snpgdsIBDKING: KING method of moment for the identity-by-descent (IBD)...
In SNPRelate: Parallel Computing Toolset for Relatedness and Principal Component Analysis of SNP Data
Description
Usage
Arguments
Details
Value
Author(s)
References
See Also
Examples
Description
Calculate IBD coefficients by KING method of moment.
Usage
1
2
3
4
Arguments
gdsobj
an object of class SNPGDSFileClass,
a SNP GDS file
sample.id
a vector of sample id specifying selected samples; if NULL,
all samples are used
snp.id
a vector of snp id specifying selected SNPs;
if NULL, all SNPs are used
autosome.only
if TRUE, use autosomal SNPs only; if it is a
numeric or character value, keep SNPs according to the specified
chromosome
remove.monosnp
if TRUE, remove monomorphic SNPs
maf
to use the SNPs with ">= maf" only; if NaN, no MAF threshold
missing.rate
to use the SNPs with "<= missing.rate" only; if NaN, no
missing threshold
type
"KING-robust" – relationship inference in the presence
of population stratification; "KING-homo" – relationship
inference in a homogeneous population
family.id
if NULL, all individuals are treated as singletons;
if family id is given, within- and between-family relationship are
estimated differently. If sample.id=NULL, family.id
should have the same length as "sample.id" in the GDS file, otherwise
family.id should have the same length and order as the argument
sample.id
num.thread
the number of (CPU) cores used; if NA, detect
the number of cores automatically
useMatrix
if TRUE, use Matrix::dspMatrix to store
the output square matrix to save memory
verbose
if TRUE, show information
Details
KING IBD estimator is a moment estimator, and it is computationally
efficient relative to MLE method. The approaches include "KING-robust"
– robust relationship inference within or across families in the presence of
population substructure, and "KING-homo" – relationship inference in
a homogeneous population.
With "KING-robust", the function would return the proportion of SNPs
with zero IBS (IBS0) and kinship coefficient (kinship). With
"KING-homo" it would return the probability of sharing one IBD
(k1) and the probability of sharing zero IBD (k0).
The minor allele frequency and missing rate for each SNP passed in
snp.id are calculated over all the samples in sample.id.
Value
Return a list:
sample.id
the sample ids used in the analysis
snp.id
the SNP ids used in the analysis
k0
IBD coefficient, the probability of sharing zero IBD
k1
IBD coefficient, the probability of sharing one IBD
IBS0
proportion of SNPs with zero IBS
kinship
the estimated kinship coefficients, if the parameter
kinship=TRUE
Author(s)
Xiuwen Zheng
References
Manichaikul A, Mychaleckyj JC, Rich SS, Daly K, Sale M, Chen WM.
Robust relationship inference in genome-wide association studies.
Bioinformatics. 2010 Nov 15;26(22):2867-73.
See Also
Examples
1
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# open an example dataset (HapMap)
genofile <- snpgdsOpen(snpgdsExampleFileName())
# CEU population
samp.id <- read.gdsn(index.gdsn(genofile, "sample.id"))
CEU.id <- samp.id[
read.gdsn(index.gdsn(genofile, "sample.annot/pop.group"))=="CEU"]
#### KING-robust:
#### relationship inference in the presence of population stratification
#### robust relationship inference across family
ibd.robust <- snpgdsIBDKING(genofile, sample.id=CEU.id)
names(ibd.robust)
# [1] "sample.id" "snp.id" "afreq" "IBS0" "kinship"
# select a set of pairs of individuals
dat <- snpgdsIBDSelection(ibd.robust, 1/32)
head(dat)
plot(dat$IBS0, dat$kinship, xlab="Proportion of Zero IBS",
ylab="Estimated Kinship Coefficient (KING-robust)")
# using Matrix
ibd.robust <- snpgdsIBDKING(genofile, sample.id=CEU.id, useMatrix=TRUE)
