Showing 23 of total 23 results (show query)
bioc
cardelino:Clone Identification from Single Cell Data
Methods to infer clonal tree configuration for a population of cells using single-cell RNA-seq data (scRNA-seq), and possibly other data modalities. Methods are also provided to assign cells to inferred clones and explore differences in gene expression between clones. These methods can flexibly integrate information from imperfect clonal trees inferred based on bulk exome-seq data, and sparse variant alleles expressed in scRNA-seq data. A flexible beta-binomial error model that accounts for stochastic dropout events as well as systematic allelic imbalance is used.
Maintained by Davis McCarthy. Last updated 5 months ago.
singlecellrnaseqvisualizationtranscriptomicsgeneexpressionsequencingsoftwareexomeseqclonal-clusteringgibbs-samplingscrna-seqsingle-cellsomatic-mutations
61 stars 7.05 score 62 scripts
bioc
gwascat:representing and modeling data in the EMBL-EBI GWAS catalog
Represent and model data in the EMBL-EBI GWAS catalog.
Maintained by VJ Carey. Last updated 3 days ago.
6.35 score 110 scripts 2 dependentsbioc
martini:GWAS Incorporating Networks
martini deals with the low power inherent to GWAS studies by using prior knowledge represented as a network. SNPs are the vertices of the network, and the edges represent biological relationships between them (genomic adjacency, belonging to the same gene, physical interaction between protein products). The network is scanned using SConES, which looks for groups of SNPs maximally associated with the phenotype, that form a close subnetwork.
Maintained by Hector Climente-Gonzalez. Last updated 5 months ago.
softwaregenomewideassociationsnpgeneticvariabilitygeneticsfeatureextractiongraphandnetworknetworkbioinformaticsgenomicsgwasnetwork-analysissnpssystems-biologycpp
4 stars 6.16 score 30 scriptsbioc
circRNAprofiler:circRNAprofiler: An R-Based Computational Framework for the Downstream Analysis of Circular RNAs
R-based computational framework for a comprehensive in silico analysis of circRNAs. This computational framework allows to combine and analyze circRNAs previously detected by multiple publicly available annotation-based circRNA detection tools. It covers different aspects of circRNAs analysis from differential expression analysis, evolutionary conservation, biogenesis to functional analysis.
Maintained by Simona Aufiero. Last updated 5 months ago.
annotationstructuralpredictionfunctionalpredictiongenepredictiongenomeassemblydifferentialexpression
10 stars 5.78 score 5 scriptsbioc
RVS:Computes estimates of the probability of related individuals sharing a rare variant
Rare Variant Sharing (RVS) implements tests of association and linkage between rare genetic variant genotypes and a dichotomous phenotype, e.g. a disease status, in family samples. The tests are based on probabilities of rare variant sharing by relatives under the null hypothesis of absence of linkage and association between the rare variants and the phenotype and apply to single variants or multiple variants in a region (e.g. gene-based test).
Maintained by Alexandre Bureau. Last updated 5 months ago.
immunooncologygeneticsgenomewideassociationvariantdetectionexomeseqwholegenome
4.78 score 9 scripts
fischuu
GenomicTools.fileHandler:File Handlers for Genomic Data Analysis
A collection of I/O tools for handling the most commonly used genomic datafiles, like fasta/-q, bed, gff, gtf, ped/map and vcf.
Maintained by Daniel Fischer. Last updated 2 months ago.
4.48 score 4 scripts 2 dependentsbioc
scoreInvHap:Get inversion status in predefined regions
scoreInvHap can get the samples' inversion status of known inversions. scoreInvHap uses SNP data as input and requires the following information about the inversion: genotype frequencies in the different haplotypes, R2 between the region SNPs and inversion status and heterozygote genotypes in the reference. The package include this data for 21 inversions.
Maintained by Dolors Pelegri-Siso. Last updated 5 months ago.
4.34 score 11 scriptsbioc
MAGAR:MAGAR: R-package to compute methylation Quantitative Trait Loci (methQTL) from DNA methylation and genotyping data
"Methylation-Aware Genotype Association in R" (MAGAR) computes methQTL from DNA methylation and genotyping data from matched samples. MAGAR uses a linear modeling stragety to call CpGs/SNPs that are methQTLs. MAGAR accounts for the local correlation structure of CpGs.
Maintained by Michael Scherer. Last updated 5 months ago.
regressionepigeneticsdnamethylationsnpgeneticvariabilitymethylationarraymicroarraycpgislandmethylseqsequencingmrnamicroarraypreprocessingcopynumbervariationtwochannelimmunooncologydifferentialmethylationbatcheffectqualitycontroldataimportnetworkclusteringgraphandnetwork
4.30 score 3 scriptsbioc
GeneGeneInteR:Tools for Testing Gene-Gene Interaction at the Gene Level
The aim of this package is to propose several methods for testing gene-gene interaction in case-control association studies. Such a test can be done by aggregating SNP-SNP interaction tests performed at the SNP level (SSI) or by using gene-gene multidimensionnal methods (GGI) methods. The package also proposes tools for a graphic display of the results. <doi:10.18637/jss.v095.i12>.
Maintained by Mathieu Emily. Last updated 5 months ago.
genomewideassociationsnpgeneticsgeneticvariabilitycpp
4.30 score 2 scriptsbioc
CeTF:Coexpression for Transcription Factors using Regulatory Impact Factors and Partial Correlation and Information Theory analysis
This package provides the necessary functions for performing the Partial Correlation coefficient with Information Theory (PCIT) (Reverter and Chan 2008) and Regulatory Impact Factors (RIF) (Reverter et al. 2010) algorithm. The PCIT algorithm identifies meaningful correlations to define edges in a weighted network and can be applied to any correlation-based network including but not limited to gene co-expression networks, while the RIF algorithm identify critical Transcription Factors (TF) from gene expression data. These two algorithms when combined provide a very relevant layer of information for gene expression studies (Microarray, RNA-seq and single-cell RNA-seq data).
