| Type: | Package |
| Title: | Single-Iteration Permutation for Large-Scale Biobank Data |
| Version: | 0.1.0 |
| Description: | A single, phenome-wide permutation of large-scale biobank data. When a large number of phenotypes are analyzed in parallel, a single permutation across all phenotypes followed by genetic association analyses of the permuted data enables estimation of false discovery rates (FDRs) across the phenome. These FDR estimates provide a significance criterion for interpreting genetic associations in a biobank context. For the basic permutation of unrelated samples, this package takes a sample-by-variable file with ID, genotypic covariates, phenotypic covariates, and phenotypes as input. For data with related samples, it also takes a file with sample pair-wise identity-by-descent information. The function outputs a permuted sample-by-variable file ready for genome-wide association analysis. See Annis et al. (2021) <doi:10.21203/rs.3.rs-873449/v1> for details. |
| URL: | https://github.com/acannis/SIP |
| BugReports: | https://github.com/acannis/SIP/issues |
| License: | MIT + file LICENSE |
| Encoding: | UTF-8 |
| LazyData: | true |
| Depends: | R (≥ 3.5) |
| Imports: | stats, data.table, ggplot2 |
| RoxygenNote: | 7.3.3 |
| Suggests: | testthat (≥ 3.0.0) |
| Config/testthat/edition: | 3 |
| NeedsCompilation: | no |
| Packaged: | 2025-12-02 14:26:37 UTC; mk |
| Author: | Aubrey Annis [aut, cre] |
| Maintainer: | Aubrey Annis <acannis@umich.edu> |
| Repository: | CRAN |
| Date/Publication: | 2025-12-09 08:00:02 UTC |
SIP-package internal setup
Description
Declares global variables and imports common functions used throughout the SIP package. This file is executed when the package is loaded.
This function subsets the sample-by-variable dataframe to the "fixed" (i.e., non-permuted) data. This subset should include ID variables, sex, and genotypic covariates.
Description
This function subsets the sample-by-variable dataframe to the "fixed" (i.e., non-permuted) data. This subset should include ID variables, sex, and genotypic covariates.
Usage
get_fixed(df, id.var = id.var, sex.var = sex.var, geno.vars = geno.vars)
Arguments
df |
Data frame |
id.var, sex.var |
String |
geno.vars |
Character vector |
Value
Data frame
This function samples individuals by pairs for permuting phenotype vectors in the paired-permutation function (sipPair.R)
Description
This function samples individuals by pairs for permuting phenotype vectors in the paired-permutation function (sipPair.R)
Usage
get_pairPerm(deglst, rid.vars = rid.vars, ibd.var = ibd.var, seed = seed)
Arguments
deglst |
List of data frames |
rid.vars |
Character vector |
ibd.var |
String |
seed |
Number |
Value
Data frame
This function recombines the fixed data and permuted data in the paired-permutation function (sipPair.R) into a permuted sample-by-variable data frame.
Description
This function recombines the fixed data and permuted data in the paired-permutation function (sipPair.R) into a permuted sample-by-variable data frame.
Usage
get_pairPermDF(fix.df, perm.df, perm.map, id.var = id.var)
Arguments
fix.df, perm.df, perm.map |
Data frames |
id.var |
String |
Value
Data frame
This function recombines the fixed data and permuted data into a permuted sample-by-variable data frame.
Description
This function recombines the fixed data and permuted data into a permuted sample-by-variable data frame.
Usage
get_permDF(fix.df, perm.df, perm.idx)
Arguments
fix.df, perm.df |
Data frames |
perm.idx |
Numeric vector |
Value
Data frame
This function samples indices for permuting phenotype vectors in the basic permutation function (sip.R) and for permuting leftover unpaired individuals in the paired-permutation function (sipPair.R).
Description
This function samples indices for permuting phenotype vectors in the basic permutation function (sip.R) and for permuting leftover unpaired individuals in the paired-permutation function (sipPair.R).
Usage
get_permIdx(df, seed = seed)
Arguments
df |
Data frame |
seed |
Number |
Value
Numeric vector
This function subsets the sample-by-variable data frame to the permutable data. This subset should include phenotypes and phenotypic covariates.
Description
This function subsets the sample-by-variable data frame to the permutable data. This subset should include phenotypes and phenotypic covariates.
Usage
get_permute(df, id.var = id.var, pheno.vars = pheno.vars)
Arguments
df |
Data frame |
id.var |
String |
pheno.vars |
Character vector |
Value
Data frame
This function infers relatedness categories in the paired-permutation function (sip_pair.R) prior to permutation.
Description
This function infers relatedness categories in the paired-permutation function (sip_pair.R) prior to permutation.
Usage
get_relCat(pairs, rid.vars = rid.vars, ibd.var = ibd.var)
Arguments
pairs |
Data frame |
rid.vars |
Character vector |
ibd.var |
String |
Value
List of data frames
This function pairs individuals in the paired-permutation function (sip_pair.R) into the most highly-related pairs possible.
Description
This function pairs individuals in the paired-permutation function (sip_pair.R) into the most highly-related pairs possible.
Usage
get_relPairs(
df,
id.var = id.var,
rel.df = rel.df,
rid.vars = rid.vars,
ibd.var = ibd.var
)
Arguments
df, rel.df |
Data frames |
id.var, ibd.var |
Strings |
rid.vars |
Character vector |
Value
Data frame
This function divides the sample-by-variable data frame into males and females prior to permutation within sexes.
Description
This function divides the sample-by-variable data frame into males and females prior to permutation within sexes.
Usage
get_sexDF(df = df, sex.var = sex.var, sex.val = sex.val)
Arguments
df |
Data frame |
sex.var |
String |
sex.val |
String or integer |
Value
Data frame
This function checks for uneven numbers of individuals within relatedness category and creates a data set for permuting single samples that will not be pair permuted (sip_pair.R).
Description
This function checks for uneven numbers of individuals within relatedness category and creates a data set for permuting single samples that will not be pair permuted (sip_pair.R).
Usage
get_singSamp(df, deglst, id.var = id.var)
Arguments
df |
Data frame |
deglst |
List of data frames |
id.var |
String |
Value
Data frame
This function reorders the permuted sample-by-variable data frame to match the ID order of the primary sample-by-variable data frame.
Description
This function reorders the permuted sample-by-variable data frame to match the ID order of the primary sample-by-variable data frame.
Usage
order_permDF(df = df, perm = perm, id.var = id.var)
Arguments
df, perm |
Data frames |
id.var |
String |
Value
Data frame
Phenotype-IBD correlation
Description
This function first calculates the correlation between phenotypes for sample pairs. Then it calculates the correlation between the phenotype correlation and identity-by-descent for the sample pairs. (N.B., Please omit missing values before running this function.)