is(ibd.robust$IBS0) # dspMatrix
is(ibd.robust$kinship) # dspMatrix
#### KING-robust:
#### relationship inference in the presence of population stratification
#### within- and between-family relationship inference
# incorporate with pedigree information
family.id <- read.gdsn(index.gdsn(genofile, "sample.annot/family.id"))
family.id <- family.id[match(CEU.id, samp.id)]
ibd.robust2 <- snpgdsIBDKING(genofile, sample.id=CEU.id, family.id=family.id)
names(ibd.robust2)
# select a set of pairs of individuals
dat <- snpgdsIBDSelection(ibd.robust2, 1/32)
head(dat)
plot(dat$IBS0, dat$kinship, xlab="Proportion of Zero IBS",
ylab="Estimated Kinship Coefficient (KING-robust)")
#### KING-homo: relationship inference in a homogeneous population
ibd.homo <- snpgdsIBDKING(genofile, sample.id=CEU.id, type="KING-homo")
names(ibd.homo)
# "sample.id" "snp.id" "afreq" "k0" "k1"
# select a subset of pairs of individuals
dat <- snpgdsIBDSelection(ibd.homo, 1/32)
head(dat)
plot(dat$k0, dat$kinship, xlab="Pr(IBD=0)",
ylab="Estimated Kinship Coefficient (KING-homo)")
# using Matrix
ibd.homo <- snpgdsIBDKING(genofile, sample.id=CEU.id, type="KING-homo",
useMatrix=TRUE)
is(ibd.homo$k0) # dspMatrix
is(ibd.homo$k1) # dspMatrix
# close the genotype file
snpgdsClose(genofile)
Example output
Loading required package: gdsfmt
SNPRelate -- supported by Streaming SIMD Extensions 2 (SSE2)
IBD analysis (KING method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1,217 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
# of samples: 92
# of SNPs: 7,506
using 1 thread
No family is specified, and all individuals are treated as singletons.
Relationship inference in the presence of population stratification.
KING IBD: the sum of all selected genotypes (0,1,2) = 702139
CPU capabilities: Double-Precision SSE2
Fri Apr 23 09:38:25 2021 (internal increment: 39808)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Fri Apr 23 09:38:25 2021 Done.
[1] "sample.id" "snp.id" "afreq" "IBS0" "kinship"
ID1 ID2 IBS0 kinship
1 NA07034 NA07048 0.0001342102 0.24495171
2 NA07034 NA12873 0.0520145533 0.03284983
3 NA07055 NA07048 0.0000000000 0.25153644
4 NA12814 NA12802 0.0002680606 0.25291074
5 NA10847 NA12239 0.0000000000 0.23510079
6 NA10847 NA12146 0.0000000000 0.24659640
IBD analysis (KING method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1,217 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
# of samples: 92
# of SNPs: 7,506
using 1 thread
No family is specified, and all individuals are treated as singletons.
Relationship inference in the presence of population stratification.
KING IBD: the sum of all selected genotypes (0,1,2) = 702139
CPU capabilities: Double-Precision SSE2
Fri Apr 23 09:38:25 2021 (internal increment: 39808)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Fri Apr 23 09:38:25 2021 Done.
[1] "dspMatrix" "ddenseMatrix" "symmetricMatrix" "dMatrix"
[5] "denseMatrix" "compMatrix" "Matrix" "xMatrix"
[9] "mMatrix" "Mnumeric" "replValueSp"
[1] "dspMatrix" "ddenseMatrix" "symmetricMatrix" "dMatrix"
[5] "denseMatrix" "compMatrix" "Matrix" "xMatrix"
[9] "mMatrix" "Mnumeric" "replValueSp"
IBD analysis (KING method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1,217 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
# of samples: 92
# of SNPs: 7,506
using 1 thread
# of families: 20, and within- and between-family relationship are estimated differently.
Relationship inference in the presence of population stratification.
KING IBD: the sum of all selected genotypes (0,1,2) = 702139
CPU capabilities: Double-Precision SSE2
Fri Apr 23 09:38:26 2021 (internal increment: 39808)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Fri Apr 23 09:38:26 2021 Done.
