bioconda / packages

Package Name Access Summary Updated
bioconductor-rhdf5 public This package provides an interface between HDF5 and R. HDF5's main features are the ability to store and access very large and/or complex datasets and a wide variety of metadata on mass storage (disk) through a completely portable file format. The rhdf5 package is thus suited for the exchange of large and/or complex datasets between R and other software package, and for letting R applications work on datasets that are larger than the available RAM. 2019-02-13
bioconductor-degreport public Creation of a HTML report of differential expression analyses of count data. It integrates some of the code mentioned in DESeq2 and edgeR vignettes, and report a ranked list of genes according to the fold changes mean and variability for each selected gene. 2019-01-28
r-msm public Functions for fitting continuous-time Markov and hidden Markov multi-state models to longitudinal data. Designed for processes observed at arbitrary times in continuous time (panel data) but some other observation schemes are supported. Both Markov transition rates and the hidden Markov output process can be modelled in terms of covariates, which may be constant or piecewise-constant in time. 2019-01-27
r-phylobase public Provides a base S4 class for comparative methods, incorporating one or more trees and trait data. 2019-01-27
r-polysat public A collection of tools to handle microsatellite data of any ploidy (and samples of mixed ploidy) where allele copy number is not known in partially heterozygous genotypes. 2019-01-27
r-rtfbs public Identifies and scores possible Transcription Factor Binding Sites and allows for FDR analysis and pruning. It supports splitting of sequences based on size or a specified GFF, grouping by G+C content, and specification of Markov model order. The heavy lifting is done in C while all results are made available via R. 2019-01-27
r-rphast public Provides an R interface to the 'PHAST'(<>) software (Phylogenetic Analysis with Space/Time Models). It can be used for many types of analysis in comparative and evolutionary genomics, such as estimating models of evolution from sequence data, scoring alignments for conservation or acceleration, and predicting elements based on conservation or custom phylogenetic hidden Markov models. It can also perform many basic operations on multiple sequence alignments and phylogenetic trees. 2019-01-27
bioconductor-biobase public Functions that are needed by many other packages or which replace R functions. 2019-01-17
bioconductor-singlecelltk public Run common single cell analysis directly through your browser including differential expression, downsampling analysis, and clustering. 2019-01-13
bioconductor-universalmotif public Allows for importing most common motif types into R for use by functions provided by other Bioconductor motif-related packages. Motifs can be exported into most major motif formats from various classes as defined by other Bioconductor packages. A suite of motif and sequence manipulation and analysis functions are included, including enrichment, comparison, P-value calculation, shuffling, trimming, higher-order motifs, and others. 2019-01-13
bioconductor-philr public PhILR is short for Phylogenetic Isometric Log-Ratio Transform. This package provides functions for the analysis of compositional data (e.g., data representing proportions of different variables/parts). Specifically this package allows analysis of compositional data where the parts can be related through a phylogenetic tree (as is common in microbiota survey data) and makes available the Isometric Log Ratio transform built from the phylogenetic tree and utilizing a weighted reference measure. 2019-01-13
bioconductor-post public Perform orthogonal projection of high dimensional data of a set, and statistical modeling of phenotye with projected vectors as predictor. 2019-01-13
bioconductor-linc public This package provides methods to compute co-expression networks of lincRNAs and protein-coding genes. Biological terms associated with the sets of protein-coding genes predict the biological contexts of lincRNAs according to the 'Guilty by Association' approach. 2019-01-13
bioconductor-platecore public Provides basic S4 data structures and routines for analyzing plate based flow cytometry data. 2019-01-13
bioconductor-cytoml public Uses platform-specific implemenations of the GatingML2.0 standard to exchange gated cytometry data with other software platforms. 2019-01-13
bioconductor-opencyto public This package is designed to facilitate the automated gating methods in sequential way to mimic the manual gating strategy. 2019-01-13
bioconductor-flowvs public Per-channel variance stabilization from a collection of flow cytometry samples by Bertlett test for homogeneity of variances. The approach is applicable to microarrays data as well. 2019-01-13
bioconductor-ibmq public integrated Bayesian Modeling of eQTL data 2019-01-13
bioconductor-lymphoseq public This R package analyzes high-throughput sequencing of T and B cell receptor complementarity determining region 3 (CDR3) sequences generated by Adaptive Biotechnologies' ImmunoSEQ assay. Its input comes from tab-separated value (.tsv) files exported from the ImmunoSEQ analyzer. 2019-01-13
bioconductor-frgepistasis public A Tool for Epistasis Analysis Based on Functional Regression Model 2019-01-13
bioconductor-fourcseq public FourCSeq is an R package dedicated to the analysis of (multiplexed) 4C sequencing data. The package provides a pipeline to detect specific interactions between DNA elements and identify differential interactions between conditions. The statistical analysis in R starts with individual bam files for each sample as inputs. To obtain these files, the package contains a python script (extdata/python/ to demultiplex libraries and trim off primer sequences. With a standard alignment software the required bam files can be then be generated. 2019-01-13
bioconductor-ping public Probabilistic inference of ChIP-Seq using an empirical Bayes mixture model approach. 2019-01-13
