Showing 9 of total 9 results (show query)
pboutros
VennDiagram:Generate High-Resolution Venn and Euler Plots
A set of functions to generate high-resolution Venn and Euler plots. Includes handling for several special cases, including two-case scaling, and extensive customization of plot shape and structure.
Maintained by Paul Boutros. Last updated 3 years ago.
55.0 match 3 stars 8.53 score 5.7k scripts 41 dependents
bioc
VennDetail:A package for visualization and extract details
A set of functions to generate high-resolution Venn,Vennpie plot,extract and combine details of these subsets with user datasets in data frame is available.
Maintained by Kai Guo. Last updated 5 months ago.
datarepresentationgraphandnetworkextractvenndiagram
12.7 match 29 stars 6.75 score 65 scriptsbioc
limma:Linear Models for Microarray and Omics Data
Data analysis, linear models and differential expression for omics data.
Maintained by Gordon Smyth. Last updated 7 days ago.
exonarraygeneexpressiontranscriptionalternativesplicingdifferentialexpressiondifferentialsplicinggenesetenrichmentdataimportbayesianclusteringregressiontimecoursemicroarraymicrornaarraymrnamicroarrayonechannelproprietaryplatformstwochannelsequencingrnaseqbatcheffectmultiplecomparisonnormalizationpreprocessingqualitycontrolbiomedicalinformaticscellbiologycheminformaticsepigeneticsfunctionalgenomicsgeneticsimmunooncologymetabolomicsproteomicssystemsbiologytranscriptomics
3.3 match 13.81 score 16k scripts 585 dependents
pwwang
plotthis:High-Level Plotting Built Upon 'ggplot2' and Other Plotting Packages
Provides high-level API and a wide range of options to create stunning, publication-quality plots effortlessly. It is built upon 'ggplot2' and other plotting packages, and is designed to be easy to use and to work seamlessly with 'ggplot2' objects. It is particularly useful for creating complex plots with multiple layers, facets, and annotations. It also provides a set of functions to create plots for specific types of data, such as Venn diagrams, alluvial diagrams, and phylogenetic trees. The package is designed to be flexible and customizable, and to work well with the 'ggplot2' ecosystem. The API can be found at <https://pwwang.github.io/plotthis/reference/index.html>.
Maintained by Panwen Wang. Last updated 3 days ago.
6.6 match 36 stars 5.51 score 2 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
2.0 match 183 stars 9.70 score 126 scripts 1 dependentsbioc
fCI:f-divergence Cutoff Index for Differential Expression Analysis in Transcriptomics and Proteomics
(f-divergence Cutoff Index), is to find DEGs in the transcriptomic & proteomic data, and identify DEGs by computing the difference between the distribution of fold-changes for the control-control and remaining (non-differential) case-control gene expression ratio data. fCI provides several advantages compared to existing methods.
Maintained by Shaojun Tang. Last updated 5 months ago.
5.3 match 3.30 score 5 scriptsbioc
phenomis:Postprocessing and univariate analysis of omics data
The 'phenomis' package provides methods to perform post-processing (i.e. quality control and normalization) as well as univariate statistical analysis of single and multi-omics data sets. These methods include quality control metrics, signal drift and batch effect correction, intensity transformation, univariate hypothesis testing, but also clustering (as well as annotation of metabolomics data). The data are handled in the standard Bioconductor formats (i.e. SummarizedExperiment and MultiAssayExperiment for single and multi-omics datasets, respectively; the alternative ExpressionSet and MultiDataSet formats are also supported for convenience). As a result, all methods can be readily chained as workflows. The pipeline can be further enriched by multivariate analysis and feature selection, by using the 'ropls' and 'biosigner' packages, which support the same formats. Data can be conveniently imported from and exported to text files. Although the methods were initially targeted to metabolomics data, most of the methods can be applied to other types of omics data (e.g., transcriptomics, proteomics).
Maintained by Etienne A. Thevenot. Last updated 5 months ago.
batcheffectclusteringcoveragekeggmassspectrometrymetabolomicsnormalizationproteomicsqualitycontrolsequencingstatisticalmethodtranscriptomics
2.0 match 4.40 score 6 scriptsbioc
abseqR:Reporting and data analysis functionalities for Rep-Seq datasets of antibody libraries
AbSeq is a comprehensive bioinformatic pipeline for the analysis of sequencing datasets generated from antibody libraries and abseqR is one of its packages. abseqR empowers the users of abseqPy (https://github.com/malhamdoosh/abseqPy) with plotting and reporting capabilities and allows them to generate interactive HTML reports for the convenience of viewing and sharing with other researchers. Additionally, abseqR extends abseqPy to compare multiple repertoire analyses and perform further downstream analysis on its output.
Maintained by JiaHong Fong. Last updated 5 months ago.
sequencingvisualizationreportwritingqualitycontrolmultiplecomparison
1.8 match 4.00 score 3 scripts
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 8 days ago.
2.3 match 2.30 score 6 scripts