tagIMPUTE (Tag-based imputation) is a command-line program for the imputation of untyped SNPs. tagIMPUTE is based on a few flanking SNPs that can optimally predict the SNP under imputation.
The genipe module includes a script (named genipe-launcher) that automatically runs a genome-wide imputation pipeline using Plink, shapeit and impute2.
hsphase is an R package that implements a very fast method for phasing, sire genotype imputation, identification of paternal strand of origin and recombination events in half-sib families
HIBAG is a state of the art software package for imputing HLA types using SNP data, and it uses the R statistical programming language. HIBAG is highly accurate, computationally tractable, and can be used by researchers with published parameter estimates (provided for subjects of European, Asian, Hispanic and African ancestries) instead of requiring access to large training sample datasets. It combines the concepts of attribute bagging, an ensemble classifier method, with haplotype inference for SNPs and HLA types. Attribute bagging is a technique which improves the accuracy and stability of classifier ensembles deduced using bootstrap aggregating and random subsets of variables.
ImpG-Summary is a software package implementing methods for imputation from summary statistics and accompanying data. The software takes as input 1000 Genomes reference haplotypes and summary association statistics at a typed set of SNPs from a GWAS or meta-analysis. It outputs summary association statistics at all 1000 Genomes variants.
PBLR is an effective tool to recover dropout events on both simulated and real datasets,and can dramatically improve low-dimensional representation and reveal gene-gene relationship compared to several state-of-the-art methods.