Description Usage Arguments Details Value References Examples
Convert input data files to an object of haplohh-class
.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | data2haplohh(
hap_file,
map_file = NA,
min_perc_geno.hap = NA,
min_perc_geno.mrk = 100,
min_maf = NA,
chr.name = NA,
popsel = NA,
recode.allele = FALSE,
allele_coding = "12",
haplotype.in.columns = FALSE,
remove_multiple_markers = FALSE,
polarize_vcf = TRUE,
capitalize_AA = TRUE,
vcf_reader = "data.table",
position_scaling_factor = NA,
verbose = TRUE
)
|
hap_file |
file containing haplotype data (see details below). |
map_file |
file containing map information (see details below). |
min_perc_geno.hap |
threshold on percentage of missing data for haplotypes
(haplotypes with less than |
min_perc_geno.mrk |
threshold on percentage of missing data for markers (markers genotyped on less than
|
min_maf |
threshold on the Minor Allele Frequency. Markers having a MAF lower than or equal to minmaf are discarded.
In case of multi-allelic markers the second-most frequent allele is referred to as minor allele.
Setting this value to zero eliminates monomorphic sites. Default is |
chr.name |
name of the chromosome considered (relevant if data for several chromosomes is contained in the haplotype or map file). |
popsel |
code of the population considered (relevant for fastPHASE output which can contain haplotypes from various populations). |
recode.allele |
*Deprecated*. logical. |
allele_coding |
the allele coding provided by the user. Either |
haplotype.in.columns |
logical. If |
remove_multiple_markers |
logical. If |
polarize_vcf |
logical. Only of relevance for vcf files. If |
capitalize_AA |
logical. Only of relevance for vcf files with ancestral allele information.
Low confidence ancestral alleles are usually coded by lower-case letters. If |
vcf_reader |
library used to read vcf. By default, low-level parsing is
performed using the generic package |
position_scaling_factor |
intended primarily for output of ms where positions lie in the interval [0,1]. These can be rescaled to sizes of typical markers in real data. |
verbose |
logical. If |
Five haplotype input formats are supported:
a "standard format" with haplotypes in rows and markers in columns (with no header, but a haplotype ID/name in the first column).
a "transposed format" similar to the one produced by the phasing program SHAPEIT2 (O'Connell et al., 2014) in which haplotypes are in columns and markers in rows (with neither header nor marker IDs nor haplotype IDs).
output files from the fastPHASE program (Sheet and Stephens, 2006).
If haplotypes from several different population were phased simultaneously (-u fastPHASE option
was used), it is necessary to specify the population of interest by parameter popsel
(if this parameter is not or wrongly set, the error message will provide a list of
the population numbers contained in the file).
files in variant call format (vcf). No mapfile is needed is this case. If
the file contains several chromosomes, it is necessary to choose one by parameter
chr.name
.
output of the simulation program 'ms'. No mapfile is needed in this case. If the file
contains several 'runs', a specific number has to be specified by the
parameter chr.name
.
The "transposed format" has to be explicitly set while the other formats are recognized automatically.
The map file contains marker information in three, or, if it is used for polarization (see below), five columns:
marker name/id
chromosome
position (physical or genetic)
ancestral allele encoding
derived allele encoding
The markers must be in the same order as in the haplotype file. If
several chromosomes are represented in the map file, it is necessary to choose that
which corresponds to the haplotype file by parameter chr.name
.
Haplotypes can be given either with alleles already coded as numbers (in two possible ways)
or with the actual alleles (e.g. nucleotides) which can be translated into numbers
either using the fourth and fifth column of the map file or by their alpha-numeric order.
Correspondingly, the parameter allele_coding
has to be set to either "12"
,
"01"
, "map"
or "none"
:
"12"
: 0 represents missing values, 1 the ancestral allele
and 2 (or higher integers) derived allele(s).
"01"
: NA
or '.' (a point) represent missing values, 0 the
ancestral and 1 (or higher integers) derived allele(s).
"map"
: for each marker, the fourth column of the map file
defines the ancestral allele and the fifth column derived alleles.
In case of multiple derived alleles, they must be separated by commas without space.
Alleles in the haplotype file which do not appear in neither of the two columns
of the map file are regarded as missing values (NA
).
"none"
: NA
or '.' (a point) represent missing values, otherwise for each
marker the allele that comes first in alpha-numeric
order is coded by 0, the next by 1, etc. Evidently, this coding does not convey
any information about allele status as ancestral or derived, hence the alleles
cannot be regarded as polarized.
The information of allelic ancestry is exploited only in the frequency-bin-wise
standardization of iHS (see ihh2ihs
). However, although ancestry status does
not figure in the formulas of the cross populations statistics
Rsb and XP-EHH, their values do depend on the assigned status.
The arguments min_perc_geno.hap
,
min_perc_geno.mrk
and min_maf
are evaluated in this order.
The returned value is an object of haplohh-class
.
Scheet P, Stephens M (2006) A fast and flexible statistical model for large-scale population genotype data: applications to inferring missing genotypes and haplotypic phase. Am J Hum Genet, 78, 629-644.
O'Connell J, Gurdasani D, Delaneau O, et al (2014) A general approach for haplotype phasing across the full spectrum of relatedness. PLoS Genet, 10, e1004234.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | #copy example files into the current working directory.
make.example.files()
#create object using a haplotype file in "standard format"
hap <- data2haplohh(hap_file = "bta12_cgu.hap",
map_file = "map.inp",
chr.name = 12,
allele_coding = "map")
#create object using fastPHASE output
hap <- data2haplohh(hap_file = "bta12_hapguess_switch.out",
map_file = "map.inp",
chr.name = 12,
popsel = 7,
allele_coding = "map")
#clean up demo files
remove.example.files()
|
* Reading input file(s) *
Map info: 1424 markers declared for chromosome 12 .
Haplotype input file in standard format assumed.
Alleles are being recoded according to fourth and fifth column of map file.
* Filtering data *
Discard markers genotyped on less than 100 % of haplotypes.
No marker discarded.
Data consists of 280 haplotypes and 1424 markers.
Number of mono-, bi-, multi-allelic markers:
1 2
27 1397
* Reading input file(s) *
Map info: 1424 markers declared for chromosome 12 .
Haplotype input file in fastPHASE format assumed.
Haplotypes in the fastPHASE output file originate from 8 populations.
Alleles are being recoded according to fourth and fifth column of map file.
* Filtering data *
Discard markers genotyped on less than 100 % of haplotypes.
No marker discarded.
Data consists of 280 haplotypes and 1424 markers.
Number of mono-, bi-, multi-allelic markers:
1 2
27 1397
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