Showing 152 of total 152 results (show query)
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clusterProfiler:A universal enrichment tool for interpreting omics data
This package supports functional characteristics of both coding and non-coding genomics data for thousands of species with up-to-date gene annotation. It provides a univeral interface for gene functional annotation from a variety of sources and thus can be applied in diverse scenarios. It provides a tidy interface to access, manipulate, and visualize enrichment results to help users achieve efficient data interpretation. Datasets obtained from multiple treatments and time points can be analyzed and compared in a single run, easily revealing functional consensus and differences among distinct conditions.
Maintained by Guangchuang Yu. Last updated 4 months ago.
annotationclusteringgenesetenrichmentgokeggmultiplecomparisonpathwaysreactomevisualizationenrichment-analysisgsea
1.1k stars 17.03 score 11k scripts 48 dependentsbioc
ggtree:an R package for visualization of tree and annotation data
'ggtree' extends the 'ggplot2' plotting system which implemented the grammar of graphics. 'ggtree' is designed for visualization and annotation of phylogenetic trees and other tree-like structures with their annotation data.
Maintained by Guangchuang Yu. Last updated 5 months ago.
alignmentannotationclusteringdataimportmultiplesequencealignmentphylogeneticsreproducibleresearchsoftwarevisualizationannotationsggplot2phylogenetic-trees
871 stars 16.83 score 5.1k scripts 109 dependentsbioc
enrichplot:Visualization of Functional Enrichment Result
The 'enrichplot' package implements several visualization methods for interpreting functional enrichment results obtained from ORA or GSEA analysis. It is mainly designed to work with the 'clusterProfiler' package suite. All the visualization methods are developed based on 'ggplot2' graphics.
Maintained by Guangchuang Yu. Last updated 3 months ago.
annotationgenesetenrichmentgokeggpathwayssoftwarevisualizationenrichment-analysispathway-analysis
239 stars 15.71 score 3.1k scripts 58 dependentsyulab-smu
scatterpie:Scatter Pie Plot
Creates scatterpie plots, especially useful for plotting pies on a map.
Maintained by Guangchuang Yu. Last updated 3 months ago.
62 stars 13.60 score 820 scripts 68 dependentsbioc
ChIPseeker:ChIPseeker for ChIP peak Annotation, Comparison, and Visualization
This package implements functions to retrieve the nearest genes around the peak, annotate genomic region of the peak, statstical methods for estimate the significance of overlap among ChIP peak data sets, and incorporate GEO database for user to compare the own dataset with those deposited in database. The comparison can be used to infer cooperative regulation and thus can be used to generate hypotheses. Several visualization functions are implemented to summarize the coverage of the peak experiment, average profile and heatmap of peaks binding to TSS regions, genomic annotation, distance to TSS, and overlap of peaks or genes.
Maintained by Guangchuang Yu. Last updated 5 months ago.
annotationchipseqsoftwarevisualizationmultiplecomparisonatac-seqchip-seqcomparisonepigeneticsepigenomics
233 stars 13.05 score 1.6k scripts 5 dependentsgaospecial
ggVennDiagram:A 'ggplot2' Implement of Venn Diagram
Easy-to-use functions to generate 2-7 sets Venn or upset plot in publication quality. 'ggVennDiagram' plot Venn or upset using well-defined geometry dataset and 'ggplot2'. The shapes of 2-4 sets Venn use circles and ellipses, while the shapes of 4-7 sets Venn use irregular polygons (4 has both forms), which are developed and imported from another package 'venn', authored by Adrian Dusa. We provided internal functions to integrate shape data with user provided sets data, and calculated the geometry of every regions/intersections of them, then separately plot Venn in four components, set edges/labels, and region edges/labels. From version 1.0, it is possible to customize these components as you demand in ordinary 'ggplot2' grammar. From version 1.4.4, it supports unlimited number of sets, as it can draw a plain upset plot automatically when number of sets is more than 7.
Maintained by Chun-Hui Gao. Last updated 5 months ago.
set-operationsupsetupsetplotvenn-diagramvenn-plot
292 stars 12.31 score 1.3k scripts 4 dependentsbioc
ReactomePA:Reactome Pathway Analysis
This package provides functions for pathway analysis based on REACTOME pathway database. It implements enrichment analysis, gene set enrichment analysis and several functions for visualization. This package is not affiliated with the Reactome team.
Maintained by Guangchuang Yu. Last updated 5 months ago.
pathwaysvisualizationannotationmultiplecomparisongenesetenrichmentreactomeenrichment-analysisreactome-pathway-analysisreactomepa
40 stars 12.25 score 1.5k scripts 7 dependentsyulab-smu
aplot:Decorate a 'ggplot' with Associated Information
For many times, we are not just aligning plots as what 'cowplot' and 'patchwork' did. Users would like to align associated information that requires axes to be exactly matched in subplots, e.g. hierarchical clustering with a heatmap. Inspired by the 'Method 2' in 'ggtree' (G Yu (2018) <doi:10.1093/molbev/msy194>), 'aplot' provides utilities to aligns associated subplots to a main plot at different sides (left, right, top and bottom) with axes exactly matched.
Maintained by Guangchuang Yu. Last updated 1 months ago.
103 stars 12.25 score 520 scripts 118 dependentsguangchuangyu
hexSticker:Create Hexagon Sticker in R
Helper functions for creating reproducible hexagon sticker purely in R.
Maintained by Guangchuang Yu. Last updated 2 months ago.
ggplot2hexagon-stickerlogostickersvisualization
773 stars 11.79 score 1.3k scripts 8 dependentsguangchuangyu
ggimage:Use Image in 'ggplot2'
Supports image files and graphic objects to be visualized in 'ggplot2' graphic system.
Maintained by Guangchuang Yu. Last updated 1 years ago.
172 stars 11.12 score 2.4k scripts 20 dependentsbioc
singleCellTK:Comprehensive and Interactive Analysis of Single Cell RNA-Seq Data
The Single Cell Toolkit (SCTK) in the singleCellTK package provides an interface to popular tools for importing, quality control, analysis, and visualization of single cell RNA-seq data. SCTK allows users to seamlessly integrate tools from various packages at different stages of the analysis workflow. A general "a la carte" workflow gives users the ability access to multiple methods for data importing, calculation of general QC metrics, doublet detection, ambient RNA estimation and removal, filtering, normalization, batch correction or integration, dimensionality reduction, 2-D embedding, clustering, marker detection, differential expression, cell type labeling, pathway analysis, and data exporting. Curated workflows can be used to run Seurat and Celda. Streamlined quality control can be performed on the command line using the SCTK-QC pipeline. Users can analyze their data using commands in the R console or by using an interactive Shiny Graphical User Interface (GUI). Specific analyses or entire workflows can be summarized and shared with comprehensive HTML reports generated by Rmarkdown. Additional documentation and vignettes can be found at camplab.net/sctk.
Maintained by Joshua David Campbell. Last updated 1 months ago.
singlecellgeneexpressiondifferentialexpressionalignmentclusteringimmunooncologybatcheffectnormalizationqualitycontroldataimportgui
182 stars 10.17 score 252 scriptsyulab-smu
ggbreak:Set Axis Break for 'ggplot2'
An implementation of scale functions for setting axis breaks of a 'gg' plot (S Xu (2021) <doi:10.3389/fgene.2021.774846>).
Maintained by Guangchuang Yu. Last updated 2 months ago.
axis-breakcut-plotggbreakggplot2wrap-plot
137 stars 9.81 score 956 scripts 1 dependentsbioc
MicrobiotaProcess:A comprehensive R package for managing and analyzing microbiome and other ecological data within the tidy framework
MicrobiotaProcess is an R package for analysis, visualization and biomarker discovery of microbial datasets. It introduces MPSE class, this make it more interoperable with the existing computing ecosystem. Moreover, it introduces a tidy microbiome data structure paradigm and analysis grammar. It provides a wide variety of microbiome data analysis procedures under the unified and common framework (tidy-like framework).
Maintained by Shuangbin Xu. Last updated 5 months ago.
visualizationmicrobiomesoftwaremultiplecomparisonfeatureextractionmicrobiome-analysismicrobiome-data
186 stars 9.70 score 126 scripts 1 dependentsbioc
pcaExplorer:Interactive Visualization of RNA-seq Data Using a Principal Components Approach
This package provides functionality for interactive visualization of RNA-seq datasets based on Principal Components Analysis. The methods provided allow for quick information extraction and effective data exploration. A Shiny application encapsulates the whole analysis.
Maintained by Federico Marini. Last updated 3 months ago.
immunooncologyvisualizationrnaseqdimensionreductionprincipalcomponentqualitycontrolguireportwritingshinyappsbioconductorprincipal-componentsreproducible-researchrna-seq-analysisrna-seq-datashinytranscriptomeuser-friendly
56 stars 9.63 score 180 scriptsbioc
ggtreeExtra:An R Package To Add Geometric Layers On Circular Or Other Layout Tree Of "ggtree"
'ggtreeExtra' extends the method for mapping and visualizing associated data on phylogenetic tree using 'ggtree'. These associated data can be presented on the external panels to circular layout, fan layout, or other rectangular layout tree built by 'ggtree' with the grammar of 'ggplot2'.
Maintained by Shuangbin Xu. Last updated 5 months ago.
softwarevisualizationphylogeneticsannotation
91 stars 9.55 score 426 scripts 2 dependentsbioc
ggmsa:Plot Multiple Sequence Alignment using 'ggplot2'
A visual exploration tool for multiple sequence alignment and associated data. Supports MSA of DNA, RNA, and protein sequences using 'ggplot2'. Multiple sequence alignment can easily be combined with other 'ggplot2' plots, such as phylogenetic tree Visualized by 'ggtree', boxplot, genome map and so on. More features: visualization of sequence logos, sequence bundles, RNA secondary structures and detection of sequence recombinations.
Maintained by Guangchuang Yu. Last updated 3 months ago.
softwarevisualizationalignmentannotationmultiplesequencealignment
210 stars 9.35 score 196 scripts 2 dependentsbioc
EWCE:Expression Weighted Celltype Enrichment
Used to determine which cell types are enriched within gene lists. The package provides tools for testing enrichments within simple gene lists (such as human disease associated genes) and those resulting from differential expression studies. The package does not depend upon any particular Single Cell Transcriptome dataset and user defined datasets can be loaded in and used in the analyses.
Maintained by Alan Murphy. Last updated 2 months ago.
geneexpressiontranscriptiondifferentialexpressiongenesetenrichmentgeneticsmicroarraymrnamicroarrayonechannelrnaseqbiomedicalinformaticsproteomicsvisualizationfunctionalgenomicssinglecelldeconvolutionsingle-cellsingle-cell-rna-seqtranscriptomics
56 stars 9.29 score 99 scriptsstscl
gdverse:Analysis of Spatial Stratified Heterogeneity
Detecting spatial associations via spatial stratified heterogeneity, accounting for spatial dependencies, interpretability, complex interactions, and robust stratification. In addition, it supports the spatial stratified heterogeneity family described in Lv et al. (2025)<doi:10.1111/tgis.70032>.
