perIndividualQC checks the samples in the plink dataset for their total missingness and heterozygosity rates, the concordance of their assigned sex to their SNP sex, their relatedness to other study individuals and their genetic ancestry.
perIndividualQC(
indir,
name,
qcdir = indir,
dont.check_sex = FALSE,
do.run_check_sex = TRUE,
do.evaluate_check_sex = TRUE,
maleTh = 0.8,
femaleTh = 0.2,
externalSex = NULL,
externalMale = "M",
externalSexSex = "Sex",
externalSexID = "IID",
externalFemale = "F",
fixMixup = FALSE,
dont.check_het_and_miss = FALSE,
do.run_check_het_and_miss = TRUE,
do.evaluate_check_het_and_miss = TRUE,
imissTh = 0.03,
hetTh = 3,
dont.check_relatedness = FALSE,
do.run_check_relatedness = TRUE,
do.evaluate_check_relatedness = TRUE,
highIBDTh = 0.1875,
mafThRelatedness = 0.1,
filter_high_ldregion = TRUE,
high_ldregion_file = NULL,
genomebuild = "hg19",
dont.check_ancestry = FALSE,
do.run_check_ancestry = TRUE,
do.evaluate_check_ancestry = TRUE,
prefixMergedDataset,
europeanTh = 1.5,
defaultRefSamples = c("HapMap", "1000Genomes"),
refSamples = NULL,
refColors = NULL,
refSamplesFile = NULL,
refColorsFile = NULL,
refSamplesIID = "IID",
refSamplesPop = "Pop",
refColorsColor = "Color",
refColorsPop = "Pop",
studyColor = "#2c7bb6",
label_fail = TRUE,
highlight_samples = NULL,
highlight_type = c("text", "label", "color", "shape"),
highlight_text_size = 3,
highlight_color = "#c51b8a",
highlight_shape = 17,
highlight_legend = FALSE,
interactive = FALSE,
verbose = TRUE,
keep_individuals = NULL,
remove_individuals = NULL,
exclude_markers = NULL,
extract_markers = NULL,
legend_text_size = 5,
legend_title_size = 7,
axis_text_size = 5,
axis_title_size = 7,
subplot_label_size = 9,
title_size = 9,
path2plink = NULL,
showPlinkOutput = TRUE
)[character] /path/to/directory containing the basic PLINK data files name.bim, name.bed, name.fam files.
[character] Prefix of PLINK files, i.e. name.bed, name.bim, name.fam.
[character] /path/to/directory where results will be saved.
Per default, qcdir=indir. If do.evaluate_[analysis] is set to TRUE and
do.run_[analysis] is FALSE, perIndividualQC expects the
analysis-specific plink output files in qcdir i.e. do.check_sex expects
name.sexcheck, do.evaluate_check_het_and_miss expects name.het and name.imiss,
do.evaluate_check_relatedness expects name.genome and name.imiss and
do.evaluate_check_ancestry expects prefixMergeData.eigenvec. If these files
are not present perIndividualQC will fail with missing file error.
Setting do.run_[analysis] TRUE will execute the checks and create the
required files. User needs writing permission to qcdir.
[logical] If TRUE, no sex check will be conducted; short for do.run_check_sex=FALSE and do.evaluate_check_sex=FALSE. Takes precedence over do.run_check_sex and do.evaluate_check_sex.
[logical] If TRUE, run run_check_sex
[logical] If TRUE, run
evaluate_check_sex
[double] Threshold of X-chromosomal heterozygosity rate for males.
[double] Threshold of X-chromosomal heterozygosity rate for females.
[data.frame, optional] Dataframe with sample IDs [externalSexID] and sex [externalSexSex] to double check if external and PEDSEX data (often processed at different centers) match.
[integer/character] Identifier for 'male' in externalSex.
[character] Column identifier for column containing sex information in externalSex.
[character] Column identifier for column containing ID information in externalSex.
