdta)
mc <- check.marker(data=srdta@gtdata[,1:100],redundant="all",maf=0.01,
minconcordance=0.9,fdr=.1,ibs.mrk=0)
mc <- check.marker(data=srdta@gtdata[,1:100],maf=0.01,fdr=.1,ibs.mrk=0)
plot(mc)
mc1 <- snp.subset(mc,snps=srdta@gtdata@snpnames[20:40])
plot(mc1)
Results
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(GenABEL)
Loading required package: MASS
Loading required package: GenABEL.data
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/GenABEL/plot.check.marker.Rd_%03d_medium.png", width=480, height=480)
> ### Name: plot.check.marker
> ### Title: plots "check.marker" object
> ### Aliases: plot.check.marker
> ### Keywords: hplot
>
> ### ** Examples
>
> require(GenABEL.data)
> data(srdta)
> mc <- check.marker(data=srdta@gtdata[,1:100],redundant="all",maf=0.01,
+ minconcordance=0.9,fdr=.1,ibs.mrk=0)
Excluding people/markers with extremely low call rate...
100 markers and 2500 people in total
0 people excluded because of call rate < 0.1
0 markers excluded because of call rate < 0.1
Passed: 100 markers and 2500 people
RUN 1
100 markers and 2500 people in total
0 (0%) markers excluded as having low (<1%) minor allele frequency
37 (37%) markers excluded because of low (<95%) call rate
2 (2%) markers excluded because they are out of HWE (FDR <0.1)
823 (32.92%) people excluded because of low (<95%) call rate
Mean autosomal HET is 0.3487854 (s.e. 0.1133168)
0 people excluded because too high autosomal heterozygosity (FDR <1%)
In total, 61 (61%) markers passed all criteria
In total, 1677 (67.08%) people passed all criteria
RUN 2
61 markers and 1677 people in total
0 (0%) markers excluded as having low (<1%) minor allele frequency
0 (0%) markers excluded because of low (<95%) call rate
0 (0%) markers excluded because they are out of HWE (FDR <0.1)
0 (0%) people excluded because of low (<95%) call rate
Mean autosomal HET is 0.3492996 (s.e. 0.1143979)
0 people excluded because too high autosomal heterozygosity (FDR <1%)
In total, 61 (100%) markers passed all criteria
In total, 1677 (100%) people passed all criteria
CHECK REDUNDANCY
61 markers and 1677 people in total
6 (9.836066%) markers excluded as redundant (option = "all")
0 (0%) markers excluded as having low (<1%) minor allele frequency
0 (0%) markers excluded because of low (<95%) call rate
0 (0%) markers excluded because they are out of HWE (FDR <0.1)
418 (24.92546%) people excluded because of low (<95%) call rate
Mean autosomal HET is 0.3445665 (s.e. 0.1100367)
0 people excluded because too high autosomal heterozygosity (FDR <1%)
In total, 55 (90.16393%) markers passed all criteria
In total, 1259 (75.07454%) people passed all criteria
> mc <- check.marker(data=srdta@gtdata[,1:100],maf=0.01,fdr=.1,ibs.mrk=0)
Excluding people/markers with extremely low call rate...
100 markers and 2500 people in total
0 people excluded because of call rate < 0.1
0 markers excluded because of call rate < 0.1
Passed: 100 markers and 2500 people
RUN 1
100 markers and 2500 people in total
0 (0%) markers excluded as having low (<1%) minor allele frequency
37 (37%) markers excluded because of low (<95%) call rate
2 (2%) markers excluded because they are out of HWE (FDR <0.1)
823 (32.92%) people excluded because of low (<95%) call rate
Mean autosomal HET is 0.3487854 (s.e. 0.1133168)
0 people excluded because too high autosomal heterozygosity (FDR <1%)
In total, 61 (61%) markers passed all criteria
In total, 1677 (67.08%) people passed all criteria
RUN 2
61 markers and 1677 people in total
0 (0%) markers excluded as having low (<1%) minor allele frequency
0 (0%) markers excluded because of low (<95%) call rate
0 (0%) markers excluded because they are out of HWE (FDR <0.1)
0 (0%) people excluded because of low (<95%) call rate
Mean autosomal HET is 0.3492996 (s.e. 0.1143979)
0 people excluded because too high autosomal heterozygosity (FDR <1%)
In total, 61 (100%) markers passed all criteria
In total, 1677 (100%) people passed all criteria
> plot(mc)
Red: no call
Yellow: low frequency
Green: out of HWE
Cyan: redundant
Diagonal: redundant markers (reference presented as "+")
> mc1 <- snp.subset(mc,snps=srdta@gtdata@snpnames[20:40])
> plot(mc1)
Red: no call
Yellow: low frequency
Green: out of HWE
Cyan: redundant
Diagonal: redundant markers (reference presented as "+")
>
>
>
>
>
> dev.off()
null device
1
>