Maintained by Wenbo Lv. Last updated 20 hours ago.
geographical-detectorgeoinformaticsgeospatial-analysisspatial-statisticsspatial-stratified-heterogeneitycpp
34 stars 9.13 score 41 scripts 2 dependentsbioc
miaViz:Microbiome Analysis Plotting and Visualization
The miaViz package implements functions to visualize TreeSummarizedExperiment objects especially in the context of microbiome analysis. Part of the mia family of R/Bioconductor packages.
Maintained by Tuomas Borman. Last updated 15 days ago.
microbiomesoftwarevisualizationbioconductormicrobiome-analysisplotting
10 stars 8.67 score 81 scripts 1 dependentsbioc
lefser:R implementation of the LEfSE method for microbiome biomarker discovery
lefser is the R implementation of the popular microbiome biomarker discovery too, LEfSe. It uses the Kruskal-Wallis test, Wilcoxon-Rank Sum test, and Linear Discriminant Analysis to find biomarkers from two-level classes (and optional sub-classes).
Maintained by Sehyun Oh. Last updated 1 months ago.
softwaresequencingdifferentialexpressionmicrobiomestatisticalmethodclassificationbioconductor-packager01ca230551
56 stars 8.44 score 56 scriptsbioc
GeneTonic:Enjoy Analyzing And Integrating The Results From Differential Expression Analysis And Functional Enrichment Analysis
This package provides functionality to combine the existing pieces of the transcriptome data and results, making it easier to generate insightful observations and hypothesis. Its usage is made easy with a Shiny application, combining the benefits of interactivity and reproducibility e.g. by capturing the features and gene sets of interest highlighted during the live session, and creating an HTML report as an artifact where text, code, and output coexist. Using the GeneTonicList as a standardized container for all the required components, it is possible to simplify the generation of multiple visualizations and summaries.
Maintained by Federico Marini. Last updated 3 months ago.
guigeneexpressionsoftwaretranscriptiontranscriptomicsvisualizationdifferentialexpressionpathwaysreportwritinggenesetenrichmentannotationgoshinyappsbioconductorbioconductor-packagedata-explorationdata-visualizationfunctional-enrichment-analysisgene-expressionpathway-analysisreproducible-researchrna-seq-analysisrna-seq-datashinytranscriptomeuser-friendly
77 stars 8.28 score 37 scripts 1 dependentsbioc
FLAMES:FLAMES: Full Length Analysis of Mutations and Splicing in long read RNA-seq data
Semi-supervised isoform detection and annotation from both bulk and single-cell long read RNA-seq data. Flames provides automated pipelines for analysing isoforms, as well as intermediate functions for manual execution.
Maintained by Changqing Wang. Last updated 3 days ago.
rnaseqsinglecelltranscriptomicsdataimportdifferentialsplicingalternativesplicinggeneexpressionlongreadzlibcurlbzip2xz-utilscpp
33 stars 8.04 score 12 scriptsbioc
philr:Phylogenetic partitioning based ILR transform for metagenomics data
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.
Maintained by Justin Silverman. Last updated 5 months ago.
immunooncologysequencingmicrobiomemetagenomicssoftware
19 stars 7.99 score 95 scriptsbioc
orthogene:Interspecies gene mapping
`orthogene` is an R package for easy mapping of orthologous genes across hundreds of species. It pulls up-to-date gene ortholog mappings across **700+ organisms**. It also provides various utility functions to aggregate/expand common objects (e.g. data.frames, gene expression matrices, lists) using **1:1**, **many:1**, **1:many** or **many:many** gene mappings, both within- and between-species.
Maintained by Brian Schilder. Last updated 5 months ago.
geneticscomparativegenomicspreprocessingphylogeneticstranscriptomicsgeneexpressionanimal-modelsbioconductorbioconductor-packagebioinformaticsbiomedicinecomparative-genomicsevolutionary-biologygenesgenomicsontologiestranslational-research
43 stars 7.86 score 31 scripts 2 dependentsbioc
debrowser:Interactive Differential Expresion Analysis Browser
Bioinformatics platform containing interactive plots and tables for differential gene and region expression studies. Allows visualizing expression data much more deeply in an interactive and faster way. By changing the parameters, users can easily discover different parts of the data that like never have been done before. Manually creating and looking these plots takes time. With DEBrowser users can prepare plots without writing any code. Differential expression, PCA and clustering analysis are made on site and the results are shown in various plots such as scatter, bar, box, volcano, ma plots and Heatmaps.
Maintained by Alper Kucukural. Last updated 5 months ago.
sequencingchipseqrnaseqdifferentialexpressiongeneexpressionclusteringimmunooncology
61 stars 7.80 score 65 scriptsbioc
ggsc:Visualizing Single Cell and Spatial Transcriptomics
Useful functions to visualize single cell and spatial data. It supports visualizing 'Seurat', 'SingleCellExperiment' and 'SpatialExperiment' objects through grammar of graphics syntax implemented in 'ggplot2'.
Maintained by Guangchuang Yu. Last updated 5 months ago.
dimensionreductiongeneexpressionsinglecellsoftwarespatialtranscriptomicsvisualizationopenblascppopenmp
47 stars 7.59 score 18 scriptsbioc
EpiCompare:Comparison, Benchmarking & QC of Epigenomic Datasets
EpiCompare is used to compare and analyse epigenetic datasets for quality control and benchmarking purposes. The package outputs an HTML report consisting of three sections: (1. General metrics) Metrics on peaks (percentage of blacklisted and non-standard peaks, and peak widths) and fragments (duplication rate) of samples, (2. Peak overlap) Percentage and statistical significance of overlapping and non-overlapping peaks. Also includes upset plot and (3. Functional annotation) functional annotation (ChromHMM, ChIPseeker and enrichment analysis) of peaks. Also includes peak enrichment around TSS.
Maintained by Hiranyamaya Dash. Last updated 2 months ago.
epigeneticsgeneticsqualitycontrolchipseqmultiplecomparisonfunctionalgenomicsatacseqdnaseseqbenchmarkbenchmarkingbioconductorbioconductor-packagecomparisonhtmlinteractive-reporting
15 stars 7.49 score 46 scriptskharchenkolab
numbat:Haplotype-Aware CNV Analysis from scRNA-Seq
A computational method that infers copy number variations (CNVs) in cancer scRNA-seq data and reconstructs the tumor phylogeny. 'numbat' integrates signals from gene expression, allelic ratio, and population haplotype structures to accurately infer allele-specific CNVs in single cells and reconstruct their lineage relationship. 'numbat' can be used to: 1. detect allele-specific copy number variations from single-cells; 2. differentiate tumor versus normal cells in the tumor microenvironment; 3. infer the clonal architecture and evolutionary history of profiled tumors. 'numbat' does not require tumor/normal-paired DNA or genotype data, but operates solely on the donor scRNA-data data (for example, 10x Cell Ranger output). Additional examples and documentations are available at <https://kharchenkolab.github.io/numbat/>. For details on the method please see Gao et al. Nature Biotechnology (2022) <doi:10.1038/s41587-022-01468-y>.
Maintained by Teng Gao. Last updated 15 days ago.
cancer-genomicscnv-detectionlineage-tracingphylogenysingle-cellsingle-cell-analysissingle-cell-rna-seqspatial-transcriptomicscpp
180 stars 7.48 score 120 scriptsropensci
rsat:Dealing with Multiplatform Satellite Images
Downloading, customizing, and processing time series of satellite images for a region of interest. 'rsat' functions allow a unified access to multispectral images from Landsat, MODIS and Sentinel repositories. 'rsat' also offers capabilities for customizing satellite images, such as tile mosaicking, image cropping and new variables computation. Finally, 'rsat' covers the processing, including cloud masking, compositing and gap-filling/smoothing time series of images (Militino et al., 2018 <doi:10.3390/rs10030398> and Militino et al., 2019 <doi:10.1109/TGRS.2019.2904193>).
Maintained by Unai Pérez - Goya. Last updated 12 months ago.
54 stars 7.45 score 52 scriptsbioc
signatureSearch:Environment for Gene Expression Searching Combined with Functional Enrichment Analysis
This package implements algorithms and data structures for performing gene expression signature (GES) searches, and subsequently interpreting the results functionally with specialized enrichment methods.
Maintained by Brendan Gongol. Last updated 5 months ago.
softwaregeneexpressiongokeggnetworkenrichmentsequencingcoveragedifferentialexpressioncpp
18 stars 7.20 score 74 scripts 1 dependentsbioc
meshes:MeSH Enrichment and Semantic analyses
MeSH (Medical Subject Headings) is the NLM controlled vocabulary used to manually index articles for MEDLINE/PubMed. MeSH terms were associated by Entrez Gene ID by three methods, gendoo, gene2pubmed and RBBH. This association is fundamental for enrichment and semantic analyses. meshes supports enrichment analysis (over-representation and gene set enrichment analysis) of gene list or whole expression profile. The semantic comparisons of MeSH terms provide quantitative ways to compute similarities between genes and gene groups. meshes implemented five methods proposed by Resnik, Schlicker, Jiang, Lin and Wang respectively and supports more than 70 species.
Maintained by Guangchuang Yu. Last updated 5 months ago.
annotationclusteringmultiplecomparisonsoftwareenrichment-analysismedical-subject-headingssemantic-similarity
12 stars 7.19 score 43 scriptsbioc
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 scriptsloelschlaeger
fHMM:Fitting Hidden Markov Models to Financial Data
Fitting (hierarchical) hidden Markov models to financial data via maximum likelihood estimation. See Oelschläger, L. and Adam, T. "Detecting Bearish and Bullish Markets in Financial Time Series Using Hierarchical Hidden Markov Models" (2021, Statistical Modelling) <doi:10.1177/1471082X211034048> for a reference on the method. A user guide is provided by the accompanying software paper "fHMM: Hidden Markov Models for Financial Time Series in R", Oelschläger, L., Adam, T., and Michels, R. (2024, Journal of Statistical Software) <doi:10.18637/jss.v109.i09>.
Maintained by Lennart Oelschläger. Last updated 11 days ago.
financehidden-markov-modelscppopenmp
17 stars 7.04 score 5 scriptsguangchuangyu
ggtangle:Draw Network with Data
Extends the 'ggplot2' plotting system to support network visualization. Inspired by the 'Method 1' in 'ggtree' (G Yu (2018) <doi:10.1093/molbev/msy194>), 'ggtangle' is designed to work with network associated data.
Maintained by Guangchuang Yu. Last updated 4 months ago.
