Easy-to-use, efficient, flexible and scalable tools for analyzing massive SNP arrays. Privé et al. (2018) <doi:10.1093/bioinformatics/bty185>.
A FBM.code256
(typically <bigSNP>$genotypes).
You shouldn't have missing values. Also, remember to do quality control,
e.g. some algorithms in this package won't work if you use SNPs with 0 MAF.
A FBM.code256
(typically <bigSNP>$genotypes).
You can have missing values in these data.
A bigSNP.
Vector of integers specifying each SNP's chromosome.
Typically <bigSNP>$map$chromosome.
Vector of integers specifying the physical position
on a chromosome (in base pairs) of each SNP.
Typically <bigSNP>$map$physical.pos.
Number of trials, parameter of the binomial distribution.
Default is 2, which corresponds to diploidy, such as for the human genome.
An optional vector of the row indices (individuals) that
are used. If not specified, all rows are used.
Don't use negative indices.
An optional vector of the column indices (SNPs) that are used.
If not specified, all columns are used.
Don't use negative indices.
Number of cores used. Default doesn't use parallelism. You may use nb_cores.
Deprecated.
Object of type bed, which is the mapping of some bed file.
Use obj.bed <- bed(bedfile) to get this object.
Maintainer: Florian Privé florian.prive.21@gmail.com
Other contributors:
Michael Blum michael.blum@univ-grenoble-alpes.fr [thesis advisor]
Hugues Aschard hugues.aschard@pasteur.fr [thesis advisor]
Bjarni Jóhann Vilhjálmsson bjv@econ.au.dk [thesis advisor]
Useful links: