new_ggraph

This function merges multiple gene-pathway related dataframes, processes them
for graph creation, and visualizes the relationships in a dendrogram layout using
the provided node and edge gathering functions from the 'ggraph' package.

A tool for comprehensive transcriptomic data analysis, with a focus on transcript-level data preprocessing, expression profiling, differential expression analysis, and functional enrichment. It enables researchers to identify key biological processes, disease biomarkers, and gene regulatory mechanisms. 'TransProR' is aimed at researchers and bioinformaticians working with RNA-Seq data, providing an intuitive framework for in-depth analysis and visualization of transcriptomic datasets. The package includes comprehensive documentation and usage examples to guide users through the entire analysis pipeline. The differential expression analysis methods incorporated in the package include 'limma' (Ritchie et al., 2015, <doi:10.1093/nar/gkv007>; Smyth, 2005, <doi:10.1007/0-387-29362-0_23>), 'edgeR' (Robinson et al., 2010, <doi:10.1093/bioinformatics/btp616>), 'DESeq2' (Love et al., 2014, <doi:10.1186/s13059-014-0550-8>), and Wilcoxon tests (Li et al., 2022, <doi:10.1186/s13059-022-02648-4>), providing flexible and robust approaches to RNA-Seq data analysis. For more information, refer to the package vignettes and related publications.

Dongyue Yu

TransProR

Analysis and Visualization of Multi-Omics Data

new_ggraph function

<dl><dt>BP_dataframe</dt>
<dd>Dataframe for Biological Process.</dd>
<dt>BP_ids</dt>
<dd>IDs for Biological Process.</dd>
<dt>KEGG_dataframe</dt>
<dd>Dataframe for KEGG pathways.</dd>
<dt>KEGG_ids</dt>
<dd>IDs for KEGG pathways.</dd>
<dt>MF_dataframe</dt>
<dd>Dataframe for Molecular Function.</dd>
<dt>MF_ids</dt>
<dd>IDs for Molecular Function.</dd>
<dt>REACTOME_dataframe</dt>
<dd>Dataframe for REACTOME pathways.</dd>
<dt>REACTOME_ids</dt>
<dd>IDs for REACTOME pathways.</dd>
<dt>CC_dataframe</dt>
<dd>Dataframe for Cellular Component.</dd>
<dt>CC_ids</dt>
<dd>IDs for Cellular Component.</dd>
<dt>DO_dataframe</dt>
<dd>Dataframe for Disease Ontology.</dd>
<dt>DO_ids</dt>
<dd>IDs for Disease Ontology.</dd></dl>

Arguments

Generate a graphical representation of pathway gene maps — new_ggraph

<dl>

<dt>BP_dataframe</dt>
<dd>Dataframe for Biological Process.</dd>


<dt>BP_ids</dt>
<dd>IDs for Biological Process.</dd>


<dt>KEGG_dataframe</dt>
<dd>Dataframe for KEGG pathways.</dd>


<dt>KEGG_ids</dt>
<dd>IDs for KEGG pathways.</dd>


<dt>MF_dataframe</dt>
<dd>Dataframe for Molecular Function.</dd>


<dt>MF_ids</dt>
<dd>IDs for Molecular Function.</dd>


<dt>REACTOME_dataframe</dt>
<dd>Dataframe for REACTOME pathways.</dd>


<dt>REACTOME_ids</dt>
<dd>IDs for REACTOME pathways.</dd>


<dt>CC_dataframe</dt>
<dd>Dataframe for Cellular Component.</dd>


<dt>CC_ids</dt>
<dd>IDs for Cellular Component.</dd>


<dt>DO_dataframe</dt>
<dd>Dataframe for Disease Ontology.</dd>


<dt>DO_ids</dt>
<dd>IDs for Disease Ontology.</dd>

</dl>

new_ggraph: Generate a graphical representation of pathway gene maps

Description

Usage

Value

Arguments