inst/extdata/GeneTonic101.md

In federicomarini/GeneTonic: Enjoy Analyzing And Integrating The Results From Differential Expression Analysis And Functional Enrichment Analysis

What is GeneTonic?

GeneTonic is a Bioconductor package whose aim is to analyze and integrate the results from Differential Expression analysis and functional enrichment analysis, together with the original expression matrix.

As a distinctive trait, this app combines the ease and beauty of interactive analysis with the technical robustness and the practicality of generating a reproducible report.

What do I need to use GeneTonic?

Four main ingredients are required:

1. dds: a DESeqDataSet object, the main component in the DESeq2 framework, which extends the widely adopted SummarizedExperiment class. This object will store the information related to the expression matrix.

2. res_de: a DESeqResults object, the results of Differential Expression analysis, computed on the dds object above. This extends the S4Vectors::DataFrame class.

3. res_enrich: a data.frame, containing the results of the enrichment analysis, generally computed on the basis of the DE results and the expression matrix. The GeneTonic main functions require some specific columns to be present, specified in the package documentation. Common formats (e.g. from pcaExplorer::topGOtable or from ClusterProfiler) are supported with conversion functions.

4. annotation_obj: the annotation data.frame, composed at least of two columns, gene_id, with a set of unambiguous identifiers (e.g. ENSEMBL ids) corresponding to the row names of the dds object, and gene_name, containing e.g. HGNC-based gene symbols.

For more detail on these and more aspects (getting to know the user interface, using the functions in a normal R session), please consult the vignette, and try out the tours for each tab in a running instance of the app (e.g. the demo available at http://shiny.imbei.uni-mainz.de:3838/GeneTonic)

federicomarini/GeneTonic documentation built on March 27, 2024, 4:19 p.m.