bioconductor-rqt public Despite the recent advances of modern GWAS methods, it still remains an important problem of addressing calculation an effect size and corresponding p-value for the whole gene rather than for single variant. The R- package rqt offers gene-level GWAS meta-analysis. For more information, see: "Gene-set association tests for next-generation sequencing data" by Lee et al (2016), Bioinformatics, 32(17), i611-i619, <doi:10.1093/bioinformatics/btw429>. 2019-01-13
bioconductor-fccac public An application of functional canonical correlation analysis to assess covariance of nucleic acid sequencing datasets such as chromatin immunoprecipitation followed by deep sequencing (ChIP-seq). The package can be used as well with other types of sequencing data such as neMeRIP-seq (PMID: 29489750) or with single cell RNA-seq or epigenome data provided in bigWig format. 2019-01-13
bioconductor-funchip public Preprocessing and smoothing of ChIP-Seq peaks and efficient implementation of the k-mean alignment algorithm to classify them. 2019-01-13
bioconductor-flowstats public Methods and functionality to analyse flow data that is beyond the basic infrastructure provided by the flowCore package. 2019-01-13
bioconductor-nethet public Package nethet is an implementation of statistical solid methodology enabling the analysis of network heterogeneity from high-dimensional data. It combines several implementations of recent statistical innovations useful for estimation and comparison of networks in a heterogeneous, high-dimensional setting. In particular, we provide code for formal two-sample testing in Gaussian graphical models (differential network and GGM-GSA; Stadler and Mukherjee, 2013, 2014) and make a novel network-based clustering algorithm available (mixed graphical lasso, Stadler and Mukherjee, 2013). 2019-01-13
bioconductor-narrowpeaks public The package applies a functional version of principal component analysis (FPCA) to: (1) Postprocess data in wiggle track format, commonly produced by generic ChIP-seq peak callers, by applying FPCA over a set of read-enriched regions (ChIP-seq peaks). This is done to study variability of the the peaks, or to shorten their genomic locations accounting for a given proportion of variation among the enrichment-score profiles. (2) Analyse differential variation between multiple ChIP-seq samples with replicates. The function 'narrowpeaksDiff' quantifies differences between the shapes, and uses Hotelling's T2 tests on the functional principal component scores to identify significant differences across conditions. An application of the package for Arabidopsis datasets is described in Mateos, Madrigal, et al. (2015) Genome Biology: 16:31. 2019-01-13
bioconductor-iwtomics public Implementation of the Interval-Wise Testing (IWT) for omics data. This inferential procedure tests for differences in "Omics" data between two groups of genomic regions (or between a group of genomic regions and a reference center of symmetry), and does not require fixing location and scale at the outset. 2019-01-13
bioconductor-proteoqc public This package creates an HTML format QC report for MS/MS-based proteomics data. The report is intended to allow the user to quickly assess the quality of proteomics data. 2019-01-13
bioconductor-pga public This package provides functions for construction of customized protein databases based on RNA-Seq data with/without genome guided, database searching, post-processing and report generation. This kind of customized protein database includes both the reference database (such as Refseq or ENSEMBL) and the novel peptide sequences form RNA-Seq data. 2019-01-13
bioconductor-shinytandem public This package provides a GUI interface for rTANDEM. The GUI is primarily designed to visualize rTANDEM result object or result xml files. But it will also provides an interface for creating parameter objects, launching searches or performing conversions between R objects and xml files. 2019-01-12
bioconductor-sapfinder public sapFinder is developed to automate (1) variation-associated database construction, (2) database searching, (3) post-processing, (4) HTML-based report generation in shotgun proteomics. 2019-01-12
bioconductor-ggtree public 'ggtree' extends the 'ggplot2' plotting system which implemented the grammar of graphics. 'ggtree' is designed for visualization and annotation of phylogenetic trees with their covariates and other associated data. 2019-01-12
bioconductor-prostar public This package provides a GUI interface for DAPAR. 2019-01-12
bioconductor-primirtss public A fast, convenient tool to identify the TSSs of miRNAs by integrating the data of H3K4me3 and Pol II as well as combining the conservation level and sequence feature, provided within both command-line and graphical interfaces, which achieves a better performance than the previous non-cell-specific methods on miRNA TSSs. 2019-01-12
bioconductor-rtandem public This package interfaces the tandem protein identification algorithm in R. Identification can be launched in the X!Tandem style, by using as sole parameter the path to a parameter file. But rTANDEM aslo provides extended syntax and functions to streamline launching analyses, as well as function to convert results, parameters and taxonomy to/from R. A related package, shinyTANDEM, provides visualization interface for result objects. 2019-01-12
r-ggrasp public Given a group of genomes and their relationship with each other, the package clusters the genomes and selects the most representative members of each cluster. Additional data can be provided to the prioritize certain genomes. The results can be printed out as a list or a new phylogeny with graphs of the trees and distance distributions also available. For detailed introduction see: Thomas H Clarke, Lauren M Brinkac, Granger Sutton, and Derrick E Fouts (2018), GGRaSP: a R-package for selecting representative genomes using Gaussian mixture models, Bioinformatics, bty300, <doi:10.1093/bioinformatics/bty300>. 2019-01-12