1 stars 6.87 score 3 scripts 59 dependentsbioc
treeclimbR:An algorithm to find optimal signal levels in a tree
The arrangement of hypotheses in a hierarchical structure appears in many research fields and often indicates different resolutions at which data can be viewed. This raises the question of which resolution level the signal should best be interpreted on. treeclimbR provides a flexible method to select optimal resolution levels (potentially different levels in different parts of the tree), rather than cutting the tree at an arbitrary level. treeclimbR uses a tuning parameter to generate candidate resolutions and from these selects the optimal one.
Maintained by Charlotte Soneson. Last updated 3 months ago.
statisticalmethodcellbasedassays
20 stars 6.86 score 45 scriptskbhoehn
dowser:B Cell Receptor Phylogenetics Toolkit
Provides a set of functions for inferring, visualizing, and analyzing B cell phylogenetic trees. Provides methods to 1) reconstruct unmutated ancestral sequences, 2) build B cell phylogenetic trees using multiple methods, 3) visualize trees with metadata at the tips, 4) reconstruct intermediate sequences, 5) detect biased ancestor-descendant relationships among metadata types Workflow examples available at documentation site (see URL). Citations: Hoehn et al (2022) <doi:10.1371/journal.pcbi.1009885>, Hoehn et al (2021) <doi:10.1101/2021.01.06.425648>.
Maintained by Kenneth Hoehn. Last updated 3 months ago.
6.81 score 84 scriptsjunjunlab
ClusterGVis:One-Step to Cluster and Visualize Gene Expression Data
Streamlining the clustering and visualization of time-series gene expression data from RNA-Seq experiments, this tool supports fuzzy c-means and k-means clustering algorithms. It is compatible with outputs from widely-used packages such as 'Seurat', 'Monocle', and 'WGCNA', enabling seamless downstream visualization and analysis. See Lokesh Kumar and Matthias E Futschik (2007) <doi:10.6026/97320630002005> for more details.
Maintained by Jun Zhang. Last updated 24 days ago.
sequencingclusterprofilersummarizedexperimentmfuzzcomplexheatmapgene-clusteringgene-expressionvisualization
281 stars 6.80 score 30 scriptsbioc
MicrobiomeProfiler:An R/shiny package for microbiome functional enrichment analysis
This is an R/shiny package to perform functional enrichment analysis for microbiome data. This package was based on clusterProfiler. Moreover, MicrobiomeProfiler support KEGG enrichment analysis, COG enrichment analysis, Microbe-Disease association enrichment analysis, Metabo-Pathway analysis.
Maintained by Guangchuang Yu. Last updated 5 months ago.
microbiomesoftwarevisualizationkegg
38 stars 6.80 score 22 scriptsbioc
ideal:Interactive Differential Expression AnaLysis
This package provides functions for an Interactive Differential Expression AnaLysis of RNA-sequencing datasets, to extract quickly and effectively information downstream the step of differential expression. A Shiny application encapsulates the whole package. Support for reproducibility of the whole analysis is provided by means of a template report which gets automatically compiled and can be stored/shared.
Maintained by Federico Marini. Last updated 3 months ago.
immunooncologygeneexpressiondifferentialexpressionrnaseqsequencingvisualizationqualitycontrolguigenesetenrichmentreportwritingshinyappsbioconductordifferential-expressionreproducible-researchrna-seqrna-seq-analysisshinyuser-friendly
29 stars 6.78 score 5 scriptsjoshwlambert
DAISIEprep:Extracts Phylogenetic Island Community Data from Phylogenetic Trees
Extracts colonisation and branching times of island species to be used for analysis in the R package 'DAISIE'. It uses phylogenetic and endemicity data to extract the separate island colonists and store them.
Maintained by Joshua W. Lambert. Last updated 2 months ago.
data-scienceisland-biogeographyphylogenetics
6 stars 6.78 score 24 scriptsxjsun1221
tinyarray:Expression Data Analysis and Visualization
The Gene Expression Omnibus (<https://www.ncbi.nlm.nih.gov/geo/>) and The Cancer Genome Atlas (<https://portal.gdc.cancer.gov/>) are widely used medical public databases. Our platform integrates routine analysis and visualization tools for expression data to provide concise and intuitive data analysis and presentation.
Maintained by Xiaojie Sun. Last updated 10 months ago.
91 stars 6.67 score 138 scriptsjunjunlab
GseaVis:Implement for 'GSEA' Enrichment Visualization
Mark your interesting genes on plot and support more parameters to handle your own gene set enrichment analysis plot.
Maintained by Jun Zhang. Last updated 3 months ago.
146 stars 6.60 score 54 scriptsbioc
pathlinkR:Analyze and interpret RNA-Seq results
pathlinkR is an R package designed to facilitate analysis of RNA-Seq results. Specifically, our aim with pathlinkR was to provide a number of tools which take a list of DE genes and perform different analyses on them, aiding with the interpretation of results. Functions are included to perform pathway enrichment, with muliplte databases supported, and tools for visualizing these results. Genes can also be used to create and plot protein-protein interaction networks, all from inside of R.
Maintained by Travis Blimkie. Last updated 3 months ago.
genesetenrichmentnetworkpathwaysreactomernaseqnetworkenrichmentbioinformaticsnetworkspathway-enrichment-analysisvisualization
28 stars 6.59 score 2 scriptsbioc
MoonlightR:Identify oncogenes and tumor suppressor genes from omics data
Motivation: The understanding of cancer mechanism requires the identification of genes playing a role in the development of the pathology and the characterization of their role (notably oncogenes and tumor suppressors). Results: We present an R/bioconductor package called MoonlightR which returns a list of candidate driver genes for specific cancer types on the basis of TCGA expression data. The method first infers gene regulatory networks and then carries out a functional enrichment analysis (FEA) (implementing an upstream regulator analysis, URA) to score the importance of well-known biological processes with respect to the studied cancer type. Eventually, by means of random forests, MoonlightR predicts two specific roles for the candidate driver genes: i) tumor suppressor genes (TSGs) and ii) oncogenes (OCGs). As a consequence, this methodology does not only identify genes playing a dual role (e.g. TSG in one cancer type and OCG in another) but also helps in elucidating the biological processes underlying their specific roles. In particular, MoonlightR can be used to discover OCGs and TSGs in the same cancer type. This may help in answering the question whether some genes change role between early stages (I, II) and late stages (III, IV) in breast cancer. In the future, this analysis could be useful to determine the causes of different resistances to chemotherapeutic treatments.
Maintained by Matteo Tiberti. Last updated 5 months ago.
dnamethylationdifferentialmethylationgeneregulationgeneexpressionmethylationarraydifferentialexpressionpathwaysnetworksurvivalgenesetenrichmentnetworkenrichment
17 stars 6.57 scorebioc
Statial:A package to identify changes in cell state relative to spatial associations
Statial is a suite of functions for identifying changes in cell state. The functionality provided by Statial provides robust quantification of cell type localisation which are invariant to changes in tissue structure. In addition to this Statial uncovers changes in marker expression associated with varying levels of localisation. These features can be used to explore how the structure and function of different cell types may be altered by the agents they are surrounded with.
Maintained by Farhan Ameen. Last updated 5 months ago.
singlecellspatialclassificationsingle-cell
5 stars 6.49 score 23 scriptsyulab-smu
tidydr:Unify Dimensionality Reduction Results
Dimensionality reduction (DR) is widely used in many domain for analyzing and visualizing high-dimensional data. 'tidydr' provides uniform output and is compatible with multiple methods, including 'prcomp', 'mds', 'Rtsne'. etc.
Maintained by Guangchuang Yu. Last updated 1 years ago.
14 stars 6.47 score 71 scripts 1 dependentsbioc
Moonlight2R:Identify oncogenes and tumor suppressor genes from omics data
The understanding of cancer mechanism requires the identification of genes playing a role in the development of the pathology and the characterization of their role (notably oncogenes and tumor suppressors). We present an updated version of the R/bioconductor package called MoonlightR, namely Moonlight2R, which returns a list of candidate driver genes for specific cancer types on the basis of omics data integration. The Moonlight framework contains a primary layer where gene expression data and information about biological processes are integrated to predict genes called oncogenic mediators, divided into putative tumor suppressors and putative oncogenes. This is done through functional enrichment analyses, gene regulatory networks and upstream regulator analyses to score the importance of well-known biological processes with respect to the studied cancer type. By evaluating the effect of the oncogenic mediators on biological processes or through random forests, the primary layer predicts two putative roles for the oncogenic mediators: i) tumor suppressor genes (TSGs) and ii) oncogenes (OCGs). As gene expression data alone is not enough to explain the deregulation of the genes, a second layer of evidence is needed. We have automated the integration of a secondary mutational layer through new functionalities in Moonlight2R. These functionalities analyze mutations in the cancer cohort and classifies these into driver and passenger mutations using the driver mutation prediction tool, CScape-somatic. Those oncogenic mediators with at least one driver mutation are retained as the driver genes. As a consequence, this methodology does not only identify genes playing a dual role (e.g. TSG in one cancer type and OCG in another) but also helps in elucidating the biological processes underlying their specific roles. In particular, Moonlight2R can be used to discover OCGs and TSGs in the same cancer type. This may for instance help in answering the question whether some genes change role between early stages (I, II) and late stages (III, IV). In the future, this analysis could be useful to determine the causes of different resistances to chemotherapeutic treatments. An additional mechanistic layer evaluates if there are mutations affecting the protein stability of the transcription factors (TFs) of the TSGs and OCGs, as that may have an effect on the expression of the genes.
Maintained by Matteo Tiberti. Last updated 2 months ago.
dnamethylationdifferentialmethylationgeneregulationgeneexpressionmethylationarraydifferentialexpressionpathwaysnetworksurvivalgenesetenrichmentnetworkenrichment
5 stars 6.41 score 43 scriptsbioc
tanggle:Visualization of Phylogenetic Networks
Offers functions for plotting split (or implicit) networks (unrooted, undirected) and explicit networks (rooted, directed) with reticulations extending. 'ggtree' and using functions from 'ape' and 'phangorn'. It extends the 'ggtree' package [@Yu2017] to allow the visualization of phylogenetic networks using the 'ggplot2' syntax. It offers an alternative to the plot functions already available in 'ape' Paradis and Schliep (2019) <doi:10.1093/bioinformatics/bty633> and 'phangorn' Schliep (2011) <doi:10.1093/bioinformatics/btq706>.
Maintained by Klaus Schliep. Last updated 5 months ago.
softwarevisualizationphylogeneticsalignmentclusteringmultiplesequencealignmentdataimport
11 stars 6.40 score 38 scriptsbioc
CBNplot:plot bayesian network inferred from gene expression data based on enrichment analysis results
This package provides the visualization of bayesian network inferred from gene expression data. The networks are based on enrichment analysis results inferred from packages including clusterProfiler and ReactomePA. The networks between pathways and genes inside the pathways can be inferred and visualized.
