Showing 122 of total 122 results (show query)
bioc
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 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 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 dependentsbioc
mia:Microbiome analysis
mia implements tools for microbiome analysis based on the SummarizedExperiment, SingleCellExperiment and TreeSummarizedExperiment infrastructure. Data wrangling and analysis in the context of taxonomic data is the main scope. Additional functions for common task are implemented such as community indices calculation and summarization.
Maintained by Tuomas Borman. Last updated 16 hours ago.
microbiomesoftwaredataimportanalysisbioconductorcpp
51 stars 11.52 score 316 scripts 5 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 scriptsbioc
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 scriptsbioc
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 14 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
maaslin3:"Refining and extending generalized multivariate linear models for meta-omic association discovery"
MaAsLin 3 refines and extends generalized multivariate linear models for meta-omicron association discovery. It finds abundance and prevalence associations between microbiome meta-omics features and complex metadata in population-scale epidemiological studies. The software includes multiple analysis methods (including support for multiple covariates, repeated measures, and ordered predictors), filtering, normalization, and transform options to customize analysis for your specific study.
Maintained by William Nickols. Last updated 7 days ago.
metagenomicssoftwaremicrobiomenormalizationmultiplecomparison
33 stars 8.16 score 34 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 scripts
bioc
TreeSummarizedExperiment:TreeSummarizedExperiment: a S4 Class for Data with Tree Structures
TreeSummarizedExperiment has extended SingleCellExperiment to include hierarchical information on the rows or columns of the rectangular data.
Maintained by Ruizhu Huang. Last updated 21 days ago.
datarepresentationinfrastructure
7.57 score 251 scripts 15 dependentsbioc
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 scriptsbioc
MGnifyR:R interface to EBI MGnify metagenomics resource
Utility package to facilitate integration and analysis of EBI MGnify data in R. The package can be used to import microbial data for instance into TreeSummarizedExperiment (TreeSE). In TreeSE format, the data is directly compatible with miaverse framework.
Maintained by Tuomas Borman. Last updated 6 days ago.
infrastructuredataimportmetagenomicsmicrobiomemicrobiomedata
21 stars 7.48 score 32 scripts
kharchenkolab
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 14 days ago.
cancer-genomicscnv-detectionlineage-tracingphylogenysingle-cellsingle-cell-analysissingle-cell-rna-seqspatial-transcriptomicscpp
180 stars 7.48 score 120 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 scriptsbioc
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 scripts
kbhoehn
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 scripts
junjunlab
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 23 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 scripts
joshwlambert
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 scripts
xjsun1221
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 scriptsbioc
miaSim:Microbiome Data Simulation
Microbiome time series simulation with generalized Lotka-Volterra model, Self-Organized Instability (SOI), and other models. Hubbell's Neutral model is used to determine the abundance matrix. The resulting abundance matrix is applied to (Tree)SummarizedExperiment objects.
Maintained by Yagmur Simsek. Last updated 5 months ago.
microbiomesoftwaresequencingdnaseqatacseqcoveragenetwork
21 stars 6.64 score 23 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 scriptsbioc
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 14 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 scripts
revbayes
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 scripts
ganglilab
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
dar:Differential Abundance Analysis by Consensus
Differential abundance testing in microbiome data challenges both parametric and non-parametric statistical methods, due to its sparsity, high variability and compositional nature. Microbiome-specific statistical methods often assume classical distribution models or take into account compositional specifics. These produce results that range within the specificity vs sensitivity space in such a way that type I and type II error that are difficult to ascertain in real microbiome data when a single method is used. Recently, a consensus approach based on multiple differential abundance (DA) methods was recently suggested in order to increase robustness. With dar, you can use dplyr-like pipeable sequences of DA methods and then apply different consensus strategies. In this way we can obtain more reliable results in a fast, consistent and reproducible way.
Maintained by Francesc Catala-Moll. Last updated 18 days ago.
softwaresequencingmicrobiomemetagenomicsmultiplecomparisonnormalizationbioconductorbiomarker-discoverydifferential-abundance-analysisfeature-selectionmicrobiologyphyloseq
2 stars 5.98 score 8 scriptsbioc
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 dependents
xiaoluo-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
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 scriptsbioc
benchdamic:Benchmark of differential abundance methods on microbiome data
Starting from a microbiome dataset (16S or WMS with absolute count values) it is possible to perform several analysis to assess the performances of many differential abundance detection methods. A basic and standardized version of the main differential abundance analysis methods is supplied but the user can also add his method to the benchmark. The analyses focus on 4 main aspects: i) the goodness of fit of each method's distributional assumptions on the observed count data, ii) the ability to control the false discovery rate, iii) the within and between method concordances, iv) the truthfulness of the findings if any apriori knowledge is given. Several graphical functions are available for result visualization.