[integer/character] Identifier for 'female' in externalSex.
[logical] Should PEDSEX of individuals with mismatch between PEDSEX and Sex while Sex==SNPSEX automatically corrected: this will directly change the name.bim/.bed/.fam files!
[logical] If TRUE, no heterozygosity and missingness check will be conducted; short for do.run_check_heterozygosity=FALSE, do.run_check_missingness=FALSE and do.evaluate_check_het_and_miss=FALSE. Takes precedence over do.run_check_heterozygosity, do.run_check_missingness and do.evaluate_check_het_and_miss.
[logical] If TRUE, run
run_check_heterozygosity and
run_check_missingness
[logical] If TRUE, run
evaluate_check_het_and_miss.
[double] Threshold for acceptable missing genotype rate in any individual; has to be proportion between (0,1)
[double] Threshold for acceptable deviation from mean heterozygosity per individual. Expressed as multiples of standard deviation of heterozygosity (het), i.e. individuals outside mean(het) +/- hetTh*sd(het) will be returned as failing heterozygosity check; has to be larger than 0.
[logical] If TRUE, no relatedness check will be conducted; short for do.run_check_relatedness=FALSE and do.evaluate_check_relatedness=FALSE. Takes precedence over do.run_check_relatedness and do.evaluate_check_relatedness.
[logical] If TRUE, run
run_check_relatedness.
[logical] If TRUE, run
evaluate_check_relatedness.
[double] Threshold for acceptable proportion of IBD between pair of individuals.
[double] Threshold of minor allele frequency filter for selecting variants for IBD estimation.
[logical] Should high LD regions be filtered
before IBD estimation; carried out per default with high LD regions for
hg19 provided as default via genomebuild. For alternative genome
builds not provided or non-human data, high LD regions files can be
provided via high_ldregion_file.
[character] Path to file with high LD regions used
for filtering before IBD estimation if filter_high_ldregion == TRUE,
otherwise ignored; for human genome data, high LD region files are provided
and can simply be chosen via genomebuild. Files have to be
space-delimited, no column names with the following columns: chromosome,
region-start, region-end, region number. Chromosomes are specified without
'chr' prefix. For instance:
1 48000000 52000000 1
2 86000000 100500000 2
[character] Name of the genome build of the PLINK file annotations, ie mappings in the name.bim file. Will be used to remove high-LD regions based on the coordinates of the respective build. Options are hg18, hg19 and hg38. See @details.
[logical] If TRUE, no ancestry check will be conducted; short for do.run_check_ancestry=FALSE and do.evaluate_check_ancestry=FALSE. Takes precedence over do.run_check_ancestry and do.evaluate_check_ancestry.
[logical] If TRUE, run
run_check_ancestry.
[logical] If TRUE, run
evaluate_check_ancestry.
[character] Prefix of merged dataset (study and reference samples) used in plink --pca, resulting in prefixMergedDataset.eigenvec.
[double] Scaling factor of radius to be drawn around center of European reference samples, with study samples inside this radius considered to be of European descent and samples outside this radius of non-European descent. The radius is computed as the maximum Euclidean distance of European reference samples to the centre of European reference samples.
[character] Option to use pre-downloaded individual and population identifiers from either the 1000Genomes or HapMap project. If refSamples and refSamplesFile are not provided, the HapMap identifiers (or 1000Genomes is specified) will be used as default and the function will fail if the reference samples in the prefixMergedDataset do not match these reference samples. If refColors and refColorsFile are not provided, this also sets default colors for the reference populations.
[data.frame] Dataframe with sample identifiers [refSamplesIID] corresponding to IIDs in prefixMergedDataset.eigenvec and population identifier [refSamplesPop] corresponding to population IDs [refColorsPop] in refColorsfile/refColors. Either refSamples or refSamplesFile have to be specified.
[data.frame, optional] Dataframe with population IDs in column [refColorsPop] and corresponding colour-code for PCA plot in column [refColorsColor]. If not provided and is.null(refColorsFile) default colors are used.