Maintained by Noriaki Sato. Last updated 5 months ago.
visualizationbayesiangeneexpressionnetworkinferencepathwaysreactomenetworknetworkenrichmentgenesetenrichment
64 stars 6.28 score 9 scriptsbioc
iSEEtree:Interactive visualisation for microbiome data
iSEEtree is an extension of iSEE for the TreeSummarizedExperiment data container. It provides interactive panel designs to explore hierarchical datasets, such as the microbiome and cell lines.
Maintained by Giulio Benedetti. Last updated 15 days ago.
softwarevisualizationmicrobiomeguishinyappsdataimportshiny-appsvisualisation
3 stars 6.28 score 5 scriptsbioc
iNETgrate:Integrates DNA methylation data with gene expression in a single gene network
The iNETgrate package provides functions to build a correlation network in which nodes are genes. DNA methylation and gene expression data are integrated to define the connections between genes. This network is used to identify modules (clusters) of genes. The biological information in each of the resulting modules is represented by an eigengene. These biological signatures can be used as features e.g., for classification of patients into risk categories. The resulting biological signatures are very robust and give a holistic view of the underlying molecular changes.
Maintained by Habil Zare. Last updated 5 months ago.
geneexpressionrnaseqdnamethylationnetworkinferencenetworkgraphandnetworkbiomedicalinformaticssystemsbiologytranscriptomicsclassificationclusteringdimensionreductionprincipalcomponentmrnamicroarraynormalizationgenepredictionkeggsurvivalcore-services
74 stars 6.21 score 1 scriptsbioc
esATAC:An Easy-to-use Systematic pipeline for ATACseq data analysis
This package provides a framework and complete preset pipeline for quantification and analysis of ATAC-seq Reads. It covers raw sequencing reads preprocessing (FASTQ files), reads alignment (Rbowtie2), aligned reads file operations (SAM, BAM, and BED files), peak calling (F-seq), genome annotations (Motif, GO, SNP analysis) and quality control report. The package is managed by dataflow graph. It is easy for user to pass variables seamlessly between processes and understand the workflow. Users can process FASTQ files through end-to-end preset pipeline which produces a pretty HTML report for quality control and preliminary statistical results, or customize workflow starting from any intermediate stages with esATAC functions easily and flexibly.
Maintained by Zheng Wei. Last updated 5 months ago.
immunooncologysequencingdnaseqqualitycontrolalignmentpreprocessingcoverageatacseqdnaseseqatac-seqbioconductorpipelinecppopenjdk
23 stars 6.11 score 3 scriptsrevbayes
RevGadgets:Visualization and Post-Processing of 'RevBayes' Analyses
Processes and visualizes the output of complex phylogenetic analyses from the 'RevBayes' phylogenetic graphical modeling software.
Maintained by Carrie Tribble. Last updated 1 years ago.
13 stars 6.09 score 208 scriptsbioc
cogeqc:Systematic quality checks on comparative genomics analyses
cogeqc aims to facilitate systematic quality checks on standard comparative genomics analyses to help researchers detect issues and select the most suitable parameters for each data set. cogeqc can be used to asses: i. genome assembly and annotation quality with BUSCOs and comparisons of statistics with publicly available genomes on the NCBI; ii. orthogroup inference using a protein domain-based approach and; iii. synteny detection using synteny network properties. There are also data visualization functions to explore QC summary statistics.
Maintained by Fabrício Almeida-Silva. Last updated 5 months ago.
softwaregenomeassemblycomparativegenomicsfunctionalgenomicsphylogeneticsqualitycontrolnetworkcomparative-genomicsevolutionary-genomics
10 stars 6.08 score 20 scriptscardiomoon
interpretCI:Estimate the Confidence Interval and Interpret Step by Step
Estimate confidence intervals for mean, proportion, mean difference for unpaired and paired samples and proportion difference. Plot the confidence intervals. Generate documents explaining the statistical result step by step.
Maintained by Keon-Woong Moon. Last updated 3 years ago.
4 stars 6.03 score 49 scriptsganglilab
genekitr:Gene Analysis Toolkit
Provides features for searching, converting, analyzing, plotting, and exporting data effortlessly by inputting feature IDs. Enables easy retrieval of feature information, conversion of ID types, gene enrichment analysis, publication-level figures, group interaction plotting, and result export in one Excel file for seamless sharing and communication.
Maintained by Yunze Liu. Last updated 3 months ago.
enrichment-analysisgeneid-converterplotting
56 stars 6.00 score 24 scripts 1 dependentsbioc
mosdef:MOSt frequently used and useful Differential Expression Functions
This package provides functionality to run a number of tasks in the differential expression analysis workflow. This encompasses the most widely used steps, from running various enrichment analysis tools with a unified interface to creating plots and beautifying table components linking to external websites and databases. This streamlines the generation of comprehensive analysis reports.
Maintained by Federico Marini. Last updated 3 months ago.
geneexpressionsoftwaretranscriptiontranscriptomicsdifferentialexpressionvisualizationreportwritinggenesetenrichmentgo
5.98 score 4 dependentsxiaoluo-boy
ggheatmap:Plot Heatmap
The flexibility and excellence of 'ggplot2' is unquestionable, so many drawing tools basically need 'ggplot2' as the operating object. In order to develop a heatmap drawing system based on ggplot2, we developed this tool, mainly to solve the heatmap puzzle problem and the flexible connection between the heatmap and the 'ggplot2' object. The advantages of this tool are as follows: 1. More flexible label settings; 2. Realize the linkage of heatmap and 'ggplot2' drawing system, which is helpful for operations such as puzzles; 3. Simple and easy to operate; 4. Optimization of clustering tree visualization.
Maintained by Baiwei Luo. Last updated 2 years ago.
87 stars 5.91 score 63 scripts 1 dependentsbioc
miRspongeR:Identification and analysis of miRNA sponge regulation
This package provides several functions to explore miRNA sponge (also called ceRNA or miRNA decoy) regulation from putative miRNA-target interactions or/and transcriptomics data (including bulk, single-cell and spatial gene expression data). It provides eight popular methods for identifying miRNA sponge interactions, and an integrative method to integrate miRNA sponge interactions from different methods, as well as the functions to validate miRNA sponge interactions, and infer miRNA sponge modules, conduct enrichment analysis of miRNA sponge modules, and conduct survival analysis of miRNA sponge modules. By using a sample control variable strategy, it provides a function to infer sample-specific miRNA sponge interactions. In terms of sample-specific miRNA sponge interactions, it implements three similarity methods to construct sample-sample correlation network.
Maintained by Junpeng Zhang. Last updated 5 months ago.
geneexpressionbiomedicalinformaticsnetworkenrichmentsurvivalmicroarraysoftwaresinglecellspatialrnaseqcernamirnasponge
5 stars 5.88 score 8 scriptsbioc
scBubbletree:Quantitative visual exploration of scRNA-seq data
scBubbletree is a quantitative method for the visual exploration of scRNA-seq data, preserving key biological properties such as local and global cell distances and cell density distributions across samples. It effectively resolves overplotting and enables the visualization of diverse cell attributes from multiomic single-cell experiments. Additionally, scBubbletree is user-friendly and integrates seamlessly with popular scRNA-seq analysis tools, facilitating comprehensive and intuitive data interpretation.
Maintained by Simo Kitanovski. Last updated 5 months ago.
visualizationclusteringsinglecelltranscriptomicsrnaseqbig-databigdatascrna-seqscrna-seq-analysisvisualvisual-exploration
6 stars 5.82 score 8 scriptsbioc
CCPlotR:Plots For Visualising Cell-Cell Interactions
CCPlotR is an R package for visualising results from tools that predict cell-cell interactions from single-cell RNA-seq data. These plots are generic and can be used to visualise results from multiple tools such as Liana, CellPhoneDB, NATMI etc.
Maintained by Sarah Ennis. Last updated 5 months ago.
singlecellnetworkvisualizationcellbiologysystemsbiology
43 stars 5.81 score 7 scriptsbioc
ggtreeSpace:Visualizing Phylomorphospaces using 'ggtree'
This package is a comprehensive visualization tool specifically designed for exploring phylomorphospace. It not only simplifies the process of generating phylomorphospace, but also enhances it with the capability to add graphic layers to the plot with grammar of graphics to create fully annotated phylomorphospaces. It also provide some utilities to help interpret evolutionary patterns.
Maintained by Guangchuang Yu. Last updated 5 months ago.
annotationvisualizationphylogeneticssoftware
5 stars 5.80 score 12 scriptsbioc
bioCancer:Interactive Multi-Omics Cancers Data Visualization and Analysis
This package is a Shiny App to visualize and analyse interactively Multi-Assays of Cancer Genomic Data.
Maintained by Karim Mezhoud. Last updated 5 months ago.
guidatarepresentationnetworkmultiplecomparisonpathwaysreactomevisualizationgeneexpressiongenetargetanalysisbiocancer-interfacecancercancer-studiesrmarkdown
20 stars 5.78 score 7 scriptslimengbinggz
ddtlcm:Latent Class Analysis with Dirichlet Diffusion Tree Process Prior
Implements a Bayesian algorithm for overcoming weak separation in Bayesian latent class analysis. Reference: Li et al. (2023) <arXiv:2306.04700>.
Maintained by Mengbing Li. Last updated 8 months ago.
6 stars 5.73 score 8 scriptsbioc
CaMutQC:An R Package for Comprehensive Filtration and Selection of Cancer Somatic Mutations
CaMutQC is able to filter false positive mutations generated due to technical issues, as well as to select candidate cancer mutations through a series of well-structured functions by labeling mutations with various flags. And a detailed and vivid filter report will be offered after completing a whole filtration or selection section. Also, CaMutQC integrates serveral methods and gene panels for Tumor Mutational Burden (TMB) estimation.
Maintained by Xin Wang. Last updated 5 months ago.
softwarequalitycontrolgenetargetcancer-genomicssomatic-mutations
7 stars 5.72 score 1 scriptstiago-simoes
EvoPhylo:Pre- And Postprocessing of Morphological Data from Relaxed Clock Bayesian Phylogenetics
Performs automated morphological character partitioning for phylogenetic analyses and analyze macroevolutionary parameter outputs from clock (time-calibrated) Bayesian inference analyses, following concepts introduced by Simões and Pierce (2021) <doi:10.1038/s41559-021-01532-x>.
Maintained by Tiago Simoes. Last updated 2 years ago.
4 stars 5.66 score 19 scriptsthermostats
RVA:RNAseq Visualization Automation
Automate downstream visualization & pathway analysis in RNAseq analysis. 'RVA' is a collection of functions that efficiently visualize RNAseq differential expression analysis result from summary statistics tables. It also utilize the Fisher's exact test to evaluate gene set or pathway enrichment in a convenient and efficient manner.
Maintained by Xingpeng Li. Last updated 3 years ago.