Usage
phenotype_IBD_correlation(
df = NULL,
rel.df = NULL,
id.var = NULL,
rid.vars = NULL,
ibd.var = NULL,
pheno.vars = NULL
)
Arguments
df, rel.df |
Data frame |
id.var, ibd.var |
Strings |
pheno.vars, rid.vars |
Character vectors |
Details
The function requires the following inputs:
1) A sample-by-variable data frame with sample ID and phenotypes. Columns should include an individual ID variable and phenotype names.
2) A string identifying the ID variable name (e.g., id.var="ID").
3) A vector of phenotype names. (e.g., pheno.vars=c("PHENO1","PHENO2",...)).
4) A relatedness data frame containing identity-by-descent (IBD) for pairs of individuals in the sample-by-variable data frame Column names should include two ID variables and an IBD variable.
5) A vector of the 2 ID variable names in the relatedness data frame. (e.g., rid.vars=c("ID1","ID2")).
6) A string identifying the IBD variable name (e.g., ibd.var="PropIBD").
Value
Correlation
Examples
phenotype_IBD_correlation(df = sipPair_exampleData,
rel.df = sipPair_relatednessData, id.var = "IID",
rid.vars = c("IID1","IID2"), ibd.var = "PropIBD",
pheno.vars = paste0("PHENO",1:300))
phenotype_IBD_correlation(df = sipPair_exampleData[
sipPair_exampleData$IID %in% unlist(sipPair_relatednessData[1:100,c("IID1",
"IID2")]),], rel.df = sipPair_relatednessData[1:100,], id.var = "IID",
rid.vars = c("IID1","IID2"), ibd.var = "PropIBD",
pheno.vars = paste0("PHENO",1:300))
Phenotype correlation plot
Description
This function returns a plot showing correlation between phenotypes. (N.B., please omit missing values before running this function.)
Usage
plot_phenotype_correlations(df = NULL, pheno.vars = NULL)
Arguments
df |
Data frame |
pheno.vars |
Character vector |
Details
The function requires the following inputs:
1) A sample-by-variable data frame with phenotypes. Column names should include phenotype names.
2) A vector of phenotype names. (e.g., pheno.vars=c("PHENO1","PHENO2",...)).
Value
Plot
Examples
plot_phenotype_correlations(df = sip_exampleData,
pheno.vars = paste0("PHENO",1:500))
Single-iteration permutation for large-scale biobank data
Description
This function performs the basic permutation for permuting phenotype vectors in biobank data.
Usage
sip(
df = NULL,
id.var = NULL,
sex.var = NULL,
male.val = NULL,
female.val = NULL,
geno.vars = NULL,
within.sex = TRUE,
seed = NULL
)
Arguments
df |
Data frame |
id.var, sex.var |
Strings |
male.val, female.val |
Strings or integers |
geno.vars |
Character vectors |
within.sex |
Boolean, defaults to TRUE |
seed |
Number |
Details
The function requires the following inputs:
1) A sample-by-variable dataframe with phenotypes and covariates. Column names should include an ID variable, sex variable, genotypic covariate names, phenotypic covariate names, and phenotype names. (N.B. a secondary ID variable can be included in the genotypic covariate names.)
2) A string identifying the ID variable name (e.g., id.var="ID").
3) A vector of genotypic covariates (e.g., geno.vars=c("ID2","Batch","PC1","PC2",...)).
4) Optional: within.sex = FALSE. Default is within.sex = TRUE and will permute males and females separately.
5) If within.sex = TRUE (the default), a string identifying the sex variable name (e.g., sex.var="Inferred_Sex").
6) If within.sex = TRUE (the default), male and female values in the sex vector (e.g., male.val=1, female.val=2).
7) Optional: a seed for sampling. If a seed is not provided, one will be chosen randomly during the sampling process (e.g., seed=123).
8) N.B. Any column names not specified in (2)-(6) are assumed to be phenotypes or phenotypic covariates.
Value
Data frame
Examples
sip(df = sip_exampleData, id.var = "IID", sex.var = "SEX", male.val = 1,
female.val = 2, geno.vars = c("FID","ANCESTRY","BATCH",paste0("PC",1:4)))
Single-iteration paired permutation phenotype and covariate data
Description
A sample-by-variable data frame with IDs, covariates, and phenotypes as column names.
Usage
sipPair_exampleData
Format
A data frame with 10,000 rows and 309 variables:
- FID
Family ID.
- IID
Individual ID.
- BATCH
Genotyping batch.
- SEX
Sample biological sex.
- AGE
Sample age.
- PC1
Genetic principal component 1.
- PC2
Genetic principal component 2.
- PC3
Genetic principal component 3.
- PC4
Genetic principal component 4.
- PHENO1
Simulated phenotype 1.
- PHENO2
Simulated phenotype 2.
- PHENO3
Simulated phenotype 3.
- PHENO4
Simulated phenotype 4.
- PHENO5
Simulated phenotype 5.
- PHENO6
Simulated phenotype 6.
- PHENO7
Simulated phenotype 7.
- PHENO8
Simulated phenotype 8.
- PHENO9
Simulated phenotype 9.
- PHENO10
Simulated phenotype 10.
- PHENO11
Simulated phenotype 11.
- PHENO12
Simulated phenotype 12.
- PHENO13
Simulated phenotype 13.
- PHENO14
Simulated phenotype 14.
- PHENO15
Simulated phenotype 15.
- PHENO16
Simulated phenotype 16.
- PHENO17
Simulated phenotype 17.
- PHENO18
Simulated phenotype 18.
- PHENO19
Simulated phenotype 19.
- PHENO20
Simulated phenotype 20.
- PHENO21
Simulated phenotype 21.
- PHENO22
Simulated phenotype 22.
- PHENO23
Simulated phenotype 23.
- PHENO24
Simulated phenotype 24.
- PHENO25
Simulated phenotype 25.
- PHENO26
Simulated phenotype 26.
- PHENO27
Simulated phenotype 27.
- PHENO28
Simulated phenotype 28.
- PHENO29
Simulated phenotype 29.
- PHENO30
Simulated phenotype 30.
- PHENO31
Simulated phenotype 31.
- PHENO32
Simulated phenotype 32.
- PHENO33
Simulated phenotype 33.
- PHENO34
Simulated phenotype 34.
- PHENO35
Simulated phenotype 35.
- PHENO36
Simulated phenotype 36.
- PHENO37
Simulated phenotype 37.
- PHENO38
Simulated phenotype 38.
- PHENO39
Simulated phenotype 39.
