SNPRelate - Parallel Computing Toolset for Relatedness and Principal Component Analysis of SNP Data

Genome-wide association studies (GWAS) are widely used to investigate the genetic basis of diseases and traits, but they pose many computational challenges. We developed an R package SNPRelate to provide a binary format for single-nucleotide polymorphism (SNP) data in GWAS utilizing CoreArray Genomic Data Structure (GDS) data files. The GDS format offers the efficient operations specifically designed for integers with two bits, since a SNP could occupy only two bits. SNPRelate is also designed to accelerate two key computations on SNP data using parallel computing for multi-core symmetric multiprocessing computer architectures: Principal Component Analysis (PCA) and relatedness analysis using Identity-By-Descent measures. The SNP GDS format is also used by the GWASTools package with the support of S4 classes and generic functions. The extended GDS format is implemented in the SeqArray package to support the storage of single nucleotide variations (SNVs), insertion/deletion polymorphism (indel) and structural variation calls in whole-genome and whole-exome variant data.

Last updated 4 months ago

infrastructuregeneticsstatisticalmethodprincipalcomponentbioinformaticsgds-formatpcasimdsnpopenblascpp

12.69 score 104 stars 18 dependents 1.6k scripts 2.7k downloads

SeqArray - Data Management of Large-Scale Whole-Genome Sequence Variant Calls

Data management of large-scale whole-genome sequencing variant calls with thousands of individuals: genotypic data (e.g., SNVs, indels and structural variation calls) and annotations in SeqArray GDS files are stored in an array-oriented and compressed manner, with efficient data access using the R programming language.

Last updated 1 months ago

infrastructuredatarepresentationsequencinggeneticsbioinformaticsgds-formatsnpsnvweswgscpp

12.05 score 45 stars 9 dependents 1.1k scripts 1.7k downloads

gdsfmt - R Interface to CoreArray Genomic Data Structure (GDS) Files

Provides a high-level R interface to CoreArray Genomic Data Structure (GDS) data files. GDS is portable across platforms with hierarchical structure to store multiple scalable array-oriented data sets with metadata information. It is suited for large-scale datasets, especially for data which are much larger than the available random-access memory. The gdsfmt package offers the efficient operations specifically designed for integers of less than 8 bits, since a diploid genotype, like single-nucleotide polymorphism (SNP), usually occupies fewer bits than a byte. Data compression and decompression are available with relatively efficient random access. It is also allowed to read a GDS file in parallel with multiple R processes supported by the package parallel.

Last updated 11 days ago

infrastructuredataimportbioinformaticsgds-formatgenomicscpp

11.30 score 18 stars 30 dependents 920 scripts 3.4k downloads

HIBAG - HLA Genotype Imputation with Attribute Bagging

Imputes HLA classical alleles using GWAS SNP data, and it relies on a training set of HLA and SNP genotypes. HIBAG can be used by researchers with published parameter estimates 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 using bootstrap aggregating and random variable selection.

Last updated 4 months ago

geneticsstatisticalmethodbioinformaticsgpuhlaimputationmhcsnpcpp

8.24 score 30 stars 48 scripts 375 downloads