9 stars 5.65 score 6 scriptsbioc
GDCRNATools:GDCRNATools: an R/Bioconductor package for integrative analysis of lncRNA, mRNA, and miRNA data in GDC
This is an easy-to-use package for downloading, organizing, and integrative analyzing RNA expression data in GDC with an emphasis on deciphering the lncRNA-mRNA related ceRNA regulatory network in cancer. Three databases of lncRNA-miRNA interactions including spongeScan, starBase, and miRcode, as well as three databases of mRNA-miRNA interactions including miRTarBase, starBase, and miRcode are incorporated into the package for ceRNAs network construction. limma, edgeR, and DESeq2 can be used to identify differentially expressed genes/miRNAs. Functional enrichment analyses including GO, KEGG, and DO can be performed based on the clusterProfiler and DO packages. Both univariate CoxPH and KM survival analyses of multiple genes can be implemented in the package. Besides some routine visualization functions such as volcano plot, bar plot, and KM plot, a few simply shiny apps are developed to facilitate visualization of results on a local webpage.
Maintained by Ruidong Li. Last updated 5 months ago.
immunooncologygeneexpressiondifferentialexpressiongeneregulationgenetargetnetworkinferencesurvivalvisualizationgenesetenrichmentnetworkenrichmentnetworkrnaseqgokegg
5.64 score 44 scriptsbioc
CEMiTool:Co-expression Modules identification Tool
The CEMiTool package unifies the discovery and the analysis of coexpression gene modules in a fully automatic manner, while providing a user-friendly html report with high quality graphs. Our tool evaluates if modules contain genes that are over-represented by specific pathways or that are altered in a specific sample group. Additionally, CEMiTool is able to integrate transcriptomic data with interactome information, identifying the potential hubs on each network.
Maintained by Helder Nakaya. Last updated 5 months ago.
geneexpressiontranscriptomicsgraphandnetworkmrnamicroarrayrnaseqnetworknetworkenrichmentpathwaysimmunooncology
5.58 score 38 scriptsbioc
miRSM:Inferring miRNA sponge modules in heterogeneous data
The package aims to identify miRNA sponge or ceRNA modules in heterogeneous data. It provides several functions to study miRNA sponge modules at single-sample and multi-sample levels, including popular methods for inferring gene modules (candidate miRNA sponge or ceRNA modules), and two functions to identify miRNA sponge modules at single-sample and multi-sample levels, as well as several functions to conduct modular analysis of miRNA sponge modules.
Maintained by Junpeng Zhang. Last updated 5 months ago.
geneexpressionbiomedicalinformaticsclusteringgenesetenrichmentmicroarraysoftwaregeneregulationgenetargetcernamirnamirna-spongemirna-targetsmodulesopenjdk
4 stars 5.51 score 5 scriptsyulab-smu
fanyi:Translate Words or Sentences via Online Translators
Useful functions to translate text for multiple languages using online translators. For example, by translating error messages and descriptive analysis results into a language familiar to the user, it enables a better understanding of the information, thereby reducing the barriers caused by language. It offers several helper functions to query gene information to help interpretation of interested genes (e.g., marker genes, differential expression genes), and provides utilities to translate 'ggplot' graphics. This package is not affiliated with any of the online translators. The developers do not take responsibility for the invoice it incurs when using this package, especially for exceeding the free quota.
Maintained by Guangchuang Yu. Last updated 5 months ago.
52 stars 5.49 score 10 scriptsbioc
enrichViewNet:From functional enrichment results to biological networks
This package enables the visualization of functional enrichment results as network graphs. First the package enables the visualization of enrichment results, in a format corresponding to the one generated by gprofiler2, as a customizable Cytoscape network. In those networks, both gene datasets (GO terms/pathways/protein complexes) and genes associated to the datasets are represented as nodes. While the edges connect each gene to its dataset(s). The package also provides the option to create enrichment maps from functional enrichment results. Enrichment maps enable the visualization of enriched terms into a network with edges connecting overlapping genes.
Maintained by Astrid Deschênes. Last updated 5 months ago.
biologicalquestionsoftwarenetworknetworkenrichmentgocystocapefunctional-enrichment
5 stars 5.48 score 6 scriptsbioc
scDotPlot:Cluster a Single-cell RNA-seq Dot Plot
Dot plots of single-cell RNA-seq data allow for an examination of the relationships between cell groupings (e.g. clusters) and marker gene expression. The scDotPlot package offers a unified approach to perform a hierarchical clustering analysis and add annotations to the columns and/or rows of a scRNA-seq dot plot. It works with SingleCellExperiment and Seurat objects as well as data frames.
Maintained by Benjamin I Laufer. Last updated 14 days ago.
softwarevisualizationdifferentialexpressiongeneexpressiontranscriptionrnaseqsinglecellsequencingclustering
7 stars 5.45 score 2 scriptsloelschlaeger
RprobitB:Bayesian Probit Choice Modeling
Bayes estimation of probit choice models, both in the cross-sectional and panel setting. The package can analyze binary, multivariate, ordered, and ranked choices, as well as heterogeneity of choice behavior among deciders. The main functionality includes model fitting via Markov chain Monte Carlo m ethods, tools for convergence diagnostic, choice data simulation, in-sample and out-of-sample choice prediction, and model selection using information criteria and Bayes factors. The latent class model extension facilitates preference-based decider classification, where the number of latent classes can be inferred via the Dirichlet process or a weight-based updating heuristic. This allows for flexible modeling of choice behavior without the need to impose structural constraints. For a reference on the method see Oelschlaeger and Bauer (2021) <https://trid.trb.org/view/1759753>.
Maintained by Lennart Oelschläger. Last updated 6 months ago.
bayesdiscrete-choiceprobitopenblascppopenmp
4 stars 5.45 score 1 scriptsjaipizgon
NeuralSens:Sensitivity Analysis of Neural Networks
Analysis functions to quantify inputs importance in neural network models. Functions are available for calculating and plotting the inputs importance and obtaining the activation function of each neuron layer and its derivatives. The importance of a given input is defined as the distribution of the derivatives of the output with respect to that input in each training data point <doi:10.18637/jss.v102.i07>.
Maintained by Jaime Pizarroso Gonzalo. Last updated 6 months ago.
15 stars 5.43 score 24 scriptsloelschlaeger
oeli:Utilities for Developing Data Science Software
Some general helper functions that I (and maybe others) find useful when developing data science software.
Maintained by Lennart Oelschläger. Last updated 4 months ago.
2 stars 5.38 score 1 scripts 4 dependentsbioc
GeDi:Defining and visualizing the distances between different genesets
The package provides different distances measurements to calculate the difference between genesets. Based on these scores the genesets are clustered and visualized as graph. This is all presented in an interactive Shiny application for easy usage.
Maintained by Annekathrin Nedwed. Last updated 5 months ago.
guigenesetenrichmentsoftwaretranscriptionrnaseqvisualizationclusteringpathwaysreportwritinggokeggreactomeshinyapps
1 stars 5.36 score 22 scriptsaftonsteps
ggalignment:Plots 'D&D'-Style Alignment Charts
'D&D' alignment charts show 9 boxes with values for good through evil and values for chaotic through lawful. This package easily creates these alignment charts from user-provided image paths and alignment values.
Maintained by Afton Coombs. Last updated 1 months ago.
10 stars 5.30 score 6 scriptsbioc
sitePath:Phylogeny-based sequence clustering with site polymorphism
Using site polymorphism is one of the ways to cluster DNA/protein sequences but it is possible for the sequences with the same polymorphism on a single site to be genetically distant. This package is aimed at clustering sequences using site polymorphism and their corresponding phylogenetic trees. By considering their location on the tree, only the structurally adjacent sequences will be clustered. However, the adjacent sequences may not necessarily have the same polymorphism. So a branch-and-bound like algorithm is used to minimize the entropy representing the purity of site polymorphism of each cluster.
Maintained by Chengyang Ji. Last updated 5 months ago.
alignmentmultiplesequencealignmentphylogeneticssnpsoftwaremutationcpp
9 stars 5.26 score 9 scriptsyulab-smu
shinyTempSignal:Explore Temporal and Other Phylogenetic Signals
Sequences sampled at different time points can be used to infer molecular phylogenies on natural time scales, but if the sequences records inaccurate sampling times, that are not the actual sampling times, then it will affect the molecular phylogenetic analysis. This shiny application helps exploring temporal characteristics of the evolutionary trees through linear regression analysis and with the ability to identify and remove incorrect labels. The method was extended to support exploring other phylogenetic signals under strict and relaxed models.
Maintained by Guangchuang Yu. Last updated 1 years ago.
molecular-clockphylogeneticsshiny-app
9 stars 5.26 score 7 scriptsbjoelle
FossilSim:Simulation and Plots for Fossil and Taxonomy Data
Simulating and plotting taxonomy and fossil data on phylogenetic trees under mechanistic models of speciation, preservation and sampling.
Maintained by Joelle Barido-Sottani. Last updated 6 months ago.
1 stars 5.24 score 65 scripts 1 dependentsjiang-junyao
CACIMAR:cross-species analysis of cell identities, markers and regulations
A toolkit to perform cross-species analysis based on scRNA-seq data. CACIMAR contains 5 main features. (1) identify Markers in each cluster. (2) Cell type annotaion (3) identify conserved markers. (4) identify conserved cell types. (5) identify conserved modules of regulatory networks.
Maintained by Junyao Jiang. Last updated 22 hours ago.
cross-species-analysisscrna-seq
12 stars 5.23 score 6 scriptsbioc
BulkSignalR:Infer Ligand-Receptor Interactions from bulk expression (transcriptomics/proteomics) data, or spatial transcriptomics
Inference of ligand-receptor (LR) interactions from bulk expression (transcriptomics/proteomics) data, or spatial transcriptomics. BulkSignalR bases its inferences on the LRdb database included in our other package, SingleCellSignalR available from Bioconductor. It relies on a statistical model that is specific to bulk data sets. Different visualization and data summary functions are proposed to help navigating prediction results.
Maintained by Jean-Philippe Villemin. Last updated 3 months ago.
networkrnaseqsoftwareproteomicstranscriptomicsnetworkinferencespatial
5.22 score 15 scriptsropengov
rogtemplate:'pkgdown' Template for 'rOpenGov' Packages
This is a private template for use by core rOpenGov packages. Please don’t use for your own code.
Maintained by Diego Hernangómez. Last updated 15 days ago.
ropengovtemplategithub-actionspkgdownpkgdown-template
2 stars 5.16 score 3 scriptsyuanchao-xu
gfer:Green Finance and Environmental Risk
Focuses on data collecting, analyzing and visualization in green finance and environmental risk research and analysis. Main function includes environmental data collecting from official websites such as MEP (Ministry of Environmental Protection of China, <https://www.mee.gov.cn>), water related projects identification and environmental data visualization.
Maintained by Yuanchao Xu. Last updated 15 days ago.
corporate-social-responsibilitycsrdata-analysisdata-scrapingenvironmental-riskgreen-financestock-data
8 stars 5.11 score 16 scriptsstscl
cisp:A Correlation Indicator Based on Spatial Patterns
Use the spatial association marginal contributions derived from spatial stratified heterogeneity to capture the degree of correlation between spatial patterns.