- PHENO40
Simulated phenotype 40.
- PHENO41
Simulated phenotype 41.
- PHENO42
Simulated phenotype 42.
- PHENO43
Simulated phenotype 43.
- PHENO44
Simulated phenotype 44.
- PHENO45
Simulated phenotype 45.
- PHENO46
Simulated phenotype 46.
- PHENO47
Simulated phenotype 47.
- PHENO48
Simulated phenotype 48.
- PHENO49
Simulated phenotype 49.
- PHENO50
Simulated phenotype 50.
- PHENO51
Simulated phenotype 51.
- PHENO52
Simulated phenotype 52.
- PHENO53
Simulated phenotype 53.
- PHENO54
Simulated phenotype 54.
- PHENO55
Simulated phenotype 55.
- PHENO56
Simulated phenotype 56.
- PHENO57
Simulated phenotype 57.
- PHENO58
Simulated phenotype 58.
- PHENO59
Simulated phenotype 59.
- PHENO60
Simulated phenotype 60.
- PHENO61
Simulated phenotype 61.
- PHENO62
Simulated phenotype 62.
- PHENO63
Simulated phenotype 63.
- PHENO64
Simulated phenotype 64.
- PHENO65
Simulated phenotype 65.
- PHENO66
Simulated phenotype 66.
- PHENO67
Simulated phenotype 67.
- PHENO68
Simulated phenotype 68.
- PHENO69
Simulated phenotype 69.
- PHENO70
Simulated phenotype 70.
- PHENO71
Simulated phenotype 71.
- PHENO72
Simulated phenotype 72.
- PHENO73
Simulated phenotype 73.
- PHENO74
Simulated phenotype 74.
- PHENO75
Simulated phenotype 75.
- PHENO76
Simulated phenotype 76.
- PHENO77
Simulated phenotype 77.
- PHENO78
Simulated phenotype 78.
- PHENO79
Simulated phenotype 79.
- PHENO80
Simulated phenotype 80.
- PHENO81
Simulated phenotype 81.
- PHENO82
Simulated phenotype 82.
- PHENO83
Simulated phenotype 83.
- PHENO84
Simulated phenotype 84.
- PHENO85
Simulated phenotype 85.
- PHENO86
Simulated phenotype 86.
- PHENO87
Simulated phenotype 87.
- PHENO88
Simulated phenotype 88.
- PHENO89
Simulated phenotype 89.
- PHENO90
Simulated phenotype 90.
- PHENO91
Simulated phenotype 91.
- PHENO92
Simulated phenotype 92.
- PHENO93
Simulated phenotype 93.
- PHENO94
Simulated phenotype 94.
- PHENO95
Simulated phenotype 95.
- PHENO96
Simulated phenotype 96.
- PHENO97
Simulated phenotype 97.
- PHENO98
Simulated phenotype 98.
- PHENO99
Simulated phenotype 99.
- PHENO100
Simulated phenotype 100.
- PHENO101
Simulated phenotype 101.
- PHENO102
Simulated phenotype 102.
- PHENO103
Simulated phenotype 103.
- PHENO104
Simulated phenotype 104.
- PHENO105
Simulated phenotype 105.
- PHENO106
Simulated phenotype 106.
- PHENO107
Simulated phenotype 107.
- PHENO108
Simulated phenotype 108.
- PHENO109
Simulated phenotype 109.
- PHENO110
Simulated phenotype 110.
- PHENO111
Simulated phenotype 111.
- PHENO112
Simulated phenotype 112.
- PHENO113
Simulated phenotype 113.
- PHENO114
Simulated phenotype 114.
- PHENO115
Simulated phenotype 115.
- PHENO116
Simulated phenotype 116.
- PHENO117
Simulated phenotype 117.
- PHENO118
Simulated phenotype 118.
- PHENO119
Simulated phenotype 119.
- PHENO120
Simulated phenotype 120.
- PHENO121
Simulated phenotype 121.
- PHENO122
Simulated phenotype 122.
- PHENO123
Simulated phenotype 123.
- PHENO124
Simulated phenotype 124.
- PHENO125
Simulated phenotype 125.
- PHENO126
Simulated phenotype 126.
- PHENO127
Simulated phenotype 127.
- PHENO128
Simulated phenotype 128.
- PHENO129
Simulated phenotype 129.
- PHENO130
Simulated phenotype 130.
- PHENO131
Simulated phenotype 131.
- PHENO132
Simulated phenotype 132.
- PHENO133
Simulated phenotype 133.
- PHENO134
Simulated phenotype 134.
- PHENO135
Simulated phenotype 135.
- PHENO136
Simulated phenotype 136.
- PHENO137
Simulated phenotype 137.
- PHENO138
Simulated phenotype 138.
- PHENO139
Simulated phenotype 139.
- PHENO140
Simulated phenotype 140.
- PHENO141
Simulated phenotype 141.
- PHENO142
Simulated phenotype 142.
- PHENO143
Simulated phenotype 143.
- PHENO144
Simulated phenotype 144.
- PHENO145
Simulated phenotype 145.
- PHENO146
Simulated phenotype 146.
- PHENO147
Simulated phenotype 147.
- PHENO148
Simulated phenotype 148.
- PHENO149
Simulated phenotype 149.
- PHENO150
Simulated phenotype 150.
- PHENO151
Simulated phenotype 151.
- PHENO152
Simulated phenotype 152.
- PHENO153
Simulated phenotype 153.
- PHENO154
Simulated phenotype 154.
- PHENO155
Simulated phenotype 155.
- PHENO156
Simulated phenotype 156.
- PHENO157
Simulated phenotype 157.
- PHENO158
Simulated phenotype 158.
- PHENO159
Simulated phenotype 159.
- PHENO160
Simulated phenotype 160.
- PHENO161
Simulated phenotype 161.
- PHENO162
Simulated phenotype 162.
- PHENO163
Simulated phenotype 163.
- PHENO164
Simulated phenotype 164.
- PHENO165
Simulated phenotype 165.
- PHENO166
Simulated phenotype 166.
- PHENO167
Simulated phenotype 167.
- PHENO168
Simulated phenotype 168.
- PHENO169
Simulated phenotype 169.
- PHENO170
Simulated phenotype 170.
- PHENO171
Simulated phenotype 171.
- PHENO172
Simulated phenotype 172.
- PHENO173
Simulated phenotype 173.
- PHENO174
Simulated phenotype 174.
- PHENO175
Simulated phenotype 175.
- PHENO176
Simulated phenotype 176.
- PHENO177
Simulated phenotype 177.
- PHENO178
Simulated phenotype 178.
