lassosum: Function to obtain LASSO estimates of a regression problem...
In tshmak/lassosum: LASSO with summary statistics and a reference panel

Description Usage Arguments Details Value Note

Function to obtain LASSO estimates of a regression problem given summary statistics and a reference panel

lassosum: A package for carrying out LASSO regression using GWAS summary statistics

lassosum(cor, bfile, lambda = exp(seq(log(0.001), log(0.1), length.out =
  20)), shrink = 0.9, thr = 1e-04, init = NULL, trace = 0,
  maxiter = 10000, blocks = NULL, keep = NULL, remove = NULL,
  extract = NULL, exclude = NULL, chr = NULL, mem.limit = 4 * 10^9,
  chunks = NULL, cluster = NULL)

`cor`	A vector of correlations (r)
`bfile`	PLINK bfile (as character, without the .bed extension)
`lambda`	A vector of λs (the tuning parameter)
`shrink`	The shrinkage parameter s for the correlation matrix R
`thr`	convergence threshold for β
`init`	Initial values for β as a vector of the same length as `cor`
`trace`	An integer controlling the amount of output generated.
`maxiter`	Maximum number of iterations
`blocks`	A vector to split the genome by blocks (coded as c(1,1,..., 2, 2, ..., etc.))
`keep`	samples to keep
`remove`	samples to remove
`extract`	SNPs to extract
`exclude`	SNPs to exclude
`chr`	a vector of chromosomes
`mem.limit`	Memory limit for genotype matrix loaded. Note that other overheads are not included.
`chunks`	Splitting the genome into chunks for computation. Either an integer indicating the number of chunks or a vector (length equal to `cor`) giving the exact split.
`cluster`	A `cluster` object from the `parallel` package for parallel computing

A function to find the minimum of β in

f(β)=β'Rβ - 2β'r + 2λ||β||_1

where

R=(1-s)X'X/n + sI

is a shrunken correlation matrix, with X being standardized reference panel. s should take values in (0,1]. r is a vector of correlations. keep, remove could take one of three formats: (1) A logical vector indicating which indivduals to keep/remove, (2) A data.frame with two columns giving the FID and IID of the indivdiuals to keep/remove (matching those in the .fam file), or (3) a character scalar giving the text file with the FID/IID. Likewise extract, exclude can also take one of the three formats, except with the role of the FID/IID data.frame replaced with a character vector of SNP ids (matching those in the .bim file).

A list with the following

`lambda`	same as the lambda input
`beta`	A matrix of estimated coefficients
`conv`	A vector of convergence indicators. 1 means converged. 0 not converged.
`pred`	=√(1-s)Xβ
`loss`	=(1-s)β'X'Xβ/n - 2β'r
`fbeta`	=β'Rβ - 2β'r + 2λ\|\|β\|\|_1
`sd`	The standard deviation of the reference panel SNPs
`shrink`	same as input
`nparams`	Number of non-zero coefficients