Maintained by Wenbo Lv. Last updated 2 months ago.
associationcorrelationgeoinformaticsspatial-patterns
5 stars 5.10 score 2 scriptskfarleigh
PopGenHelpR:Streamline Population Genomic and Genetic Analyses
Estimate commonly used population genomic statistics and generate publication quality figures. 'PopGenHelpR' uses vcf, 'geno' (012), and csv files to generate output.
Maintained by Keaka Farleigh. Last updated 8 months ago.
diversityfstheterozygosityinterpolationneispopulation-geneticspopulation-genomicsprivate-allelessnmfstructurevcf
3 stars 5.02 score 14 scriptsbioc
broadSeq:broadSeq : for streamlined exploration of RNA-seq data
This package helps user to do easily RNA-seq data analysis with multiple methods (usually which needs many different input formats). Here the user will provid the expression data as a SummarizedExperiment object and will get results from different methods. It will help user to quickly evaluate different methods.
Maintained by Rishi Das Roy. Last updated 5 months ago.
geneexpressiondifferentialexpressionrnaseqtranscriptomicssequencingcoveragegenesetenrichmentgo
4 stars 5.00 score 7 scriptsalphaprime7
normfluodbf:Cleans and Normalizes FLUOstar DBF and DAT Files from 'Liposome' Flux Assays
Cleans and Normalizes FLUOstar DBF and DAT Files obtained from liposome flux assays. Users should verify extended usage of the package on files from other assay types.
Maintained by Tingwei Adeck. Last updated 5 months ago.
1 stars 4.98 score 12 scriptsbioc
epiregulon.extra:Companion package to epiregulon with additional plotting, differential and graph functions
Gene regulatory networks model the underlying gene regulation hierarchies that drive gene expression and observed phenotypes. Epiregulon infers TF activity in single cells by constructing a gene regulatory network (regulons). This is achieved through integration of scATAC-seq and scRNA-seq data and incorporation of public bulk TF ChIP-seq data. Links between regulatory elements and their target genes are established by computing correlations between chromatin accessibility and gene expressions.
Maintained by Xiaosai Yao. Last updated 15 days ago.
generegulationnetworkgeneexpressiontranscriptionchiponchipdifferentialexpressiongenetargetnormalizationgraphandnetwork
4.95 score 10 scriptsbioc
PanomiR:Detection of miRNAs that regulate interacting groups of pathways
PanomiR is a package to detect miRNAs that target groups of pathways from gene expression data. This package provides functionality for generating pathway activity profiles, determining differentially activated pathways between user-specified conditions, determining clusters of pathways via the PCxN package, and generating miRNAs targeting clusters of pathways. These function can be used separately or sequentially to analyze RNA-Seq data.
Maintained by Pourya Naderi. Last updated 5 months ago.
geneexpressiongenesetenrichmentgenetargetmirnapathways
3 stars 4.89 score 13 scriptsbioc
gINTomics:Multi-Omics data integration
gINTomics is an R package for Multi-Omics data integration and visualization. gINTomics is designed to detect the association between the expression of a target and of its regulators, taking into account also their genomics modifications such as Copy Number Variations (CNV) and methylation. What is more, gINTomics allows integration results visualization via a Shiny-based interactive app.
Maintained by Angelo Velle. Last updated 5 months ago.
geneexpressionrnaseqmicroarrayvisualizationcopynumbervariationgenetargetquarto
3 stars 4.78 score 3 scriptsandersgs
harrietr:Wrangle Phylogenetic Distance Matrices and Other Utilities
Harriet was Charles Darwin's pet tortoise (possibly). 'harrietr' implements some function to manipulate distance matrices and phylogenetic trees to make it easier to plot with 'ggplot2' and to manipulate using 'tidyverse' tools.
Maintained by Anders Gonçalves da Silva. Last updated 7 years ago.
bioinformaticsevolutionphylogenetics
12 stars 4.78 score 50 scriptsbioc
EnrichDO:a Global Weighted Model for Disease Ontology Enrichment Analysis
To implement disease ontology (DO) enrichment analysis, this package is designed and presents a double weighted model based on the latest annotations of the human genome with DO terms, by integrating the DO graph topology on a global scale. This package exhibits high accuracy that it can identify more specific DO terms, which alleviates the over enriched problem. The package includes various statistical models and visualization schemes for discovering the associations between genes and diseases from biological big data.
Maintained by Hongyu Fu. Last updated 4 months ago.
annotationvisualizationgenesetenrichmentsoftware
4.74 score 9 scriptsloelschlaeger
ao:Alternating Optimization
Alternating optimization is an iterative procedure that optimizes a function by alternately performing restricted optimization over individual parameter subsets. Instead of tackling joint optimization directly, it breaks the problem down into simpler sub-problems. This approach can make optimization feasible when joint optimization is too difficult.
Maintained by Lennart Oelschläger. Last updated 8 months ago.
2 stars 4.70 score 2 scriptsloelschlaeger
optimizeR:Unified Framework for Numerical Optimizers
Provides a unified object-oriented framework for numerical optimizers in R. Allows for both minimization and maximization with any optimizer, optimization over more than one function argument, measuring of computation time, setting a time limit for long optimization tasks.
Maintained by Lennart Oelschläger. Last updated 7 days ago.
4 stars 4.62 score 7 scripts 1 dependentsbioc
CARDspa:Spatially Informed Cell Type Deconvolution for Spatial Transcriptomics
CARD is a reference-based deconvolution method that estimates cell type composition in spatial transcriptomics based on cell type specific expression information obtained from a reference scRNA-seq data. A key feature of CARD is its ability to accommodate spatial correlation in the cell type composition across tissue locations, enabling accurate and spatially informed cell type deconvolution as well as refined spatial map construction. CARD relies on an efficient optimization algorithm for constrained maximum likelihood estimation and is scalable to spatial transcriptomics with tens of thousands of spatial locations and tens of thousands of genes.
Maintained by Jing Fu. Last updated 7 days ago.
spatialsinglecelltranscriptomicsvisualizationopenblascppopenmp
4.60 score 3 scriptsausgis
localsp:Local Indicator of Stratified Power
Implements a local indicator of stratified power to analyze local spatial stratified association and demonstrate how spatial stratified association changes spatially and in local regions, as outlined in Hu et al. (2024) <doi:10.1080/13658816.2024.2437811>.
Maintained by Wenbo Lv. Last updated 2 months ago.
2 stars 4.60 scoredavidcarayon
IDEATools:Individual and Group Farm Sustainability Assessments using the IDEA4 Method
Collection of tools to automate the processing of data collected though the IDEA4 method (see Zahm et al. (2018) <doi:10.1051/cagri/2019004> ). Starting from the original data collecting files this packages provides functions to compute IDEA indicators, draw modern and aesthetic plots, and produce a wide range of reporting materials.
Maintained by David Carayon. Last updated 10 months ago.
1 stars 4.59 score 26 scriptsbioc
Pigengene:Infers biological signatures from gene expression data
Pigengene package provides an efficient way to infer biological signatures from gene expression profiles. The signatures are independent from the underlying platform, e.g., the input can be microarray or RNA Seq data. It can even infer the signatures using data from one platform, and evaluate them on the other. Pigengene identifies the modules (clusters) of highly coexpressed genes using coexpression network analysis, summarizes the biological information of each module in an eigengene, learns a Bayesian network that models the probabilistic dependencies between modules, and builds a decision tree based on the expression of eigengenes.
Maintained by Habil Zare. Last updated 5 months ago.
geneexpressionrnaseqnetworkinferencenetworkgraphandnetworkbiomedicalinformaticssystemsbiologytranscriptomicsclassificationclusteringdecisiontreedimensionreductionprincipalcomponentmicroarraynormalizationimmunooncology
4.56 score 10 scripts 1 dependentsbioc
treekoR:Cytometry Cluster Hierarchy and Cellular-to-phenotype Associations
treekoR is a novel framework that aims to utilise the hierarchical nature of single cell cytometry data to find robust and interpretable associations between cell subsets and patient clinical end points. These associations are aimed to recapitulate the nested proportions prevalent in workflows inovlving manual gating, which are often overlooked in workflows using automatic clustering to identify cell populations. We developed treekoR to: Derive a hierarchical tree structure of cell clusters; quantify a cell types as a proportion relative to all cells in a sample (%total), and, as the proportion relative to a parent population (%parent); perform significance testing using the calculated proportions; and provide an interactive html visualisation to help highlight key results.
Maintained by Adam Chan. Last updated 5 months ago.
clusteringdifferentialexpressionflowcytometryimmunooncologymassspectrometrysinglecellsoftwarestatisticalmethodvisualization
4.56 score 12 scripts 1 dependentstacazares
SeedMatchR:Find Matches to Canonical SiRNA Seeds in Genomic Features
On-target gene knockdown using siRNA ideally results from binding fully complementary regions in mRNA transcripts to induce cleavage. Off-target siRNA gene knockdown can occur through several modes, one being a seed-mediated mechanism mimicking miRNA gene regulation. Seed-mediated off-target effects occur when the ~8 nucleotides at the 5’ end of the guide strand, called a seed region, bind the 3’ untranslated regions of mRNA, causing reduced translation. Experiments using siRNA knockdown paired with RNA-seq can be used to detect siRNA sequences with potential off-target effects driven by the seed region. 'SeedMatchR' provides tools for exploring and detecting potential seed-mediated off-target effects of siRNA in RNA-seq experiments. 'SeedMatchR' is designed to extend current differential expression analysis tools, such as 'DESeq2', by annotating results with predicted seed matches. Using publicly available data, we demonstrate the ability of 'SeedMatchR' to detect cumulative changes in differential gene expression attributed to siRNA seed regions.
Maintained by Tareian Cazares. Last updated 1 years ago.
deseq2-analysismirnarna-seqsirnatranscriptomics
7 stars 4.54 score 7 scriptsbioc
TDbasedUFEadv:Advanced package of tensor decomposition based unsupervised feature extraction
This is an advanced version of TDbasedUFE, which is a comprehensive package to perform Tensor decomposition based unsupervised feature extraction. In contrast to TDbasedUFE which can perform simple the feature selection and the multiomics analyses, this package can perform more complicated and advanced features, but they are not so popularly required. Only users who require more specific features can make use of its functionality.
Maintained by Y-h. Taguchi. Last updated 5 months ago.
geneexpressionfeatureextractionmethylationarraysinglecellsoftwarebioconductor-packagebioinformaticstensor-decomposition
4.48 score 4 scriptscore-bioinformatics
bulkAnalyseR:Interactive Shiny App for Bulk Sequencing Data
Given an expression matrix from a bulk sequencing experiment, pre-processes it and creates a shiny app for interactive data analysis and visualisation. The app contains quality checks, differential expression analysis, volcano and cross plots, enrichment analysis and gene regulatory network inference, and can be customised to contain more panels by the user.