[character] /path/to/File/with/reference samples. Needs columns with sample identifiers [refSamplesIID] corresponding to IIDs in prefixMergedDataset.eigenvec and population identifier [refSamplesPop] corresponding to population IDs [refColorsPop] in refColorsfile/refColors.
[character, optional] /path/to/File/with/Population/Colors containing population IDs in column [refColorsPop] and corresponding colour-code for PCA plot in column [refColorsColor].If not provided and is.null(refColors) default colors for are used.
[character] Column name of reference sample IDs in refSamples/refSamplesFile.
[character] Column name of reference sample population IDs in refSamples/refSamplesFile.
[character] Column name of population colors in refColors/refColorsFile
[character] Column name of reference sample population IDs in refColors/refColorsFile.
[character] Colour to be used for study population.
[logical] Set TRUE, to add fail IDs as text labels in scatter plot.
[character vector] Vector of sample IIDs to highlight in the plot (p_sexcheck); all highlight_samples IIDs have to be present in the IIDs of the name.fam file.
[character] Type of sample highlight, labeling by IID ("text"/"label") and/or highlighting data points in different "color" and/or "shape". "text" and "label" use ggrepel for minimal overlap of text labels ("text) or label boxes ("label"). Only one of "text" and "label" can be specified. Text/Label size can be specified with highlight_text_size, highlight color with highlight_color, or highlight shape with highlight_shape.
[integer] Text/Label size for samples specified to be highlighted (highlight_samples) by "text" or "label" (highlight_type).
[character] Color for samples specified to be highlighted (highlight_samples) by "color" (highlight_type).
[integer] Shape for samples specified to be highlighted (highlight_samples) by "shape" (highlight_type). Possible shapes and their encoding can be found at: https://ggplot2.tidyverse.org/articles/ggplot2-specs.html#sec:shape-spec
[logical] Should a separate legend for the highlighted samples be provided; only relevant for highlight_type == "color" or highlight_type == "shape".
[logical] Should plots be shown interactively? When choosing this option, make sure you have X-forwarding/graphical interface available for interactive plotting. Alternatively, set interactive=FALSE and save the returned plot object (p_sampleQC) via ggplot2::ggsave(p=p_sampleQC, other_arguments) or pdf(outfile) print(p_sampleQC) dev.off(). If TRUE, i) depicts the X-chromosomal heterozygosity (SNPSEX) of the samples split by their PEDSEX (if do.evaluate_check_sex is TRUE), ii) creates a scatter plot with samples' missingness rates on x-axis and their heterozygosity rates on the y-axis (if do.evaluate_check_het_and_miss is TRUE), iii) depicts all pair-wise IBD-estimates as histogram (if do.evaluate_check_relatedness is TRUE) and iv) creates a scatter plot of PC1 versus PC2 color-coded for samples of reference populations and study population (if do.check_ancestry is set to TRUE).
[logical] If TRUE, progress info is printed to standard out.
[character] Path to file with individuals to be retained in the analysis. The file has to be a space/tab-delimited text file with family IDs in the first column and within-family IDs in the second column. All samples not listed in this file will be removed from the current analysis. See https://www.cog-genomics.org/plink/1.9/filter#indiv. Default: NULL, i.e. no filtering on individuals.
[character] Path to file with individuals to be removed from the analysis. The file has to be a space/tab-delimited text file with family IDs in the first column and within-family IDs in the second column. All samples listed in this file will be removed from the current analysis. See https://www.cog-genomics.org/plink/1.9/filter#indiv. Default: NULL, i.e. no filtering on individuals.
[character] Path to file with makers to be removed from the analysis. The file has to be a text file with a list of variant IDs (usually one per line, but it's okay for them to just be separated by spaces). All listed variants will be removed from the current analysis. See https://www.cog-genomics.org/plink/1.9/filter#snp. Default: NULL, i.e. no filtering on markers.