- PHENO179
Simulated phenotype 179.
- PHENO180
Simulated phenotype 180.
- PHENO181
Simulated phenotype 181.
- PHENO182
Simulated phenotype 182.
- PHENO183
Simulated phenotype 183.
- PHENO184
Simulated phenotype 184.
- PHENO185
Simulated phenotype 185.
- PHENO186
Simulated phenotype 186.
- PHENO187
Simulated phenotype 187.
- PHENO188
Simulated phenotype 188.
- PHENO189
Simulated phenotype 189.
- PHENO190
Simulated phenotype 190.
- PHENO191
Simulated phenotype 191.
- PHENO192
Simulated phenotype 192.
- PHENO193
Simulated phenotype 193.
- PHENO194
Simulated phenotype 194.
- PHENO195
Simulated phenotype 195.
- PHENO196
Simulated phenotype 196.
- PHENO197
Simulated phenotype 197.
- PHENO198
Simulated phenotype 198.
- PHENO199
Simulated phenotype 199.
- PHENO200
Simulated phenotype 200.
- PHENO201
Simulated phenotype 201.
- PHENO202
Simulated phenotype 202.
- PHENO203
Simulated phenotype 203.
- PHENO204
Simulated phenotype 204.
- PHENO205
Simulated phenotype 205.
- PHENO206
Simulated phenotype 206.
- PHENO207
Simulated phenotype 207.
- PHENO208
Simulated phenotype 208.
- PHENO209
Simulated phenotype 209.
- PHENO210
Simulated phenotype 210.
- PHENO211
Simulated phenotype 211.
- PHENO212
Simulated phenotype 212.
- PHENO213
Simulated phenotype 213.
- PHENO214
Simulated phenotype 214.
- PHENO215
Simulated phenotype 215.
- PHENO216
Simulated phenotype 216.
- PHENO217
Simulated phenotype 217.
- PHENO218
Simulated phenotype 218.
- PHENO219
Simulated phenotype 219.
- PHENO220
Simulated phenotype 220.
- PHENO221
Simulated phenotype 221.
- PHENO222
Simulated phenotype 222.
- PHENO223
Simulated phenotype 223.
- PHENO224
Simulated phenotype 224.
- PHENO225
Simulated phenotype 225.
- PHENO226
Simulated phenotype 226.
- PHENO227
Simulated phenotype 227.
- PHENO228
Simulated phenotype 228.
- PHENO229
Simulated phenotype 229.
- PHENO230
Simulated phenotype 230.
- PHENO231
Simulated phenotype 231.
- PHENO232
Simulated phenotype 232.
- PHENO233
Simulated phenotype 233.
- PHENO234
Simulated phenotype 234.
- PHENO235
Simulated phenotype 235.
- PHENO236
Simulated phenotype 236.
- PHENO237
Simulated phenotype 237.
- PHENO238
Simulated phenotype 238.
- PHENO239
Simulated phenotype 239.
- PHENO240
Simulated phenotype 240.
- PHENO241
Simulated phenotype 241.
- PHENO242
Simulated phenotype 242.
- PHENO243
Simulated phenotype 243.
- PHENO244
Simulated phenotype 244.
- PHENO245
Simulated phenotype 245.
- PHENO246
Simulated phenotype 246.
- PHENO247
Simulated phenotype 247.
- PHENO248
Simulated phenotype 248.
- PHENO249
Simulated phenotype 249.
- PHENO250
Simulated phenotype 250.
- PHENO251
Simulated phenotype 251.
- PHENO252
Simulated phenotype 252.
- PHENO253
Simulated phenotype 253.
- PHENO254
Simulated phenotype 254.
- PHENO255
Simulated phenotype 255.
- PHENO256
Simulated phenotype 256.
- PHENO257
Simulated phenotype 257.
- PHENO258
Simulated phenotype 258.
- PHENO259
Simulated phenotype 259.
- PHENO260
Simulated phenotype 260.
- PHENO261
Simulated phenotype 261.
- PHENO262
Simulated phenotype 262.
- PHENO263
Simulated phenotype 263.
- PHENO264
Simulated phenotype 264.
- PHENO265
Simulated phenotype 265.
- PHENO266
Simulated phenotype 266.
- PHENO267
Simulated phenotype 267.
- PHENO268
Simulated phenotype 268.
- PHENO269
Simulated phenotype 269.
- PHENO270
Simulated phenotype 270.
- PHENO271
Simulated phenotype 271.
- PHENO272
Simulated phenotype 272.
- PHENO273
Simulated phenotype 273.
- PHENO274
Simulated phenotype 274.
- PHENO275
Simulated phenotype 275.
- PHENO276
Simulated phenotype 276.
- PHENO277
Simulated phenotype 277.
- PHENO278
Simulated phenotype 278.
- PHENO279
Simulated phenotype 279.
- PHENO280
Simulated phenotype 280.
- PHENO281
Simulated phenotype 281.
- PHENO282
Simulated phenotype 282.
- PHENO283
Simulated phenotype 283.
- PHENO284
Simulated phenotype 284.
- PHENO285
Simulated phenotype 285.
- PHENO286
Simulated phenotype 286.
- PHENO287
Simulated phenotype 287.
- PHENO288
Simulated phenotype 288.
- PHENO289
Simulated phenotype 289.
- PHENO290
Simulated phenotype 290.
- PHENO291
Simulated phenotype 291.
- PHENO292
Simulated phenotype 292.
- PHENO293
Simulated phenotype 293.
- PHENO294
Simulated phenotype 294.
- PHENO295
Simulated phenotype 295.
- PHENO296
Simulated phenotype 296.
- PHENO297
Simulated phenotype 297.
- PHENO298
Simulated phenotype 298.
- PHENO299
Simulated phenotype 299.
- PHENO300
Simulated phenotype 300.
Source
<https://doi.org/10.21203/rs.3.rs-873449/v1>
Single-iteration paired permutation relatedness data
Description
A sample-by-variable data frame with IDs and identity-by-descent data between samples.
Usage
sipPair_relatednessData
Format
A data frame with 9886 rows and 4 variables:
- IID1
Individual ID for one sample.
- IID2
Iindividual ID for a second sample.
- PropIBD
Identity-by-descent proportion of genome shared between the two samples.
Source
<https://doi.org/10.21203/rs.3.rs-873449/v1>
Single-iteration permutation phenotype and covariate data
Description
A sample-by-variable data frame with IDs, covariates, and phenotypes as column names.
Usage
sip_exampleData
Format
A data frame with 10,000 rows and 511 variables:
- FID
Family ID.
- IID
Individual ID.
- ANCESTRY
Sample ancestry.
