Showing 9 of total 9 results (show query)
bioc
SIMD:Statistical Inferences with MeDIP-seq Data (SIMD) to infer the methylation level for each CpG site
This package provides a inferential analysis method for detecting differentially expressed CpG sites in MeDIP-seq data. It uses statistical framework and EM algorithm, to identify differentially expressed CpG sites. The methods on this package are described in the article 'Methylation-level Inferences and Detection of Differential Methylation with Medip-seq Data' by Yan Zhou, Jiadi Zhu, Mingtao Zhao, Baoxue Zhang, Chunfu Jiang and Xiyan Yang (2018, pending publication).
Maintained by Jiadi Zhu. Last updated 5 months ago.
immunooncologydifferentialmethylationsinglecelldifferentialexpression
62.7 match 5.00 score 2 scriptsbioc
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.
Maintained by Xiuwen Zheng. Last updated 5 months ago.
infrastructuregeneticsstatisticalmethodprincipalcomponentbioinformaticsgds-formatpcasimdsnpopenblascpp
11.0 match 104 stars 12.69 score 1.6k scripts 18 dependentsnanxstats
ssw:Striped Smith-Waterman Algorithm for Sequence Alignment using SIMD
Provides an R interface for 'SSW' (Striped Smith-Waterman) via its 'Python' binding 'ssw-py'. 'SSW' is a fast 'C' and 'C++' implementation of the Smith-Waterman algorithm for pairwise sequence alignment using Single-Instruction-Multiple-Data (SIMD) instructions. 'SSW' enhances the standard algorithm by efficiently returning alignment information and suboptimal alignment scores. The core 'SSW' library offers performance improvements for various bioinformatics tasks, including protein database searches, short-read alignments, primary and split-read mapping, structural variant detection, and read-overlap graph generation. These features make 'SSW' particularly useful for genomic applications. Zhao et al. (2013) <doi:10.1371/journal.pone.0082138> developed the original 'C' and 'C++' implementation.
Maintained by Nan Xiao. Last updated 6 months ago.
bioinformaticsreticulatesequence-alignmentsimdsmith-waterman
14.3 match 6 stars 5.18 scorebiodiverse
spAbundance:Univariate and Multivariate Spatial Modeling of Species Abundance
Fits single-species (univariate) and multi-species (multivariate) non-spatial and spatial abundance models in a Bayesian framework using Markov Chain Monte Carlo (MCMC). Spatial models are fit using Nearest Neighbor Gaussian Processes (NNGPs). Details on NNGP models are given in Datta, Banerjee, Finley, and Gelfand (2016) <doi:10.1080/01621459.2015.1044091> and Finley, Datta, and Banerjee (2022) <doi:10.18637/jss.v103.i05>. Fits single-species and multi-species spatial and non-spatial versions of generalized linear mixed models (Gaussian, Poisson, Negative Binomial), N-mixture models (Royle 2004 <doi:10.1111/j.0006-341X.2004.00142.x>) and hierarchical distance sampling models (Royle, Dawson, Bates (2004) <doi:10.1890/03-3127>). Multi-species spatial models are fit using a spatial factor modeling approach with NNGPs for computational efficiency.
Maintained by Jeffrey Doser. Last updated 17 days ago.
3.0 match 17 stars 6.15 score 43 scripts 1 dependentsmsuchard
RcppXsimd:Xsimd C++ Header-Only Library Files
This header-only library provides modern, portable C++ wrappers for SIMD intrinsics and parallelized, optimized math implementations (SSE, AVX, NEON, AVX512). By placing this library in this package, we offer an efficient distribution system for Xsimd <https://github.com/xtensor-stack/xsimd> for R packages using CRAN.
Maintained by Marc A. Suchard. Last updated 4 years ago.
9.3 match 1.70 score 6 scriptseddelbuettel
RcppSimdJson:'Rcpp' Bindings for the 'simdjson' Header-Only Library for 'JSON' Parsing
The 'JSON' format is ubiquitous for data interchange, and the 'simdjson' library written by Daniel Lemire (and many contributors) provides a high-performance parser for these files which by relying on parallel 'SIMD' instruction manages to parse these files as faster than disk speed. See the <doi:10.48550/arXiv.1902.08318> paper for more details about 'simdjson'. This package parses 'JSON' from string, file, or remote URLs under a variety of settings.
Maintained by Dirk Eddelbuettel. Last updated 9 days ago.
0.5 match 118 stars 9.02 score 47 scripts 20 dependentschrchang
pgenlibr:PLINK 2 Binary (.pgen) Reader
A thin wrapper over PLINK 2's core libraries which provides an R interface for reading .pgen files. A minimal .pvar loader is also included. Chang et al. (2015) \doi{10.1186/s13742-015-0047-8}.
Maintained by Christopher Chang. Last updated 2 months ago.
1.5 match 2.98 score 64 scripts