[character] Path to file with makers to be included in the analysis. The file has to be a text file with a list of variant IDs (usually one per line, but it's okay for them to just be separated by spaces). All unlisted variants will be removed from the current analysis. See https://www.cog-genomics.org/plink/1.9/filter#snp. Default: NULL, i.e. no filtering on markers.
[integer] Size for legend text.
[integer] Size for legend title.
[integer] Size for axis text.
[integer] Size for axis title.
[integer] Size of the subplot labeling.
[integer] Size for plot title.
[character] Absolute path to PLINK executable
(https://www.cog-genomics.org/plink/1.9/) i.e.
plink should be accessible as path2plink -h. The full name of the executable
should be specified: for windows OS, this means path/plink.exe, for unix
platforms this is path/plink. If not provided, assumed that PATH set-up works
and PLINK will be found by exec('plink').
[logical] If TRUE, plink log and error messages are printed to standard out.
Named [list] with i) fail_list, a named [list] with 1.
sample_missingness containing a [vector] with sample IIDs failing the
missingness threshold imissTh, 2. highIBD containing a [vector] with sample
IIDs failing the relatedness threshold highIBDTh, 3. outlying_heterozygosity
containing a [vector] with sample IIDs failing the heterozygosity threshold
hetTh, 4. mismatched_sex containing a [vector] with the sample IIDs failing
the sexcheck based on SNPSEX and femaleTh/maleTh and 5. ancestry containing
a vector with sample IIDs failing the ancestry check based on europeanTh and
ii) p_sampleQC, a ggplot2-object 'containing' a sub-paneled plot with the
QC-plots of check_sex,
check_het_and_miss,
check_relatedness and check_ancestry, which can
be shown by print(p_sampleQC).
List entries contain NULL if that specific check was not chosen.
perIndividualQC wraps around the individual QC functions
check_sex, check_het_and_miss,
check_relatedness and check_ancestry. For details
on the parameters and outputs, check these function documentations. For
detailed output for fail IIDs (instead of simple IID lists), run each
function individually.
# NOT RUN {
indir <- system.file("extdata", package="plinkQC")
qcdir <- tempdir()
name <- "data"
# All quality control checks
# }
# NOT RUN {
# whole dataset
fail_individuals <- perIndividualQC(indir=indir, qcdir=qcdir, name=name,
refSamplesFile=paste(qcdir, "/HapMap_ID2Pop.txt",sep=""),
refColorsFile=paste(qcdir, "/HapMap_PopColors.txt", sep=""),
prefixMergedDataset="data.HapMapIII", interactive=FALSE, verbose=FALSE,
do.run_check_het_and_miss=FALSE, do.run_check_relatedness=FALSE,
do.run_check_sex=FALSE, do.run_check_ancestry=FALSE)
# Only check sex and missingness/heterozygosity
fail_sex_het_miss <- perIndividualQC(indir=indir, qcdir=qcdir, name=name,
dont.check_ancestry=TRUE, dont.check_relatedness=TRUE,
interactive=FALSE, verbose=FALSE)
# subset of dataset with sample highlighting
highlight_samples <- read.table(system.file("extdata", "keep_individuals",
package="plinkQC"))
remove_individuals_file <- system.file("extdata", "remove_individuals",
package="plinkQC")
individual_qc <- perIndividualQC(indir=indir, qcdir=qcdir, name=name,
refSamplesFile=paste(qcdir, "/HapMap_ID2Pop.txt",sep=""),
refColorsFile=paste(qcdir, "/HapMap_PopColors.txt", sep=""),
prefixMergedDataset="data.HapMapIII", interactive=FALSE, verbose=FALSE,
do.run_check_ancestry=FALSE, do.evaluate_check_ancestry=TRUE,
path2plink=path2plink,
remove_individuals=remove_individuals_file,
highlight_samples=highlight_samples[,2],
highlight_type = c("text", "color"), highlight_color="goldenrod")
# }
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