- SEX
Sample biological sex.
- AGE
Sample age.
- BATCH
Genotyping batch.
- STUDY
Study contributing sample data.
- PC1
Genetic principal component 1.
- PC2
Genetic principal component 2.
- PC3
Genetic principal component 3.
- PC4
Genetic principal component 4.
- PHENO1
Simulated phenotype 1.
- PHENO2
Simulated phenotype 2.
- PHENO3
Simulated phenotype 3.
- PHENO4
Simulated phenotype 4.
- PHENO5
Simulated phenotype 5.
- PHENO6
Simulated phenotype 6.
- PHENO7
Simulated phenotype 7.
- PHENO8
Simulated phenotype 8.
- PHENO9
Simulated phenotype 9.
- PHENO10
Simulated phenotype 10.
- PHENO11
Simulated phenotype 11.
- PHENO12
Simulated phenotype 12.
- PHENO13
Simulated phenotype 13.
- PHENO14
Simulated phenotype 14.
- PHENO15
Simulated phenotype 15.
- PHENO16
Simulated phenotype 16.
- PHENO17
Simulated phenotype 17.
- PHENO18
Simulated phenotype 18.
- PHENO19
Simulated phenotype 19.
- PHENO20
Simulated phenotype 20.
- PHENO21
Simulated phenotype 21.
- PHENO22
Simulated phenotype 22.
- PHENO23
Simulated phenotype 23.
- PHENO24
Simulated phenotype 24.
- PHENO25
Simulated phenotype 25.
- PHENO26
Simulated phenotype 26.
- PHENO27
Simulated phenotype 27.
- PHENO28
Simulated phenotype 28.
- PHENO29
Simulated phenotype 29.
- PHENO30
Simulated phenotype 30.
- PHENO31
Simulated phenotype 31.
- PHENO32
Simulated phenotype 32.
- PHENO33
Simulated phenotype 33.
- PHENO34
Simulated phenotype 34.
- PHENO35
Simulated phenotype 35.
- PHENO36
Simulated phenotype 36.
- PHENO37
Simulated phenotype 37.
- PHENO38
Simulated phenotype 38.
- PHENO39
Simulated phenotype 39.
- PHENO40
Simulated phenotype 40.
- PHENO41
Simulated phenotype 41.
- PHENO42
Simulated phenotype 42.
- PHENO43
Simulated phenotype 43.
- PHENO44
Simulated phenotype 44.
- PHENO45
Simulated phenotype 45.
- PHENO46
Simulated phenotype 46.
- PHENO47
Simulated phenotype 47.
- PHENO48
Simulated phenotype 48.
- PHENO49
Simulated phenotype 49.
- PHENO50
Simulated phenotype 50.
- PHENO51
Simulated phenotype 51.
- PHENO52
Simulated phenotype 52.
- PHENO53
Simulated phenotype 53.
- PHENO54
Simulated phenotype 54.
- PHENO55
Simulated phenotype 55.
- PHENO56
Simulated phenotype 56.
- PHENO57
Simulated phenotype 57.
- PHENO58
Simulated phenotype 58.
- PHENO59
Simulated phenotype 59.
- PHENO60
Simulated phenotype 60.
- PHENO61
Simulated phenotype 61.
- PHENO62
Simulated phenotype 62.
- PHENO63
Simulated phenotype 63.
- PHENO64
Simulated phenotype 64.
- PHENO65
Simulated phenotype 65.
- PHENO66
Simulated phenotype 66.
- PHENO67
Simulated phenotype 67.
- PHENO68
Simulated phenotype 68.
- PHENO69
Simulated phenotype 69.
- PHENO70
Simulated phenotype 70.
- PHENO71
Simulated phenotype 71.
- PHENO72
Simulated phenotype 72.
- PHENO73
Simulated phenotype 73.
- PHENO74
Simulated phenotype 74.
- PHENO75
Simulated phenotype 75.
- PHENO76
Simulated phenotype 76.
- PHENO77
Simulated phenotype 77.
- PHENO78
Simulated phenotype 78.
- PHENO79
Simulated phenotype 79.
- PHENO80
Simulated phenotype 80.
- PHENO81
Simulated phenotype 81.
- PHENO82
Simulated phenotype 82.
- PHENO83
Simulated phenotype 83.
- PHENO84
Simulated phenotype 84.
- PHENO85
Simulated phenotype 85.
- PHENO86
Simulated phenotype 86.
- PHENO87
Simulated phenotype 87.
- PHENO88
Simulated phenotype 88.
- PHENO89
Simulated phenotype 89.
- PHENO90
Simulated phenotype 90.
- PHENO91
Simulated phenotype 91.
- PHENO92
Simulated phenotype 92.
- PHENO93
Simulated phenotype 93.
- PHENO94
Simulated phenotype 94.
- PHENO95
Simulated phenotype 95.
- PHENO96
Simulated phenotype 96.
- PHENO97
Simulated phenotype 97.
- PHENO98
Simulated phenotype 98.
- PHENO99
Simulated phenotype 99.
- PHENO100
Simulated phenotype 100.
- PHENO101
Simulated phenotype 101.
- PHENO102
Simulated phenotype 102.
- PHENO103
Simulated phenotype 103.
- PHENO104
Simulated phenotype 104.
- PHENO105
Simulated phenotype 105.
- PHENO106
Simulated phenotype 106.
- PHENO107
Simulated phenotype 107.
- PHENO108
Simulated phenotype 108.
- PHENO109
Simulated phenotype 109.
- PHENO110
Simulated phenotype 110.
- PHENO111
Simulated phenotype 111.
- PHENO112
Simulated phenotype 112.
- PHENO113
Simulated phenotype 113.
- PHENO114
Simulated phenotype 114.
- PHENO115
Simulated phenotype 115.
- PHENO116
Simulated phenotype 116.
- PHENO117
Simulated phenotype 117.
- PHENO118
Simulated phenotype 118.
- PHENO119
Simulated phenotype 119.
- PHENO120
Simulated phenotype 120.
- PHENO121
Simulated phenotype 121.
- PHENO122
Simulated phenotype 122.
- PHENO123
Simulated phenotype 123.
- PHENO124
Simulated phenotype 124.
- PHENO125
Simulated phenotype 125.
- PHENO126
Simulated phenotype 126.
- PHENO127
Simulated phenotype 127.
- PHENO128
Simulated phenotype 128.
- PHENO129
Simulated phenotype 129.
- PHENO130
Simulated phenotype 130.
- PHENO131
Simulated phenotype 131.
- PHENO132
Simulated phenotype 132.
- PHENO133
Simulated phenotype 133.
- PHENO134
Simulated phenotype 134.