bioconductor-iterativebma public The iterative Bayesian Model Averaging (BMA) algorithm is a variable selection and classification algorithm with an application of classifying 2-class microarray samples, as described in Yeung, Bumgarner and Raftery (Bioinformatics 2005, 21: 2394-2402). 2019-01-12
r-tigger public Infers the V genotype of an individual from immunoglobulin (Ig) repertoire sequencing data (AIRR-Seq, Rep-Seq). Includes detection of any novel alleles. This information is then used to correct existing V allele calls from among the sample sequences. Citations: Gadala-Maria, et al (2015) <doi:10.1073/pnas.1417683112>. 2019-01-12
bioconductor-doqtl public DOQTL is a quantitative trait locus (QTL) mapping pipeline designed for Diversity Outbred mice and other multi-parent outbred populations. The package reads in data from genotyping arrays and perform haplotype reconstruction using a hidden Markov model (HMM). The haplotype probabilities from the HMM are then used to perform linkage mapping. When founder sequences are available, DOQTL can use the haplotype reconstructions to impute the founder sequences onto DO genomes and perform association mapping. 2019-01-12
bioconductor-vtpnet public variant-transcription factor-phenotype networks, inspired by Maurano et al., Science (2012), PMID 22955828 2019-01-12
bioconductor-gwascat public Represent and model data in the EMBL-EBI GWAS catalog. 2019-01-11
bioconductor-gqtlstats public computationally efficient analysis of eQTL, mQTL, dsQTL, etc. 2019-01-11
bioconductor-r3cpet public The package provides a method to infer the set of proteins that are more probably to work together to maintain chormatin interaction given a ChIA-PET experiment results. 2019-01-11
bioconductor-pi public Priority index or Pi is developed as a genomic-led target prioritisation system, with the focus on leveraging human genetic data to prioritise potential drug targets at the gene, pathway and network level. The long term goal is to use such information to enhance early-stage target validation. Based on evidence of disease association from genome-wide association studies (GWAS), this prioritisation system is able to generate evidence to support identification of the specific modulated genes (seed genes) that are responsible for the genetic association signal by utilising knowledge of linkage disequilibrium (co-inherited genetic variants), distance of associated variants from the gene, evidence of independent genetic association with gene expression in disease-relevant tissues, cell types and states, and evidence of physical interactions between disease-associated genetic variants and gene promoters based on genome-wide capture HiC-generated promoter interactomes in primary blood cell types. Seed genes are scored in an integrative way, quantifying the genetic influence. Scored seed genes are subsequently used as baits to rank seed genes plus additional (non-seed) genes; this is achieved by iteratively exploring the global connectivity of a gene interaction network. Genes with the highest priority are further used to identify/prioritise pathways that are significantly enriched with highly prioritised genes. Prioritised genes are also used to identify a gene network interconnecting highly prioritised genes and a minimal number of less prioritised genes (which act as linkers bringing together highly prioritised genes). 2019-01-11
r-xgr public The central goal of XGR by Fang et al. (2016) <doi:10.1186/s13073-016-0384-y> is to provide a data interpretation system necessary to do "big data" science. It is designed to make a user-defined gene or SNP list (or genomic regions) more interpretable by comprehensively utilising ontology annotations and interaction networks to reveal relationships and enhance opportunities for biological discovery. XGR is unique in supporting a broad range of ontologies (including knowledge of biological and molecular functions, pathways, diseases and phenotypes - in both human and mouse) and different types of networks (including functional, physical and pathway interactions). There are two core functionalities of XGR. The first is to provide basic infrastructures for easy access to built-in ontologies and networks. The second is to support data interpretations via 1) enrichment analysis using either built-in or custom ontologies, 2) similarity analysis for calculating semantic similarity between genes (or SNPs) based on their ontology annotation profiles, 3) network analysis for identification of gene networks given a query list of (significant) genes, SNPs or genomic regions, and 4) annotation analysis for interpreting genomic regions using co-localised functional genomic annotations (such as open chromatin, epigenetic marks, TF binding sites and genomic segments) and using nearby gene annotations (by ontologies). Together with its web app, XGR aims to provide a user-friendly tool for exploring genomic relations at the gene, SNP and genomic region level. 2019-01-11
bioconductor-phantasus public Phantasus is a web-application for visual and interactive gene expression analysis. Phantasus is based on Morpheus – a web-based software for heatmap visualisation and analysis, which was integrated with an R environment via OpenCPU API. Aside from basic visualization and filtering methods, R-based methods such as k-means clustering, principal component analysis or differential expression analysis with limma package are supported. 2019-01-11
bioconductor-dapar public This package contains a collection of functions for the visualisation and the statistical analysis of proteomic data. 2019-01-11
bioconductor-flowfit public This package estimate the proliferation of a cell population in cell-tracking dye studies. The package uses an R implementation of the Levenberg-Marquardt algorithm (minpack.lm) to fit a set of peaks (corresponding to different generations of cells) over the proliferation-tracking dye distribution in a FACS experiment. 2019-01-11
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