Maintained by Ilias Moutsopoulos. Last updated 1 years ago.
27 stars 4.47 score 11 scriptsyuanlonghu
immcp:Poly-Pharmacology Toolkit for Traditional Chinese Medicine Research
Toolkit for Poly-pharmacology Research of Traditional Chinese Medicine. Based on the biological descriptors and drug-disease interaction networks, it can analyze the potential poly-pharmacological mechanisms of Traditional Chinese Medicine and be used for drug-repositioning in Traditional Chinese Medicine.
Maintained by Yuanlong Hu. Last updated 2 years ago.
network-pharmacologypolypharmacologytraditional-chinese-medicine
5 stars 4.40 score 2 scriptsbioc
goSorensen:Statistical inference based on the Sorensen-Dice dissimilarity and the Gene Ontology (GO)
This package implements inferential methods to compare gene lists in terms of their biological meaning as expressed in the GO. The compared gene lists are characterized by cross-tabulation frequency tables of enriched GO items. Dissimilarity between gene lists is evaluated using the Sorensen-Dice index. The fundamental guiding principle is that two gene lists are taken as similar if they share a great proportion of common enriched GO items.
Maintained by Pablo Flores. Last updated 15 days ago.
annotationgogenesetenrichmentsoftwaremicroarraypathwaysgeneexpressionmultiplecomparisongraphandnetworkreactomeclusteringkegg
4.38 score 12 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 scriptsyulab-smu
aplotExtra:Creating Composite Plots using 'aplot'
Many complex plots are actually composite plots, such as 'oncoplot', 'funkyheatmap', 'upsetplot', etc. We can produce subplots using 'ggplot2' and combine them to create composite plots using 'aplot'. In this way, it is easy to customize these complex plots, by adding, deleting or modifying subplots in the final plot. This package provides a set of utilities to help users to create subplots and complex plots.
Maintained by Guangchuang Yu. Last updated 4 months ago.
8 stars 4.20 scorerdinnager
phyf:Phylogenetic Flow Objects for Easy Manipulation and Modelling of Data on Phylogenetic Trees and Graphs
The {phyf} package implements a tibble and vctrs based object for storing phylogenetic trees along with data. It is fast and flexible and directly produces data structures useful for phylogenetic modelling in the {fibre} package.
Maintained by Russell Dinnage. Last updated 7 months ago.
1 stars 4.20 score 53 scripts 1 dependentsbioc
ggtreeDendro:Drawing 'dendrogram' using 'ggtree'
Offers a set of 'autoplot' methods to visualize tree-like structures (e.g., hierarchical clustering and classification/regression trees) using 'ggtree'. You can adjust graphical parameters using grammar of graphic syntax and integrate external data to the tree.
Maintained by Guangchuang Yu. Last updated 5 months ago.
clusteringclassificationdecisiontreephylogeneticsvisualization
4.18 score 10 scriptsbioc
MIRit:Integrate microRNA and gene expression to decipher pathway complexity
MIRit is an R package that provides several methods for investigating the relationships between miRNAs and genes in different biological conditions. In particular, MIRit allows to explore the functions of dysregulated miRNAs, and makes it possible to identify miRNA-gene regulatory axes that control biological pathways, thus enabling the users to unveil the complexity of miRNA biology. MIRit is an all-in-one framework that aims to help researchers in all the central aspects of an integrative miRNA-mRNA analyses, from differential expression analysis to network characterization.
Maintained by Jacopo Ronchi. Last updated 15 days ago.
softwaregeneregulationnetworkenrichmentnetworkinferenceepigeneticsfunctionalgenomicssystemsbiologynetworkpathwaysgeneexpressiondifferentialexpressionmirnamirna-mrna-interactionmirna-seqmirnaseq-analysiscpp
1 stars 4.18 score 2 scriptsbioc
ReducedExperiment:Containers and tools for dimensionally-reduced -omics representations
Provides SummarizedExperiment-like containers for storing and manipulating dimensionally-reduced assay data. The ReducedExperiment classes allow users to simultaneously manipulate their original dataset and their decomposed data, in addition to other method-specific outputs like feature loadings. Implements utilities and specialised classes for the application of stabilised independent component analysis (sICA) and weighted gene correlation network analysis (WGCNA).
Maintained by Jack Gisby. Last updated 3 months ago.
geneexpressioninfrastructuredatarepresentationsoftwaredimensionreductionnetworkbioconductor-packagebioinformaticsdimensionality-reduction
3 stars 4.13 score 8 scriptsbioc
profileplyr:Visualization and annotation of read signal over genomic ranges with profileplyr
Quick and straightforward visualization of read signal over genomic intervals is key for generating hypotheses from sequencing data sets (e.g. ChIP-seq, ATAC-seq, bisulfite/methyl-seq). Many tools both inside and outside of R and Bioconductor are available to explore these types of data, and they typically start with a bigWig or BAM file and end with some representation of the signal (e.g. heatmap). profileplyr leverages many Bioconductor tools to allow for both flexibility and additional functionality in workflows that end with visualization of the read signal.
Maintained by Tom Carroll. Last updated 5 months ago.
chipseqdataimportsequencingchiponchipcoverage
4.03 score 54 scriptskharchenkolab
scistreer:Maximum-Likelihood Perfect Phylogeny Inference at Scale
Fast maximum-likelihood phylogeny inference from noisy single-cell data using the 'ScisTree' algorithm by Yufeng Wu (2019) <doi:10.1093/bioinformatics/btz676>. 'scistreer' provides an 'R' interface and improves speed via 'Rcpp' and 'RcppParallel', making the method applicable to massive single-cell datasets (>10,000 cells).
Maintained by Teng Gao. Last updated 2 years ago.
evolutionphylogeneticssingle-cellcpp
7 stars 4.02 score 2 scripts 1 dependentsbioc
systemPipeTools:Tools for data visualization
systemPipeTools package extends the widely used systemPipeR (SPR) workflow environment with an enhanced toolkit for data visualization, including utilities to automate the data visualizaton for analysis of differentially expressed genes (DEGs). systemPipeTools provides data transformation and data exploration functions via scatterplots, hierarchical clustering heatMaps, principal component analysis, multidimensional scaling, generalized principal components, t-Distributed Stochastic Neighbor embedding (t-SNE), and MA and volcano plots. All these utilities can be integrated with the modular design of the systemPipeR environment that allows users to easily substitute any of these features and/or custom with alternatives.
Maintained by Daniela Cassol. Last updated 5 months ago.
infrastructuredataimportsequencingqualitycontrolreportwritingexperimentaldesignclusteringdifferentialexpressionmultidimensionalscalingprincipalcomponent
4.00 score 4 scriptsbioc
LymphoSeq:Analyze high-throughput sequencing of T and B cell receptors
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.
Maintained by David Coffey. Last updated 5 months ago.
softwaretechnologysequencingtargetedresequencingalignmentmultiplesequencealignment
4.00 score 4 scriptsbioc
MetaPhOR:Metabolic Pathway Analysis of RNA
MetaPhOR was developed to enable users to assess metabolic dysregulation using transcriptomic-level data (RNA-sequencing and Microarray data) and produce publication-quality figures. A list of differentially expressed genes (DEGs), which includes fold change and p value, from DESeq2 or limma, can be used as input, with sample size for MetaPhOR, and will produce a data frame of scores for each KEGG pathway. These scores represent the magnitude and direction of transcriptional change within the pathway, along with estimated p-values.MetaPhOR then uses these scores to visualize metabolic profiles within and between samples through a variety of mechanisms, including: bubble plots, heatmaps, and pathway models.
Maintained by Emily Isenhart. Last updated 5 months ago.
metabolomicsrnaseqpathwaysgeneexpressiondifferentialexpressionkeggsequencingmicroarray
4.00 score 1 scriptsbioc
scTensor:Detection of cell-cell interaction from single-cell RNA-seq dataset by tensor decomposition
The algorithm is based on the non-negative tucker decomposition (NTD2) of nnTensor.
Maintained by Koki Tsuyuzaki. Last updated 5 months ago.
dimensionreductionsinglecellsoftwaregeneexpression
4.00 score 2 scriptsbioc
EasyCellType:Annotate cell types for scRNA-seq data
We developed EasyCellType which can automatically examine the input marker lists obtained from existing software such as Seurat over the cell markerdatabases. Two quantification approaches to annotate cell types are provided: Gene set enrichment analysis (GSEA) and a modified versio of Fisher's exact test. The function presents annotation recommendations in graphical outcomes: bar plots for each cluster showing candidate cell types, as well as a dot plot summarizing the top 5 significant annotations for each cluster.
Maintained by Ruoxing Li. Last updated 5 months ago.
singlecellsoftwaregeneexpressiongenesetenrichment
4.00 score 6 scriptsbioc
seqArchRplus:Downstream analyses of promoter sequence architectures and HTML report generation
seqArchRplus facilitates downstream analyses of promoter sequence architectures/clusters identified by seqArchR (or any other tool/method). With additional available information such as the TPM values and interquantile widths (IQWs) of the CAGE tag clusters, seqArchRplus can order the input promoter clusters by their shape (IQWs), and write the cluster information as browser/IGV track files. Provided visualizations are of two kind: per sample/stage and per cluster visualizations. Those of the first kind include: plot panels for each sample showing per cluster shape, TPM and other score distributions, sequence logos, and peak annotations. The second include per cluster chromosome-wise and strand distributions, motif occurrence heatmaps and GO term enrichments. Additionally, seqArchRplus can also generate HTML reports for easy viewing and comparison of promoter architectures between samples/stages.
Maintained by Sarvesh Nikumbh. Last updated 5 months ago.
annotationvisualizationreportwritinggomotifannotationclustering
1 stars 4.00 score 2 scriptsmarcohlmann
metanetwork:Handling and Representing Trophic Networks in Space and Time
A toolbox to handle and represent trophic networks in space or time across aggregation levels. This package contains a layout algorithm specifically designed for trophic networks, using dimension reduction on a diffusion graph kernel and trophic levels. Importantly, this package provides a layout method applicable for large trophic networks. The package also implements network diversity indices at different aggregation levels and connectance computation.
Maintained by Marc Ohlmann. Last updated 2 years ago.
2 stars 3.89 score 77 scriptsbioc
famat:Functional analysis of metabolic and transcriptomic data
Famat is made to collect data about lists of genes and metabolites provided by user, and to visualize it through a Shiny app. Information collected is: - Pathways containing some of the user's genes and metabolites (obtained using a pathway enrichment analysis). - Direct interactions between user's elements inside pathways. - Information about elements (their identifiers and descriptions). - Go terms enrichment analysis performed on user's genes. The Shiny app is composed of: - information about genes, metabolites, and direct interactions between them inside pathways. - an heatmap showing which elements from the list are in pathways (pathways are structured in hierarchies). - hierarchies of enriched go terms using Molecular Function and Biological Process.