- PHENO135
Simulated phenotype 135.
- PHENO136
Simulated phenotype 136.
- PHENO137
Simulated phenotype 137.
- PHENO138
Simulated phenotype 138.
- PHENO139
Simulated phenotype 139.
- PHENO140
Simulated phenotype 140.
- PHENO141
Simulated phenotype 141.
- PHENO142
Simulated phenotype 142.
- PHENO143
Simulated phenotype 143.
- PHENO144
Simulated phenotype 144.
- PHENO145
Simulated phenotype 145.
- PHENO146
Simulated phenotype 146.
- PHENO147
Simulated phenotype 147.
- PHENO148
Simulated phenotype 148.
- PHENO149
Simulated phenotype 149.
- PHENO150
Simulated phenotype 150.
- PHENO151
Simulated phenotype 151.
- PHENO152
Simulated phenotype 152.
- PHENO153
Simulated phenotype 153.
- PHENO154
Simulated phenotype 154.
- PHENO155
Simulated phenotype 155.
- PHENO156
Simulated phenotype 156.
- PHENO157
Simulated phenotype 157.
- PHENO158
Simulated phenotype 158.
- PHENO159
Simulated phenotype 159.
- PHENO160
Simulated phenotype 160.
- PHENO161
Simulated phenotype 161.
- PHENO162
Simulated phenotype 162.
- PHENO163
Simulated phenotype 163.
- PHENO164
Simulated phenotype 164.
- PHENO165
Simulated phenotype 165.
- PHENO166
Simulated phenotype 166.
- PHENO167
Simulated phenotype 167.
- PHENO168
Simulated phenotype 168.
- PHENO169
Simulated phenotype 169.
- PHENO170
Simulated phenotype 170.
- PHENO171
Simulated phenotype 171.
- PHENO172
Simulated phenotype 172.
- PHENO173
Simulated phenotype 173.
- PHENO174
Simulated phenotype 174.
- PHENO175
Simulated phenotype 175.
- PHENO176
Simulated phenotype 176.
- PHENO177
Simulated phenotype 177.
- PHENO178
Simulated phenotype 178.
- PHENO179
Simulated phenotype 179.
- PHENO180
Simulated phenotype 180.
- PHENO181
Simulated phenotype 181.
- PHENO182
Simulated phenotype 182.
- PHENO183
Simulated phenotype 183.
- PHENO184
Simulated phenotype 184.
- PHENO185
Simulated phenotype 185.
- PHENO186
Simulated phenotype 186.
- PHENO187
Simulated phenotype 187.
- PHENO188
Simulated phenotype 188.
- PHENO189
Simulated phenotype 189.
- PHENO190
Simulated phenotype 190.
- PHENO191
Simulated phenotype 191.
- PHENO192
Simulated phenotype 192.
- PHENO193
Simulated phenotype 193.
- PHENO194
Simulated phenotype 194.
- PHENO195
Simulated phenotype 195.
- PHENO196
Simulated phenotype 196.
- PHENO197
Simulated phenotype 197.
- PHENO198
Simulated phenotype 198.
- PHENO199
Simulated phenotype 199.
- PHENO200
Simulated phenotype 200.
- PHENO201
Simulated phenotype 201.
- PHENO202
Simulated phenotype 202.
- PHENO203
Simulated phenotype 203.
- PHENO204
Simulated phenotype 204.
- PHENO205
Simulated phenotype 205.
- PHENO206
Simulated phenotype 206.
- PHENO207
Simulated phenotype 207.
- PHENO208
Simulated phenotype 208.
- PHENO209
Simulated phenotype 209.
- PHENO210
Simulated phenotype 210.
- PHENO211
Simulated phenotype 211.
- PHENO212
Simulated phenotype 212.
- PHENO213
Simulated phenotype 213.
- PHENO214
Simulated phenotype 214.
- PHENO215
Simulated phenotype 215.
- PHENO216
Simulated phenotype 216.
- PHENO217
Simulated phenotype 217.
- PHENO218
Simulated phenotype 218.
- PHENO219
Simulated phenotype 219.
- PHENO220
Simulated phenotype 220.
- PHENO221
Simulated phenotype 221.
- PHENO222
Simulated phenotype 222.
- PHENO223
Simulated phenotype 223.
- PHENO224
Simulated phenotype 224.
- PHENO225
Simulated phenotype 225.
- PHENO226
Simulated phenotype 226.
- PHENO227
Simulated phenotype 227.
- PHENO228
Simulated phenotype 228.
- PHENO229
Simulated phenotype 229.
- PHENO230
Simulated phenotype 230.
- PHENO231
Simulated phenotype 231.
- PHENO232
Simulated phenotype 232.
- PHENO233
Simulated phenotype 233.
- PHENO234
Simulated phenotype 234.
- PHENO235
Simulated phenotype 235.
- PHENO236
Simulated phenotype 236.
- PHENO237
Simulated phenotype 237.
- PHENO238
Simulated phenotype 238.
- PHENO239
Simulated phenotype 239.
- PHENO240
Simulated phenotype 240.
- PHENO241
Simulated phenotype 241.
- PHENO242
Simulated phenotype 242.
- PHENO243
Simulated phenotype 243.
- PHENO244
Simulated phenotype 244.
- PHENO245
Simulated phenotype 245.
- PHENO246
Simulated phenotype 246.
- PHENO247
Simulated phenotype 247.
- PHENO248
Simulated phenotype 248.
- PHENO249
Simulated phenotype 249.
- PHENO250
Simulated phenotype 250.
- PHENO251
Simulated phenotype 251.
- PHENO252
Simulated phenotype 252.
- PHENO253
Simulated phenotype 253.
- PHENO254
Simulated phenotype 254.
- PHENO255
Simulated phenotype 255.
- PHENO256
Simulated phenotype 256.
- PHENO257
Simulated phenotype 257.
- PHENO258
Simulated phenotype 258.
- PHENO259
Simulated phenotype 259.
- PHENO260
Simulated phenotype 260.
- PHENO261
Simulated phenotype 261.
- PHENO262
Simulated phenotype 262.
- PHENO263
Simulated phenotype 263.
- PHENO264
Simulated phenotype 264.
- PHENO265
Simulated phenotype 265.
- PHENO266
Simulated phenotype 266.
- PHENO267
Simulated phenotype 267.
- PHENO268
Simulated phenotype 268.
- PHENO269
Simulated phenotype 269.
- PHENO270
Simulated phenotype 270.
- PHENO271
Simulated phenotype 271.
- PHENO272
Simulated phenotype 272.
- PHENO273
Simulated phenotype 273.