Maintained by Carlos Alberto Oliveira de Biagi Junior. Last updated 5 months ago.
sequencingrnaseqmicroarraygeneexpressiontranscriptionnormalizationdifferentialexpressionsinglecellnetworkregressionchipseqimmunooncologycoveragecpp
4.30 score 9 scripts
green-striped-gecko
dartR.sim:Computer Simulations of 'SNP' Data
Allows to simulate SNP data using genlight objects. For example, it is straight forward to simulate a simple drift scenario with exchange of individuals between two populations or create a new genlight object based on allele frequencies of an existing genlight object.
Maintained by Jose L. Mijangos. Last updated 1 years ago.
4.18 score 1 scripts 1 dependentsfischuu
hoardeR:Collect and Retrieve Annotation Data for Various Genomic Data Using Different Webservices
Cross-species identification of novel gene candidates using the NCBI web service is provided. Further, sets of miRNA target genes can be identified by using the targetscan.org API.
Maintained by Daniel Fischer. Last updated 12 months ago.
1 stars 3.70 score 6 scriptsbioc
DExMA:Differential Expression Meta-Analysis
performing all the steps of gene expression meta-analysis considering the possible existence of missing genes. It provides the necessary functions to be able to perform the different methods of gene expression meta-analysis. In addition, it contains functions to apply quality controls, download GEO datasets and show graphical representations of the results.
Maintained by Juan Antonio Villatoro-García. Last updated 5 months ago.
differentialexpressiongeneexpressionstatisticalmethodqualitycontrol
3.30 score 7 scripts
cmn92
gpcp:Genomic Prediction of Cross Performance
This function performs genomic prediction of cross performance using genotype and phenotype data. It processes data in several steps including loading necessary software, converting genotype data, processing phenotype data, fitting mixed models, and predicting cross performance based on weighted marker effects.
Maintained by Christine Nyaga. Last updated 6 months ago.
3.00 score 1 scriptsbioc
vtpnet:variant-transcription factor-phenotype networks
variant-transcription factor-phenotype networks, inspired by Maurano et al., Science (2012), PMID 22955828
Maintained by VJ Carey. Last updated 5 months ago.
2.30 score 1 scriptsgreen-striped-gecko
dartR.spatial:Applying Landscape Genomic Methods on 'SNP' and 'Silicodart' Data
Provides landscape genomic functions to analyse 'SNP' (single nuclear polymorphism) data, such as least cost path analysis and isolation by distance. Therefore each sample needs to have coordinate data attached (lat/lon) to be able to run most of the functions. 'dartR.spatial' is a package that belongs to the 'dartRverse' suit of packages and depends on 'dartR.base' and 'dartR.data'.
Maintained by Bernd Gruber. Last updated 1 years ago.
2.00 scoregreen-striped-gecko
dartR.captive:Analysing 'SNP' Data to Support Captive Breeding
Functions are provided that facilitate the analysis of SNP (single nucleotide polymorphism) data to answer questions regarding captive breeding and relatedness between individuals. 'dartR.captive' is part of the 'dartRverse' suit of packages. Gruber et al. (2018) <doi:10.1111/1755-0998.12745>. Mijangos et al. (2022) <doi:10.1111/2041-210X.13918>.
Maintained by Bernd Gruber. Last updated 1 months ago.
1 stars 2.00 score 3 scripts
cran
dartR.sexlinked:Analysing SNP Data to Identify Sex-Linked Markers
Identifies, filters and exports sex linked markers using 'SNP' (single nucleotide polymorphism) data. To install the other packages, we recommend to install the 'dartRverse' package, that supports the installation of all packages in the 'dartRverse'. If you want understand the applied rational to identify sexlinked markers and/or want to cite 'dartR.sexlinked', you find the information by typing citation('dartR.sexlinked') in the console.
Maintained by Diana Robledo-Ruiz. Last updated 9 months ago.
2.00 scoregreen-striped-gecko
dartR.popgen:Analysing 'SNP' and 'Silicodart' Data Generated by Genome-Wide Restriction Fragment Analysis
Facilitates the analysis of SNP (single nucleotide polymorphism) and silicodart (presence/absence) data. 'dartR.popgen' provides a suit of functions to analyse such data in a population genetics context. It provides several functions to calculate population genetic metrics and to study population structure. Quite a few functions need additional software to be able to run (gl.run.structure(), gl.blast(), gl.LDNe()). You find detailed description in the help pages how to download and link the packages so the function can run the software. 'dartR.popgen' is part of the the 'dartRverse' suit of packages. Gruber et al. (2018) <doi:10.1111/1755-0998.12745>. Mijangos et al. (2022) <doi:10.1111/2041-210X.13918>.
Maintained by Bernd Gruber. Last updated 9 months ago.
2.00 score 9 scripts
ubclxing
GWASbyCluster:Identifying Significant SNPs in Genome Wide Association Studies (GWAS) via Clustering
Identifying disease-associated significant SNPs using clustering approach. This package is implementation of method proposed in Xu et al (2019) <DOI:10.1038/s41598-019-50229-6>.
Maintained by Li Xing. Last updated 5 years ago.
1.00 score