Showing 29 of total 29 results (show query)
bioc
qpgraph:Estimation of Genetic and Molecular Regulatory Networks from High-Throughput Genomics Data
Estimate gene and eQTL networks from high-throughput expression and genotyping assays.
Maintained by Robert Castelo. Last updated 5 days ago.
microarraygeneexpressiontranscriptionpathwaysnetworkinferencegraphandnetworkgeneregulationgeneticsgeneticvariabilitysnpsoftwareopenblas
3 stars 8.72 score 20 scripts 3 dependents
apariciojohan
agriutilities:Utilities for Data Analysis in Agriculture
Utilities designed to make the analysis of field trials easier and more accessible for everyone working in plant breeding. It provides a simple and intuitive interface for conducting single and multi-environmental trial analysis, with minimal coding required. Whether you're a beginner or an experienced user, 'agriutilities' will help you quickly and easily carry out complex analyses with confidence. With built-in functions for fitting Linear Mixed Models, 'agriutilities' is the ideal choice for anyone who wants to save time and focus on interpreting their results. Some of the functions require the R package 'asreml' for the 'ASReml' software, this can be obtained upon purchase from 'VSN' international <https://vsni.co.uk/software/asreml-r/>.
Maintained by Johan Aparicio. Last updated 2 months ago.
18 stars 7.46 score 88 scripts 1 dependentsapariciojohan
flexFitR:Flexible Non-Linear Least Square Model Fitting
Provides tools for flexible non-linear least squares model fitting using general-purpose optimization techniques. The package supports a variety of optimization algorithms, including those provided by the 'optimx' package, making it suitable for handling complex non-linear models. Features include parallel processing support via the 'future' and 'foreach' packages, comprehensive model diagnostics, and visualization capabilities. Implements methods described in Nash and Varadhan (2011, <doi:10.18637/jss.v043.i09>).
Maintained by Johan Aparicio. Last updated 1 days ago.
2 stars 7.13 score 77 scripts
drj001
ASMap:Linkage Map Construction using the MSTmap Algorithm
Functions for Accurate and Speedy linkage map construction, manipulation and diagnosis of Doubled Haploid, Backcross and Recombinant Inbred 'R/qtl' objects. This includes extremely fast linkage map clustering and optimal marker ordering using 'MSTmap' (see Wu et al.,2008).
Maintained by Julian Taylor. Last updated 5 months ago.
2 stars 6.73 score 79 scripts
kbroman
qtlcharts:Interactive Graphics for QTL Experiments
Web-based interactive charts (using D3.js) for the analysis of experimental crosses to identify genetic loci (quantitative trait loci, QTL) contributing to variation in quantitative traits. Broman (2015) <doi:10.1534/genetics.114.172742>.
Maintained by Karl W Broman. Last updated 2 years ago.
84 stars 6.61 score 322 scripts
bio-services
LinkageMapView:Plot Linkage Group Maps with Quantitative Trait Loci
Produces high resolution, publication ready linkage maps and quantitative trait loci maps. Input can be output from 'R/qtl', simple text or comma delimited files. Output is currently a portable document file.
Maintained by Steven Blanchard. Last updated 5 years ago.
9 stars 6.55 score 79 scripts
biometris
statgenSTA:Single Trial Analysis (STA) of Field Trials
Phenotypic analysis of field trials using mixed models with and without spatial components. One of a series of statistical genetic packages for streamlining the analysis of typical plant breeding experiments developed by Biometris. Some functions have been created to be used in conjunction with the R package 'asreml' for the 'ASReml' software, which can be obtained upon purchase from 'VSN' international (<https://vsni.co.uk/software/asreml-r/>).
Maintained by Bart-Jan van Rossum. Last updated 6 months ago.
4 stars 6.30 score 14 scripts 3 dependentsbiometris
statgenGxE:Genotype by Environment (GxE) Analysis
Analysis of multi environment data of plant breeding experiments following the analyses described in Malosetti, Ribaut, and van Eeuwijk (2013), <doi:10.3389/fphys.2013.00044>. One of a series of statistical genetic packages for streamlining the analysis of typical plant breeding experiments developed by Biometris. Some functions have been created to be used in conjunction with the R package 'asreml' for the 'ASReml' software, which can be obtained upon purchase from 'VSN' international (<https://vsni.co.uk/software/asreml-r/>).