- PHENO274
Simulated phenotype 274.
- PHENO275
Simulated phenotype 275.
- PHENO276
Simulated phenotype 276.
- PHENO277
Simulated phenotype 277.
- PHENO278
Simulated phenotype 278.
- PHENO279
Simulated phenotype 279.
- PHENO280
Simulated phenotype 280.
- PHENO281
Simulated phenotype 281.
- PHENO282
Simulated phenotype 282.
- PHENO283
Simulated phenotype 283.
- PHENO284
Simulated phenotype 284.
- PHENO285
Simulated phenotype 285.
- PHENO286
Simulated phenotype 286.
- PHENO287
Simulated phenotype 287.
- PHENO288
Simulated phenotype 288.
- PHENO289
Simulated phenotype 289.
- PHENO290
Simulated phenotype 290.
- PHENO291
Simulated phenotype 291.
- PHENO292
Simulated phenotype 292.
- PHENO293
Simulated phenotype 293.
- PHENO294
Simulated phenotype 294.
- PHENO295
Simulated phenotype 295.
- PHENO296
Simulated phenotype 296.
- PHENO297
Simulated phenotype 297.
- PHENO298
Simulated phenotype 298.
- PHENO299
Simulated phenotype 299.
- PHENO300
Simulated phenotype 300.
- PHENO301
Simulated phenotype 301.
- PHENO302
Simulated phenotype 302.
- PHENO303
Simulated phenotype 303.
- PHENO304
Simulated phenotype 304.
- PHENO305
Simulated phenotype 305.
- PHENO306
Simulated phenotype 306.
- PHENO307
Simulated phenotype 307.
- PHENO308
Simulated phenotype 308.
- PHENO309
Simulated phenotype 309.
- PHENO310
Simulated phenotype 310.
- PHENO311
Simulated phenotype 311.
- PHENO312
Simulated phenotype 312.
- PHENO313
Simulated phenotype 313.
- PHENO314
Simulated phenotype 314.
- PHENO315
Simulated phenotype 315.
- PHENO316
Simulated phenotype 316.
- PHENO317
Simulated phenotype 317.
- PHENO318
Simulated phenotype 318.
- PHENO319
Simulated phenotype 319.
- PHENO320
Simulated phenotype 320.
- PHENO321
Simulated phenotype 321.
- PHENO322
Simulated phenotype 322.
- PHENO323
Simulated phenotype 323.
- PHENO324
Simulated phenotype 324.
- PHENO325
Simulated phenotype 325.
- PHENO326
Simulated phenotype 326.
- PHENO327
Simulated phenotype 327.
- PHENO328
Simulated phenotype 328.
- PHENO329
Simulated phenotype 329.
- PHENO330
Simulated phenotype 330.
- PHENO331
Simulated phenotype 331.
- PHENO332
Simulated phenotype 332.
- PHENO333
Simulated phenotype 333.
- PHENO334
Simulated phenotype 334.
- PHENO335
Simulated phenotype 335.
- PHENO336
Simulated phenotype 336.
- PHENO337
Simulated phenotype 337.
- PHENO338
Simulated phenotype 338.
- PHENO339
Simulated phenotype 339.
- PHENO340
Simulated phenotype 340.
- PHENO341
Simulated phenotype 341.
- PHENO342
Simulated phenotype 342.
- PHENO343
Simulated phenotype 343.
- PHENO344
Simulated phenotype 344.
- PHENO345
Simulated phenotype 345.
- PHENO346
Simulated phenotype 346.
- PHENO347
Simulated phenotype 347.
- PHENO348
Simulated phenotype 348.
- PHENO349
Simulated phenotype 349.
- PHENO350
Simulated phenotype 350.
- PHENO351
Simulated phenotype 351.
- PHENO352
Simulated phenotype 352.
- PHENO353
Simulated phenotype 353.
- PHENO354
Simulated phenotype 354.
- PHENO355
Simulated phenotype 355.
- PHENO356
Simulated phenotype 356.
- PHENO357
Simulated phenotype 357.
- PHENO358
Simulated phenotype 358.
- PHENO359
Simulated phenotype 359.
- PHENO360
Simulated phenotype 360.
- PHENO361
Simulated phenotype 361.
- PHENO362
Simulated phenotype 362.
- PHENO363
Simulated phenotype 363.
- PHENO364
Simulated phenotype 364.
- PHENO365
Simulated phenotype 365.
- PHENO366
Simulated phenotype 366.
- PHENO367
Simulated phenotype 367.
- PHENO368
Simulated phenotype 368.
- PHENO369
Simulated phenotype 369.
- PHENO370
Simulated phenotype 370.
- PHENO371
Simulated phenotype 371.
- PHENO372
Simulated phenotype 372.
- PHENO373
Simulated phenotype 373.
- PHENO374
Simulated phenotype 374.
- PHENO375
Simulated phenotype 375.
- PHENO376
Simulated phenotype 376.
- PHENO377
Simulated phenotype 377.
- PHENO378
Simulated phenotype 378.
- PHENO379
Simulated phenotype 379.
- PHENO380
Simulated phenotype 380.
- PHENO381
Simulated phenotype 381.
- PHENO382
Simulated phenotype 382.
- PHENO383
Simulated phenotype 383.
- PHENO384
Simulated phenotype 384.
- PHENO385
Simulated phenotype 385.
- PHENO386
Simulated phenotype 386.
- PHENO387
Simulated phenotype 387.
- PHENO388
Simulated phenotype 388.
- PHENO389
Simulated phenotype 389.
- PHENO390
Simulated phenotype 390.
- PHENO391
Simulated phenotype 391.
- PHENO392
Simulated phenotype 392.
- PHENO393
Simulated phenotype 393.
- PHENO394
Simulated phenotype 394.
- PHENO395
Simulated phenotype 395.
- PHENO396
Simulated phenotype 396.
- PHENO397
Simulated phenotype 397.
- PHENO398
Simulated phenotype 398.
- PHENO399
Simulated phenotype 399.
- PHENO400
Simulated phenotype 400.
- PHENO401
Simulated phenotype 401.
- PHENO402
Simulated phenotype 402.
- PHENO403
Simulated phenotype 403.
- PHENO404
Simulated phenotype 404.
- PHENO405
Simulated phenotype 405.
- PHENO406
Simulated phenotype 406.
- PHENO407
Simulated phenotype 407.
- PHENO408
Simulated phenotype 408.
- PHENO409
Simulated phenotype 409.
- PHENO410
Simulated phenotype 410.
- PHENO411
Simulated phenotype 411.
- PHENO412
Simulated phenotype 412.
- PHENO413
Simulated phenotype 413.