[1] "sample.id" "snp.id" "afreq" "IBS0" "kinship"
ID1 ID2 IBS0 kinship
1 NA07034 NA07048 0.0001342102 0.24891962
2 NA07034 NA12873 0.0520145533 0.03284983
3 NA07055 NA07048 0.0000000000 0.25305410
4 NA12814 NA12802 0.0002680606 0.25344234
5 NA10847 NA12239 0.0000000000 0.23966408
6 NA10847 NA12146 0.0000000000 0.25000000
IBD analysis (KING method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1,217 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
# of samples: 92
# of SNPs: 7,506
using 1 thread
Relationship inference in a homogeneous population.
KING IBD: the sum of all selected genotypes (0,1,2) = 702139
Fri Apr 23 09:38:26 2021 (internal increment: 39808)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Fri Apr 23 09:38:26 2021 Done.
[1] "sample.id" "snp.id" "afreq" "k0" "k1"
ID1 ID2 k0 k1 kinship
1 NA07034 NA07048 0.002253744 1.0058457 0.2474117
2 NA07055 NA07048 0.000000000 0.9828815 0.2542796
3 NA12814 NA12802 0.004503063 0.9863919 0.2511505
4 NA10847 NA12239 0.000000000 1.0529144 0.2367714
5 NA10847 NA12146 0.000000000 1.0054915 0.2486271
6 NA12056 NA10851 0.002247289 0.9991049 0.2491001
IBD analysis (KING method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1,217 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
# of samples: 92
# of SNPs: 7,506
using 1 thread
Relationship inference in a homogeneous population.
KING IBD: the sum of all selected genotypes (0,1,2) = 702139
Fri Apr 23 09:38:26 2021 (internal increment: 39808)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 1s
Fri Apr 23 09:38:27 2021 Done.
[1] "dspMatrix" "ddenseMatrix" "symmetricMatrix" "dMatrix"
[5] "denseMatrix" "compMatrix" "Matrix" "xMatrix"
[9] "mMatrix" "Mnumeric" "replValueSp"
[1] "dspMatrix" "ddenseMatrix" "symmetricMatrix" "dMatrix"
[5] "denseMatrix" "compMatrix" "Matrix" "xMatrix"
[9] "mMatrix" "Mnumeric" "replValueSp"
SNPRelate documentation built on Nov. 8, 2020, 5:31 p.m.
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Description Usage Arguments Details Value Author(s) References See Also Examples
Description
Calculate IBD coefficients by KING method of moment.
Usage
1 2 3 4 |
Arguments
gdsobj |
an object of class |
sample.id |
a vector of sample id specifying selected samples; if NULL, all samples are used |
snp.id |
a vector of snp id specifying selected SNPs; if NULL, all SNPs are used |
autosome.only |
if |
remove.monosnp |
if TRUE, remove monomorphic SNPs |
maf |
to use the SNPs with ">= maf" only; if NaN, no MAF threshold |
missing.rate |
to use the SNPs with "<= missing.rate" only; if NaN, no missing threshold |
type |
|
family.id |
if |
num.thread |
the number of (CPU) cores used; if |
useMatrix |
if |
verbose |
if TRUE, show information |
Details
KING IBD estimator is a moment estimator, and it is computationally
efficient relative to MLE method. The approaches include "KING-robust"
– robust relationship inference within or across families in the presence of
population substructure, and "KING-homo" – relationship inference in
a homogeneous population.
With "KING-robust", the function would return the proportion of SNPs
with zero IBS (IBS0) and kinship coefficient (kinship). With
"KING-homo" it would return the probability of sharing one IBD
(k1) and the probability of sharing zero IBD (k0).
The minor allele frequency and missing rate for each SNP passed in
snp.id are calculated over all the samples in sample.id.