Maintained by Matteo Calgaro. Last updated 4 months ago.
metagenomicsmicrobiomedifferentialexpressionmultiplecomparisonnormalizationpreprocessingsoftwarebenchmarkdifferential-abundance-methods
8 stars 5.78 score 8 scripts
limengbinggz
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 scripts
tiago-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 scripts
thermostats
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 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 13 days ago.
softwarevisualizationdifferentialexpressiongeneexpressiontranscriptionrnaseqsinglecellsequencingclustering
7 stars 5.45 score 2 scriptsbioc
PLSDAbatch:PLSDA-batch
A novel framework to correct for batch effects prior to any downstream analysis in microbiome data based on Projection to Latent Structures Discriminant Analysis. The main method is named “PLSDA-batch”. It first estimates treatment and batch variation with latent components, then subtracts batch-associated components from the data whilst preserving biological variation of interest. PLSDA-batch is highly suitable for microbiome data as it is non-parametric, multivariate and allows for ordination and data visualisation. Combined with centered log-ratio transformation for addressing uneven library sizes and compositional structure, PLSDA-batch addresses all characteristics of microbiome data that existing correction methods have ignored so far. Two other variants are proposed for 1/ unbalanced batch x treatment designs that are commonly encountered in studies with small sample sizes, and for 2/ selection of discriminative variables amongst treatment groups to avoid overfitting in classification problems. These two variants have widened the scope of applicability of PLSDA-batch to different data settings.
Maintained by Yiwen (Eva) Wang. Last updated 5 months ago.
statisticalmethoddimensionreductionprincipalcomponentclassificationmicrobiomebatcheffectnormalizationvisualization
13 stars 5.37 score 18 scriptsbioc
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 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 scripts
jiang-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 4 months ago.
cross-species-analysisscrna-seq
12 stars 5.26 score 6 scripts
yulab-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 scripts
bjoelle
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 dependentsbioc
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 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 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 14 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 scripts
andersgs
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 scriptsbioc
HoloFoodR:R interface to EBI HoloFood resource
Utility package to facilitate integration and analysis of EBI HoloFood data in R. This package streamlines access to the resource, allowing for direct loading of data into formats optimized for downstream analytics.
Maintained by Tuomas Borman. Last updated 1 months ago.
softwareinfrastructuredataimportmicrobiomemicrobiomedata
1 stars 4.70 score 6 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 dependents
tacazares
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 scripts
yuanlonghu
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 scripts
waldronlab
MicrobiomeBenchmarkData:Datasets for benchmarking in microbiome research
The MicrobiomeBenchmarkData package provides functionality to access microbiome datasets suitable for benchmarking. These datasets have some biological truth, which allows to have expected results for comparison. The datasets come from various published sources and are provided as TreeSummarizedExperiment objects. Currently, only datasets suitable for benchmarking differential abundance methods are available.
Maintained by Samuel Gamboa. Last updated 5 months ago.
experimentdatamicrobiomedatareproducibleresearchsequencingdatabioconductor-packager01ca230551
4.39 score 18 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 14 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 scriptsbioc
microSTASIS:Microbiota STability ASsessment via Iterative cluStering
The toolkit 'µSTASIS', or microSTASIS, has been developed for the stability analysis of microbiota in a temporal framework by leveraging on iterative clustering. Concretely, the core function uses Hartigan-Wong k-means algorithm as many times as possible for stressing out paired samples from the same individuals to test if they remain together for multiple numbers of clusters over a whole data set of individuals. Moreover, the package includes multiple functions to subset samples from paired times, validate the results or visualize the output.
Maintained by Pedro Sánchez-Sánchez. Last updated 5 months ago.
geneticvariabilitybiomedicalinformaticsclusteringmultiplecomparisonmicrobiome
2 stars 4.30 score 1 scripts
rdinnager
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 14 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
ExperimentSubset:Manages subsets of data with Bioconductor Experiment objects
Experiment objects such as the SummarizedExperiment or SingleCellExperiment are data containers for one or more matrix-like assays along with the associated row and column data. Often only a subset of the original data is needed for down-stream analysis. For example, filtering out poor quality samples will require excluding some columns before analysis. The ExperimentSubset object is a container to efficiently manage different subsets of the same data without having to make separate objects for each new subset.
Maintained by Irzam Sarfraz. Last updated 5 months ago.
infrastructuresoftwaredataimportdatarepresentation
4.00 score 8 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
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 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
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
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
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
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 scripts
hanjunwei-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 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 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 scripts
zhaosq2022
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 scripts
mdhall272
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 score
oyshilin
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 scripts
cran
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 1 days ago.
2.70 score
mohmedsoudy
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 scriptsmohmedsoudy
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 scripts
falafel19
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 dependents
grafxzahl
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 23 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 scripts
daijiang
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 scripts
