EnhancedVolcano - Publication-ready volcano plots with enhanced colouring and labeling
Volcano plots represent a useful way to visualise the results of differential expression analyses. Here, we present a highly-configurable function that produces publication-ready volcano plots. EnhancedVolcano will attempt to fit as many point labels in the plot window as possible, thus avoiding 'clogging' up the plot with labels that could not otherwise have been read. Other functionality allows the user to identify up to 4 different types of attributes in the same plot space via colour, shape, size, and shade parameter configurations.
Last updated 26 days ago
rnaseqgeneexpressiontranscriptiondifferentialexpressionimmunooncology
11.37 score 409 stars 2 packages 2.4k scripts 6.6k downloadsPCAtools - PCAtools: Everything Principal Components Analysis
Principal Component Analysis (PCA) is a very powerful technique that has wide applicability in data science, bioinformatics, and further afield. It was initially developed to analyse large volumes of data in order to tease out the differences/relationships between the logical entities being analysed. It extracts the fundamental structure of the data without the need to build any model to represent it. This 'summary' of the data is arrived at through a process of reduction that can transform the large number of variables into a lesser number that are uncorrelated (i.e. the 'principal components'), while at the same time being capable of easy interpretation on the original data. PCAtools provides functions for data exploration via PCA, and allows the user to generate publication-ready figures. PCA is performed via BiocSingular - users can also identify optimal number of principal components via different metrics, such as elbow method and Horn's parallel analysis, which has relevance for data reduction in single-cell RNA-seq (scRNA-seq) and high dimensional mass cytometry data.
Last updated 26 days ago
rnaseqatacseqgeneexpressiontranscriptionsinglecellprincipalcomponent
11.14 score 329 stars 3 packages 636 scripts 1.8k downloadsscDataviz - scDataviz: single cell dataviz and downstream analyses
In the single cell World, which includes flow cytometry, mass cytometry, single-cell RNA-seq (scRNA-seq), and others, there is a need to improve data visualisation and to bring analysis capabilities to researchers even from non-technical backgrounds. scDataviz attempts to fit into this space, while also catering for advanced users. Additonally, due to the way that scDataviz is designed, which is based on SingleCellExperiment, it has a 'plug and play' feel, and immediately lends itself as flexibile and compatibile with studies that go beyond scDataviz. Finally, the graphics in scDataviz are generated via the ggplot engine, which means that users can 'add on' features to these with ease.
Last updated 26 days ago
singlecellimmunooncologyrnaseqgeneexpressiontranscriptionflowcytometrymassspectrometrydataimport
6.20 score 61 stars 13 scripts 198 downloads