Value
Return a list:
sample.id |
the sample ids used in the analysis |
snp.id |
the SNP ids used in the analysis |
k0 |
IBD coefficient, the probability of sharing zero IBD |
k1 |
IBD coefficient, the probability of sharing one IBD |
IBS0 |
proportion of SNPs with zero IBS |
kinship |
the estimated kinship coefficients, if the parameter
|
Author(s)
Xiuwen Zheng
References
Manichaikul A, Mychaleckyj JC, Rich SS, Daly K, Sale M, Chen WM. Robust relationship inference in genome-wide association studies. Bioinformatics. 2010 Nov 15;26(22):2867-73.
See Also
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 | # open an example dataset (HapMap)
genofile <- snpgdsOpen(snpgdsExampleFileName())
# CEU population
samp.id <- read.gdsn(index.gdsn(genofile, "sample.id"))
CEU.id <- samp.id[
read.gdsn(index.gdsn(genofile, "sample.annot/pop.group"))=="CEU"]
#### KING-robust:
#### relationship inference in the presence of population stratification
#### robust relationship inference across family
ibd.robust <- snpgdsIBDKING(genofile, sample.id=CEU.id)
names(ibd.robust)
# [1] "sample.id" "snp.id" "afreq" "IBS0" "kinship"
# select a set of pairs of individuals
dat <- snpgdsIBDSelection(ibd.robust, 1/32)
head(dat)
plot(dat$IBS0, dat$kinship, xlab="Proportion of Zero IBS",
ylab="Estimated Kinship Coefficient (KING-robust)")
# using Matrix
ibd.robust <- snpgdsIBDKING(genofile, sample.id=CEU.id, useMatrix=TRUE)
is(ibd.robust$IBS0) # dspMatrix
is(ibd.robust$kinship) # dspMatrix
#### KING-robust:
#### relationship inference in the presence of population stratification
#### within- and between-family relationship inference
# incorporate with pedigree information
family.id <- read.gdsn(index.gdsn(genofile, "sample.annot/family.id"))
family.id <- family.id[match(CEU.id, samp.id)]
ibd.robust2 <- snpgdsIBDKING(genofile, sample.id=CEU.id, family.id=family.id)
names(ibd.robust2)
# select a set of pairs of individuals
dat <- snpgdsIBDSelection(ibd.robust2, 1/32)
head(dat)
plot(dat$IBS0, dat$kinship, xlab="Proportion of Zero IBS",
ylab="Estimated Kinship Coefficient (KING-robust)")
#### KING-homo: relationship inference in a homogeneous population
ibd.homo <- snpgdsIBDKING(genofile, sample.id=CEU.id, type="KING-homo")
names(ibd.homo)
# "sample.id" "snp.id" "afreq" "k0" "k1"
# select a subset of pairs of individuals
dat <- snpgdsIBDSelection(ibd.homo, 1/32)
head(dat)
plot(dat$k0, dat$kinship, xlab="Pr(IBD=0)",
ylab="Estimated Kinship Coefficient (KING-homo)")
# using Matrix
ibd.homo <- snpgdsIBDKING(genofile, sample.id=CEU.id, type="KING-homo",
useMatrix=TRUE)
is(ibd.homo$k0) # dspMatrix
is(ibd.homo$k1) # dspMatrix
# close the genotype file
snpgdsClose(genofile)
|
Example output
Loading required package: gdsfmt
SNPRelate -- supported by Streaming SIMD Extensions 2 (SSE2)
IBD analysis (KING method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1,217 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
# of samples: 92
# of SNPs: 7,506
using 1 thread
No family is specified, and all individuals are treated as singletons.
Relationship inference in the presence of population stratification.
KING IBD: the sum of all selected genotypes (0,1,2) = 702139
CPU capabilities: Double-Precision SSE2
Fri Apr 23 09:38:25 2021 (internal increment: 39808)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Fri Apr 23 09:38:25 2021 Done.
[1] "sample.id" "snp.id" "afreq" "IBS0" "kinship"
ID1 ID2 IBS0 kinship
1 NA07034 NA07048 0.0001342102 0.24495171
2 NA07034 NA12873 0.0520145533 0.03284983
3 NA07055 NA07048 0.0000000000 0.25153644
4 NA12814 NA12802 0.0002680606 0.25291074
5 NA10847 NA12239 0.0000000000 0.23510079
6 NA10847 NA12146 0.0000000000 0.24659640
IBD analysis (KING method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1,217 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
# of samples: 92
# of SNPs: 7,506
using 1 thread
No family is specified, and all individuals are treated as singletons.
