BigLD {gpart} | R Documentation

## Estimation of LD block regions

### Description

`BigLD` returns the estimation of LD block regions of given data.

### Usage

    BigLD(geno=NULL, SNPinfo=NULL,genofile=NULL, SNPinfofile=NULL,
    cutByForce=NULL, LD=c("r2", "Dprime"), CLQcut=0.5,
    clstgap=40000, CLQmode=c("density", "maximal"),
    leng=200, subTaskSize=1500, MAFcut=0.05, appendRare=FALSE,
    hrstType=c("near-nonhrst", "fast", "nonhrst"),
    hrstParam=200, chrN=NULL, startbp=-Inf, endbp=Inf)

### Arguments

`geno` | Data frame or matrix of additive genotype data, each column is additive genotype of each SNP.
`SNPinfo` | Data frame or matrix of SNPs information. 1st column is rsID and 2nd column is bp position.
`genofile` | Character constant; Genotype data file name (supporting format: .txt, .ped, .raw, .traw, .vcf).
`SNPinfofile` | Character constant; SNPinfo data file name (supporting format: .txt, .map).
`cutByForce` | Data frame; information of SNPs which are forced to be the last SNP LD block boundary.
`LD` | Character constant; LD measure to use, r2 or Dprime. Default "r2".
`CLQcut` | Numeric constant; a threshold for the LD measure value |r|, between 0 to 1. Default 0.5.
`clstgap` | Numeric constant; a threshold of physical distance (bp) between two consecutive SNPs which do not belong to the same clique, i.e., if a physical distance between two consecutive SNPs in a clique greater than `clstgap`, then the algorithm split the cliques satisfying each clique do not contain such consecutive SNPs. Default 40000.
`CLQmode` | Character constant; the way to give priority among detected cliques. if `CLQmode = "density"` then the algorithm gives priority to the clique of largest value of (Number of SNPs)/(range of clique), else if `CLQmode = "maximal"`, then the algorithm gives priority to the largest clique. The default is "density".
`leng` | Numeric constant; the number of SNPs in a preceding and a following region of each sub-region boundary, every SNP in a preceding and every SNP in a following region need to be in weak LD. Default 200.
`subTaskSize` | Numeric constant; upper bound of the number of SNPs in a one-take sub-region. Default 1500.
`MAFcut` | Numeric constant; the MAF threshold. Default 0.05.
`appendRare` | logical; if TRUE, the function append rare variants with MAF<MAFcut to the constructed blocks.
`hrstType` | Character constant; heuristic methods. If you want to do not use heuristic algorithm, set `hrstType = "nonhrst"`. If you want to use heuristic algorithm suggested in Kim et al.,(2017), set `hrstType = "fast"`. That algorithm is fastest heuristic algorithm and suitable when your memory capacity is not greater than 8GB. If you want to obtain the results similar to the that of non-heuristic algorithm, set `hrstType = "near-nonhrst"`.
`hrstParam` | Numeric constant; parameter for heuristic algorithm "near-nonhrst". Default is `200`. It is recommended that you set the parameter to greater than 150.
`chrN` | Numeric(or Character) constant (or vector); chromosome number to use.
`startbp` | Numeric constant; starting bp position of the `chrN`. Default -Inf.
`endbp` | Numeric constant; last bp position of the `chrN`. Default Inf.

### Value

A data frame of block estimation result. Each row of data frame shows the starting SNP and end SNP of each estimated LD block.

### Author(s)

Sun-Ah Kim <sunny03@snu.ac.kr>, Yun Joo Yoo <yyoo@snu.ac.kr>

### See Also

`CLQD`, `LDblockHeatmap`

### Examples

    data(geno)
    data(SNPinfo)
    BigLD(geno=geno, SNPinfo=SNPinfo, startbp = 16058400, endbp = 16076500)

    ## Not run:
    BigLD(geno, SNPinfo, LD = "Dprime")
    BigLD(geno, SNPinfo, CLQcut = 0.5, clstgap = 40000, leng = 200, subTaskSize = 1500)

    ## End(Not run)

[Package gpart version 1.6.0 Index]