Maintained by Bart-Jan van Rossum. Last updated 7 months ago.
geneticsgxegxe-modellingmulti-trial-analysis
10 stars 5.53 score 17 scripts
vincentgarin
mppR:Multi-Parent Population QTL Analysis
Analysis of experimental multi-parent populations to detect regions of the genome (called quantitative trait loci, QTLs) influencing phenotypic traits measured in unique and multiple environments. The population must be composed of crosses between a set of at least three parents (e.g. factorial design, 'diallel', or nested association mapping). The functions cover data processing, QTL detection, and results visualization. The implemented methodology is described in Garin, Wimmer, Mezmouk, Malosetti and van Eeuwijk (2017) <doi:10.1007/s00122-017-2923-3>, in Garin, Malosetti and van Eeuwijk (2020) <doi: 10.1007/s00122-020-03621-0>, and in Garin, Diallo, Tekete, Thera, ..., and Rami (2024) <doi: 10.1093/genetics/iyae003>.
Maintained by Vincent Garin. Last updated 1 years ago.
2 stars 5.35 score 28 scriptsbioc
MOSClip:Multi Omics Survival Clip
Topological pathway analysis tool able to integrate multi-omics data. It finds survival-associated modules or significant modules for two-class analysis. This tool have two main methods: pathway tests and module tests. The latter method allows the user to dig inside the pathways itself.
Maintained by Paolo Martini. Last updated 5 months ago.
softwarestatisticalmethodgraphandnetworksurvivalregressiondimensionreductionpathwaysreactome
5.34 score 5 scripts
rqtl
qtl2convert:Convert Data among QTL Mapping Packages
Functions to convert data structures among the 'qtl2', 'qtl', and 'DOQTL' packages for mapping quantitative trait loci (QTL).
Maintained by Karl W Broman. Last updated 12 months ago.
5 stars 5.24 score 230 scripts 1 dependentskbroman
lineup:Lining Up Two Sets of Measurements
Tools for detecting and correcting sample mix-ups between two sets of measurements, such as between gene expression data on two tissues. Broman et al. (2015) <doi:10.1534/g3.115.019778>.
Maintained by Karl W Broman. Last updated 9 months ago.
4 stars 5.23 score 85 scriptsdrj001
wgaim:Whole Genome Average Interval Mapping for QTL Detection and Estimation using ASReml-R
A computationally efficient whole genome approach to detecting and estimating significant QTL in linkage maps using the flexible linear mixed modelling functionality of ASReml-R.
Maintained by Julian Taylor. Last updated 7 months ago.
1 stars 4.90 score 16 scripts
ivis4ml
fssemR:Fused Sparse Structural Equation Models to Jointly Infer Gene Regulatory Network
An optimizer of Fused-Sparse Structural Equation Models, which is the state of the art jointly fused sparse maximum likelihood function for structural equation models proposed by Xin Zhou and Xiaodong Cai (2018 <doi:10.1101/466623>).
Maintained by Xin Zhou. Last updated 3 years ago.
4 stars 4.85 score 35 scripts
umn-barleyoatsilphium
PopVar:Genomic Breeding Tools: Genetic Variance Prediction and Cross-Validation
The main attribute of 'PopVar' is the prediction of genetic variance in bi-parental populations, from which the package derives its name. 'PopVar' contains a set of functions that use phenotypic and genotypic data from a set of candidate parents to 1) predict the mean, genetic variance, and superior progeny value of all, or a defined set of pairwise bi-parental crosses, and 2) perform cross-validation to estimate genome-wide prediction accuracy of multiple statistical models. More details are available in Mohammadi, Tiede, and Smith (2015, <doi:10.2135/cropsci2015.01.0030>). A dataset 'think_barley.rda' is included for reference and examples.
Maintained by Jeffrey Neyhart. Last updated 5 months ago.
4.60 score 10 scriptsbioc
clipper:Gene Set Analysis Exploiting Pathway Topology
Implements topological gene set analysis using a two-step empirical approach. It exploits graph decomposition theory to create a junction tree and reconstruct the most relevant signal path. In the first step clipper selects significant pathways according to statistical tests on the means and the concentration matrices of the graphs derived from pathway topologies. Then, it "clips" the whole pathway identifying the signal paths having the greatest association with a specific phenotype.
Maintained by Paolo Martini. Last updated 5 months ago.
4.48 score 19 scriptskbroman
xoi:Tools for Analyzing Crossover Interference
Analysis of crossover interference in experimental crosses, particularly regarding the gamma model. See, for example, Broman and Weber (2000) <doi:10.1086/302923>.
Maintained by Karl W Broman. Last updated 2 years ago.
4 stars 3.76 score 29 scriptsbioc
trigger:Transcriptional Regulatory Inference from Genetics of Gene ExpRession
This R package provides tools for the statistical analysis of integrative genomic data that involve some combination of: genotypes, high-dimensional intermediate traits (e.g., gene expression, protein abundance), and higher-order traits (phenotypes). The package includes functions to: (1) construct global linkage maps between genetic markers and gene expression; (2) analyze multiple-locus linkage (epistasis) for gene expression; (3) quantify the proportion of genome-wide variation explained by each locus and identify eQTL hotspots; (4) estimate pair-wise causal gene regulatory probabilities and construct gene regulatory networks; and (5) identify causal genes for a quantitative trait of interest.