Relationship inference in the presence of population stratification.
KING IBD: the sum of all selected genotypes (0,1,2) = 702139
CPU capabilities: Double-Precision SSE2
Fri Apr 23 09:38:25 2021 (internal increment: 39808)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Fri Apr 23 09:38:25 2021 Done.
[1] "dspMatrix" "ddenseMatrix" "symmetricMatrix" "dMatrix"
[5] "denseMatrix" "compMatrix" "Matrix" "xMatrix"
[9] "mMatrix" "Mnumeric" "replValueSp"
[1] "dspMatrix" "ddenseMatrix" "symmetricMatrix" "dMatrix"
[5] "denseMatrix" "compMatrix" "Matrix" "xMatrix"
[9] "mMatrix" "Mnumeric" "replValueSp"
IBD analysis (KING method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1,217 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
# of samples: 92
# of SNPs: 7,506
using 1 thread
# of families: 20, and within- and between-family relationship are estimated differently.
Relationship inference in the presence of population stratification.
KING IBD: the sum of all selected genotypes (0,1,2) = 702139
CPU capabilities: Double-Precision SSE2
Fri Apr 23 09:38:26 2021 (internal increment: 39808)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Fri Apr 23 09:38:26 2021 Done.
[1] "sample.id" "snp.id" "afreq" "IBS0" "kinship"
ID1 ID2 IBS0 kinship
1 NA07034 NA07048 0.0001342102 0.24891962
2 NA07034 NA12873 0.0520145533 0.03284983
3 NA07055 NA07048 0.0000000000 0.25305410
4 NA12814 NA12802 0.0002680606 0.25344234
5 NA10847 NA12239 0.0000000000 0.23966408
6 NA10847 NA12146 0.0000000000 0.25000000
IBD analysis (KING method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1,217 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
# of samples: 92
# of SNPs: 7,506
using 1 thread
Relationship inference in a homogeneous population.
KING IBD: the sum of all selected genotypes (0,1,2) = 702139
Fri Apr 23 09:38:26 2021 (internal increment: 39808)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 0s
Fri Apr 23 09:38:26 2021 Done.
[1] "sample.id" "snp.id" "afreq" "k0" "k1"
ID1 ID2 k0 k1 kinship
1 NA07034 NA07048 0.002253744 1.0058457 0.2474117
2 NA07055 NA07048 0.000000000 0.9828815 0.2542796
3 NA12814 NA12802 0.004503063 0.9863919 0.2511505
4 NA10847 NA12239 0.000000000 1.0529144 0.2367714
5 NA10847 NA12146 0.000000000 1.0054915 0.2486271
6 NA12056 NA10851 0.002247289 0.9991049 0.2491001
IBD analysis (KING method of moment) on genotypes:
Excluding 365 SNPs on non-autosomes
Excluding 1,217 SNPs (monomorphic: TRUE, MAF: NaN, missing rate: NaN)
# of samples: 92
# of SNPs: 7,506
using 1 thread
Relationship inference in a homogeneous population.
KING IBD: the sum of all selected genotypes (0,1,2) = 702139
Fri Apr 23 09:38:26 2021 (internal increment: 39808)
[..................................................] 0%, ETC: ---
[==================================================] 100%, completed, 1s
Fri Apr 23 09:38:27 2021 Done.
[1] "dspMatrix" "ddenseMatrix" "symmetricMatrix" "dMatrix"
[5] "denseMatrix" "compMatrix" "Matrix" "xMatrix"
[9] "mMatrix" "Mnumeric" "replValueSp"
[1] "dspMatrix" "ddenseMatrix" "symmetricMatrix" "dMatrix"
[5] "denseMatrix" "compMatrix" "Matrix" "xMatrix"
[9] "mMatrix" "Mnumeric" "replValueSp"
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