- PHENO414
Simulated phenotype 414.
- PHENO415
Simulated phenotype 415.
- PHENO416
Simulated phenotype 416.
- PHENO417
Simulated phenotype 417.
- PHENO418
Simulated phenotype 418.
- PHENO419
Simulated phenotype 419.
- PHENO420
Simulated phenotype 420.
- PHENO421
Simulated phenotype 421.
- PHENO422
Simulated phenotype 422.
- PHENO423
Simulated phenotype 423.
- PHENO424
Simulated phenotype 424.
- PHENO425
Simulated phenotype 425.
- PHENO426
Simulated phenotype 426.
- PHENO427
Simulated phenotype 427.
- PHENO428
Simulated phenotype 428.
- PHENO429
Simulated phenotype 429.
- PHENO430
Simulated phenotype 430.
- PHENO431
Simulated phenotype 431.
- PHENO432
Simulated phenotype 432.
- PHENO433
Simulated phenotype 433.
- PHENO434
Simulated phenotype 434.
- PHENO435
Simulated phenotype 435.
- PHENO436
Simulated phenotype 436.
- PHENO437
Simulated phenotype 437.
- PHENO438
Simulated phenotype 438.
- PHENO439
Simulated phenotype 439.
- PHENO440
Simulated phenotype 440.
- PHENO441
Simulated phenotype 441.
- PHENO442
Simulated phenotype 442.
- PHENO443
Simulated phenotype 443.
- PHENO444
Simulated phenotype 444.
- PHENO445
Simulated phenotype 445.
- PHENO446
Simulated phenotype 446.
- PHENO447
Simulated phenotype 447.
- PHENO448
Simulated phenotype 448.
- PHENO449
Simulated phenotype 449.
- PHENO450
Simulated phenotype 450.
- PHENO451
Simulated phenotype 451.
- PHENO452
Simulated phenotype 452.
- PHENO453
Simulated phenotype 453.
- PHENO454
Simulated phenotype 454.
- PHENO455
Simulated phenotype 455.
- PHENO456
Simulated phenotype 456.
- PHENO457
Simulated phenotype 457.
- PHENO458
Simulated phenotype 458.
- PHENO459
Simulated phenotype 459.
- PHENO460
Simulated phenotype 460.
- PHENO461
Simulated phenotype 461.
- PHENO462
Simulated phenotype 462.
- PHENO463
Simulated phenotype 463.
- PHENO464
Simulated phenotype 464.
- PHENO465
Simulated phenotype 465.
- PHENO466
Simulated phenotype 466.
- PHENO467
Simulated phenotype 467.
- PHENO468
Simulated phenotype 468.
- PHENO469
Simulated phenotype 469.
- PHENO470
Simulated phenotype 470.
- PHENO471
Simulated phenotype 471.
- PHENO472
Simulated phenotype 472.
- PHENO473
Simulated phenotype 473.
- PHENO474
Simulated phenotype 474.
- PHENO475
Simulated phenotype 475.
- PHENO476
Simulated phenotype 476.
- PHENO477
Simulated phenotype 477.
- PHENO478
Simulated phenotype 478.
- PHENO479
Simulated phenotype 479.
- PHENO480
Simulated phenotype 480.
- PHENO481
Simulated phenotype 481.
- PHENO482
Simulated phenotype 482.
- PHENO483
Simulated phenotype 483.
- PHENO484
Simulated phenotype 484.
- PHENO485
Simulated phenotype 485.
- PHENO486
Simulated phenotype 486.
- PHENO487
Simulated phenotype 487.
- PHENO488
Simulated phenotype 488.
- PHENO489
Simulated phenotype 489.
- PHENO490
Simulated phenotype 490.
- PHENO491
Simulated phenotype 491.
- PHENO492
Simulated phenotype 492.
- PHENO493
Simulated phenotype 493.
- PHENO494
Simulated phenotype 494.
- PHENO495
Simulated phenotype 495.
- PHENO496
Simulated phenotype 496.
- PHENO497
Simulated phenotype 497.
- PHENO498
Simulated phenotype 498.
- PHENO499
Simulated phenotype 499.
- PHENO500
Simulated phenotype 500.
Source
<https://doi.org/10.21203/rs.3.rs-873449/v1>
Single-iteration paired permutation for large-scale biobank data with relatedness
Description
# This function performs paired permutation for permuting phenotype vectors among related individuals in biobank data.
Usage
sip_pair(
df = NULL,
id.var = NULL,
sex.var = NULL,
male.val = NULL,
female.val = NULL,
geno.vars = NULL,
within.sex = TRUE,
seed = NULL,
rel.df = NULL,
rid.vars = NULL,
ibd.var = NULL
)
Arguments
df, rel.df |
Data frame |
id.var, sex.var, ibd.var |
Strings |
male.val, female.val |
Strings or integers |
geno.vars, rid.vars |
Character vectors |
within.sex |
Boolean, defaults to TRUE |
seed |
Number |
Details
The function requires the following inputs:
1) A sample-by-variable data frame with phenotypes and covariates. Column names should include an ID variable, sex variable, genotypic covariate names, phenotypic covariate names, and phenotype names. (N.B. a secondary ID variable can be included in the genotypic covariate names.)
2) A string identifying the ID variable name (e.g., id.var="ID").
3) A vector of genotypic covariates (e.g., geno.vars=c("ID2","Batch","PC1","PC2",...)).
4) A relatedness data frame containing identity-by-descent (IBD) for pairs of individuals in the sample-by-variable data frame. Column names should include two ID variables and an IBD variable.
5) A vector of the 2 ID variable names in the relatedness data frame. (e.g., rid.vars=c("ID1","ID2")).
6) A string identifying the IBD variable name (e.g., ibd.var="PropIBD").
7) Optional: within.sex = FALSE. Default is within.sex = TRUE and will permute males and females separately.
8) If within.sex = TRUE (the default), a string identifying the sex variable name (e.g., sex.var="Inferred_Sex").
9) If within.sex = TRUE (the default), male and female values in the sex vector (e.g., male.val=1, female.val=2).
10) Optional: a seed for sampling. If a seed is not provided, one will be chosen randomly during the sampling process (e.g., seed=123).
11) N.B. Any column names not specified in (2)-(9) are assumed to be phenotypes or phenotypic covariates.
Value
Data frame
Examples
sip_pair(df = sipPair_exampleData, id.var = "IID",
sex.var = "SEX", male.val = "M", female.val = "F",
geno.vars = c("FID","BATCH",paste0("PC",1:4)),
rel.df = sipPair_relatednessData, rid.vars=c("IID1","IID2"),
ibd.var="PropIBD")