Maintained by John D. Storey. Last updated 7 days ago.
geneexpressionsnpgeneticvariabilitymicroarraygenetics
3.48 score 3 scripts
dannyarends
ctl:Correlated Trait Locus Mapping
Identification and network inference of genetic loci associated with correlation changes in quantitative traits (called correlated trait loci, CTLs). Arends et al. (2016) <doi:10.21105/joss.00087>.
Maintained by Danny Arends. Last updated 1 years ago.
3.31 score 103 scripts
cran
qtlhot:Inference for QTL Hotspots
Functions to infer co-mapping trait hotspots and causal models. Chaibub Neto E, Keller MP, Broman AF, Attie AD, Jansen RC, Broman KW, Yandell BS (2012) Quantile-based permutation thresholds for QTL hotspots. Genetics 191 : 1355-1365. <doi:10.1534/genetics.112.139451>. Chaibub Neto E, Broman AT, Keller MP, Attie AD, Zhang B, Zhu J, Yandell BS (2013) Modeling causality for pairs of phenotypes in system genetics. Genetics 193 : 1003-1013. <doi:10.1534/genetics.112.147124>.
Maintained by Brian S. Yandell. Last updated 7 years ago.
2.30 scorecran
qtlnet:Causal Inference of QTL Networks
Functions to Simultaneously Infer Causal Graphs and Genetic Architecture. Includes acyclic and cyclic graphs for data from an experimental cross with a modest number (<10) of phenotypes driven by a few genetic loci (QTL). Chaibub Neto E, Keller MP, Attie AD, Yandell BS (2010) Causal Graphical Models in Systems Genetics: a unified framework for joint inference of causal network and genetic architecture for correlated phenotypes. Annals of Applied Statistics 4: 320-339. <doi:10.1214/09-AOAS288>.
Maintained by Brian S. Yandell. Last updated 5 years ago.
2.30 scorecran
rNeighborQTL:Interval Mapping for Quantitative Trait Loci Underlying Neighbor Effects
To enable quantitative trait loci mapping of neighbor effects, this package extends a single-marker regression to interval mapping. The theoretical background of the method is described in Sato et al. (2021) <doi:10.1093/g3journal/jkab017>.
Maintained by Yasuhiro Sato. Last updated 4 years ago.
2.00 scorecran
topologyGSA:Gene Set Analysis Exploiting Pathway Topology
Using Gaussian graphical models we propose a novel approach to perform pathway analysis using gene expression. Given the structure of a graph (a pathway) we introduce two statistical tests to compare the mean and the concentration matrices between two groups. Specifically, these tests can be performed on the graph and on its connected components (cliques). The package is based on the method described in Massa M.S., Chiogna M., Romualdi C. (2010) <doi:10.1186/1752-0509-4-121>.
Maintained by Gabriele Sales. Last updated 2 years ago.
1.60 score
yuanmingzhang
QTL.gCIMapping:QTL Genome-Wide Composite Interval Mapping
Conduct multiple quantitative trait loci (QTL) and QTL-by-environment interaction (QEI) mapping via ordinary or compressed variance component mixed models with random- or fixed QTL/QEI effects. First, each position on the genome is detected in order to obtain a negative logarithm P-value curve against genome position. Then, all the peaks on each effect (additive or dominant) curve or on each locus curve are viewed as potential main-effect QTLs and QEIs, all their effects are included in a multi-locus model, their effects are estimated by both least angle regression and empirical Bayes (or adaptive lasso) in backcross and F2 populations, and true QTLs and QEIs are identified by likelihood radio test. See Zhou et al. (2022) <doi:10.1093/bib/bbab596> and Wen et al. (2018) <doi:10.1093/bib/bby058>.
Maintained by Yuanming Zhang. Last updated 3 years ago.
1 stars 1.48 score 2 scripts 1 dependentsyuanmingzhang
QTL.gCIMapping.GUI:QTL Genome-Wide Composite Interval Mapping with Graphical User Interface
Conduct multiple quantitative trait loci (QTL) mapping under the framework of random-QTL-effect linear mixed model. First, each position on the genome is detected in order to obtain a negative logarithm P-value curve against genome position. Then, all the peaks on each effect (additive or dominant) curve are viewed as potential QTL, all the effects of the potential QTL are included in a multi-QTL model, their effects are estimated by empirical Bayes in doubled haploid population or by adaptive lasso in F2 population, and true QTL are identified by likelihood radio test. See Wen et al. (2018) <doi:10.1093/bib/bby058>.
Maintained by Yuanming Zhang. Last updated 4 years ago.
1.00 score 6 scripts