Maintained by Mathieu Charles. Last updated 5 months ago.
functionalpredictiongenesetenrichmentpathwaysgoreactomekeggcompoundgene-ontologygenesshiny
1 stars 3.78 score 2 scriptshanjunwei-lab
ProgModule:Identification of Prognosis-Related Mutually Exclusive Modules
A novel tool to identify candidate driver modules for predicting the prognosis of patients by integrating exclusive coverage of mutations with clinical characteristics in cancer.
Maintained by Junwei Han. Last updated 3 months ago.
3.70 score 1 scriptshanjunwei-lab
PMAPscore:Identify Prognosis-Related Pathways Altered by Somatic Mutation
We innovatively defined a pathway mutation accumulate perturbation score (PMAPscore) to reflect the position and the cumulative effect of the genetic mutations at the pathway level. Based on the PMAPscore of pathways, identified prognosis-related pathways altered by somatic mutation and predict immunotherapy efficacy by constructing a multiple-pathway-based risk model (Tarca, Adi Laurentiu et al (2008) <doi:10.1093/bioinformatics/btn577>).
Maintained by Junwei Han. Last updated 3 years ago.
3.70 score 2 scriptsbioc
segmenter:Perform Chromatin Segmentation Analysis in R by Calling ChromHMM
Chromatin segmentation analysis transforms ChIP-seq data into signals over the genome. The latter represents the observed states in a multivariate Markov model to predict the chromatin's underlying states. ChromHMM, written in Java, integrates histone modification datasets to learn the chromatin states de-novo. The goal of this package is to call chromHMM from within R, capture the output files in an S4 object and interface to other relevant Bioconductor analysis tools. In addition, segmenter provides functions to test, select and visualize the output of the segmentation.
Maintained by Mahmoud Ahmed. Last updated 5 months ago.
softwarehistonemodificationbioconductorchromhmmsegmentation-an
4 stars 3.60 score 9 scriptsfmmattioni
metabolic:Datasets and Functions for Reproducing Meta-Analyses
Dataset and functions from the meta-analysis published in Medicine & Science in Sports & Exercise. It contains all the data and functions to reproduce the analysis. "Effectiveness of HIIE versus MICT in Improving Cardiometabolic Risk Factors in Health and Disease: A Meta-analysis". Felipe Mattioni Maturana, Peter Martus, Stephan Zipfel, Andreas M Nieß (2020) <doi:10.1249/MSS.0000000000002506>.
Maintained by Felipe Mattioni Maturana. Last updated 1 years ago.
8 stars 3.60 score 8 scriptsgavieira
biblioverlap:Document-Level Matching Between Bibliographic Datasets
Identifies and visualizes document overlap in any number of bibliographic datasets. This package implements the identification of overlapping documents through the exact match of a unique identifier (e.g. Digital Object Identifier - DOI) and, for records where the identifier is absent, through a score calculated from a set of fields commonly found in bibliographic datasets (Title, Source, Authors and Publication Year). Additionally, it provides functions to visualize the results of the document matching through a Venn diagram and/or UpSet plot, as well as a summary of the matching procedure.
Maintained by Gabriel Vieira. Last updated 1 years ago.
bibliometricsdocument-matchingscientometricsupsetplotvenn-diagram
5 stars 3.57 score 15 scriptszhaosq2022
BioVizSeq:Visualizing the Elements Within Bio-Sequences
Visualizing the types and distribution of elements within bio-sequences. At the same time, We have developed a geom layer, geom_rrect(), that can generate rounded rectangles. No external references are used in the development of this package.
Maintained by Shiqi Zhao. Last updated 3 months ago.
3.48 score 4 scriptsmdhall272
STraTUS:Enumeration and Uniform Sampling of Transmission Trees for a Known Phylogeny
For a single, known pathogen phylogeny, provides functions for enumeration of the set of compatible epidemic transmission trees, and for uniform sampling from that set. Optional arguments allow for incomplete sampling with a known number of missing individuals, multiple sampling, and known infection time limits. Always assumed are a complete transmission bottleneck and no superinfection or reinfection. See Hall and Colijn (2019) <doi:10.1093/molbev/msz058> for methodology.
Maintained by Matthew Hall. Last updated 5 months ago.
4 stars 3.30 scorebjoelle
FossilSimShiny:Shiny Application for 'FossilSim'
A shiny application based on 'FossilSim'. Used for simulating tree, taxonomic and fossil data under mechanistic models of speciation, preservation and sampling.
Maintained by Joelle Barido-Sottani. Last updated 11 months ago.
3.00 scoresidoruvigo
calendR:Ready to Print Monthly and Yearly Calendars Made with 'ggplot2'
Contains the function calendR() for creating fully customizable monthly and yearly calendars (colors, fonts, formats, ...) and even heatmap calendars. In addition, it allows saving the calendars in ready to print A4 format PDF files.
Maintained by José Carlos Soage González. Last updated 1 years ago.
2.78 score 97 scripts 2 dependentsjoergsesterhenn
medacoPlot:Renders plots of medaco csv data
Plot power input and output.
Maintained by Joerg Sesterhenn. Last updated 1 hours ago.
medacophotovoltaicssmartmetervisualization
2.74 score 1 scriptscran
delimtools:Helper Functions for Species Delimitation Analysis
Helpers functions to process, analyse, and visualize the output of single locus species delimitation methods. For full functionality, please install suggested software at <https://legallab.github.io/delimtools/articles/install.html>.
Maintained by Pedro Bittencourt. Last updated 3 days ago.
2.70 scoremohmedsoudy
ggaligner:Visualizing Sequence Alignment by Generating Publication-Ready Plots
Providing publication-ready graphs for Multiple sequence alignment. Moreover, it provides a unique solution for visualizing the multiple sequence alignment without the need to do the alignment in each run which is a big limitation in other available packages.
Maintained by Mohamed Soudy. Last updated 2 years ago.
2.70 score 1 scriptsoyshilin
Sysrecon:Systematical Metabolic Reconstruction
In the past decade, genome-scale metabolic reconstructions have widely been used to comprehend the systems biology of metabolic pathways within an organism. Different GSMs are constructed using various techniques that require distinct steps, but the input data, information conversion and software tools are neither concisely defined nor mathematically or programmatically formulated in a context-specific manner.The tool that quantitatively and qualitatively specifies each reconstruction steps and can generate a template list of reconstruction steps dynamically selected from a reconstruction step reservoir, constructed based on all available published papers.
Maintained by Shilin Ouyang. Last updated 2 years ago.
2.70 score 1 scriptsmohmedsoudy
DFD:Extract Drugs from Differential Expression Data
Extract Drugs from Differential Expression Data using the Connectivity Map (CMAP) Approach and Library of Integrated Network-Based Cellular Signatures (LINCS) Database.
Maintained by Mohamed Soudy. Last updated 1 years ago.
1 stars 2.70 score 1 scriptsfalafel19
AutoPipe:Automated Transcriptome Classifier Pipeline: Comprehensive Transcriptome Analysis
An unsupervised fully-automated pipeline for transcriptome analysis or a supervised option to identify characteristic genes from predefined subclasses. We rely on the 'pamr' <http://www.bioconductor.org/packages//2.7/bioc/html/pamr.html> clustering algorithm to cluster the Data and then draw a heatmap of the clusters with the most significant genes and the least significant genes according to the 'pamr' algorithm. This way we get easy to grasp heatmaps that show us for each cluster which are the clusters most defining genes.
Maintained by Karam Daka. Last updated 6 years ago.
2.48 scorehanjunwei-lab
pathwayTMB:Pathway Based Tumor Mutational Burden
A systematic bioinformatics tool to develop a new pathway-based gene panel for tumor mutational burden (TMB) assessment (pathway-based tumor mutational burden, PTMB), using somatic mutations files in an efficient manner from either The Cancer Genome Atlas sources or any in-house studies as long as the data is in mutation annotation file (MAF) format. Besides, we develop a multiple machine learning method using the sample's PTMB profiles to identify cancer-specific dysfunction pathways, which can be a biomarker of prognostic and predictive for cancer immunotherapy.
Maintained by Junwei Han. Last updated 3 years ago.
2.48 score 2 scripts 1 dependentsgrafxzahl
genBaRcode:Analysis and Visualization Tools for Genetic Barcode Data
Provides the necessary functions to identify and extract a selection of already available barcode constructs (Cornils, K. et al. (2014) <doi:10.1093/nar/gku081>) and freely choosable barcode designs from next generation sequence (NGS) data. Furthermore, it offers the possibility to account for sequence errors, the calculation of barcode similarities and provides a variety of visualisation tools (Thielecke, L. et al. (2017) <doi:10.1038/srep43249>).
Maintained by Lars Thielecke. Last updated 24 days ago.
2.30 score 6 scriptsthermostats
ssdGSA:Single Sample Directional Gene Set Analysis
A method that inherits the standard gene set variation analysis (GSVA) method and also provides the option to use summary statistics from any analysis (disease vs healthy, lesional side vs nonlesional side, etc..) input to define the direction of gene sets used for directional gene set score calculation for a given disease. Note to use this package, GSVA(>= 1.52.1) is needed to pre-installed. Hanzelmann, S., Castelo, R., and Guinney, J. (2013) <doi:10.1186/1471-2105-14-7>.
Maintained by Xingpeng Li. Last updated 8 months ago.
2.00 score 3 scriptshanjunwei-lab
DRviaSPCN:Drug Repurposing in Cancer via a Subpathway Crosstalk Network
A systematic biology tool was developed to repurpose drugs via a subpathway crosstalk network. The operation modes include 1) calculating centrality scores of SPs in the context of gene expression data to reflect the influence of SP crosstalk, 2) evaluating drug-disease reverse association based on disease- and drug-induced SPs weighted by the SP crosstalk, 3) identifying cancer candidate drugs through perturbation analysis. There are also several functions used to visualize the results.
Maintained by Junwei Han. Last updated 3 months ago.
2.00 score 5 scriptsdaijiang
lirrr:Functions collected/wrote by Daijiang Li
To keep all my functions in one place, and to use them more easily.
Maintained by Daijiang Li. Last updated 1 years ago.
1 stars 1.70 score 3 scriptspredictiveecology
usefulFuns:Useful functions for my modules and packages
A few functions and wrappers around useful code.
Maintained by Tati Micheletti. Last updated 4 months ago.
1.70 score 1 scriptsmschilli87
calendRio:'calendR' Fork with Additional Features (Backwards Compatible)
Fork of 'calendR' R package to generate ready to print calendars with 'ggplot2' (see <https://r-coder.com/calendar-plot-r/>) with additional features (backwards compatible). 'calendRio' provides a 'calendR()' function that serves as a drop-in replacement for the upstream version but allows for additional parameters unlocking extra functionality.
Maintained by Marcel Schilling. Last updated 3 months ago.
1.70 score