Package: TransProR 0.0.6

TransProR: Analysis and Visualization of Multi-Omics Data

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.

Authors:Dongyue Yu [aut, cre, cph]

TransProR_0.0.6.tar.gz
TransProR_0.0.6.zip(r-4.5)TransProR_0.0.6.zip(r-4.4)TransProR_0.0.6.zip(r-4.3)
TransProR_0.0.6.tgz(r-4.4-any)TransProR_0.0.6.tgz(r-4.3-any)
TransProR_0.0.6.tar.gz(r-4.5-noble)TransProR_0.0.6.tar.gz(r-4.4-noble)
TransProR_0.0.6.tgz(r-4.4-emscripten)TransProR_0.0.6.tgz(r-4.3-emscripten)
TransProR.pdf |TransProR.html
TransProR/json (API)

# Install 'TransProR' in R:
install.packages('TransProR', repos = c('https://sssydysss.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/sssydysss/transpror/issues

Datasets:

On CRAN:

6.30 score 50 stars 34 scripts 35 downloads 53 exports 208 dependencies

Last updated 12 days agofrom:e090e5907c. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKDec 14 2024
R-4.5-winOKDec 14 2024
R-4.5-linuxOKDec 14 2024
R-4.4-winOKDec 14 2024
R-4.4-macOKDec 14 2024
R-4.3-winOKDec 14 2024
R-4.3-macOKDec 14 2024

Exports:%>%add_boxplotadd_new_tile_layeradjust_alpha_scaleadjust_color_toneadjust_export_pathwaycircos_fruitsCombat_Normalcombat_tumorcompare_mergeContrast_Venncreate_base_plotdeg_filterDESeq2_analyzedrawLegendsedgeR_analyzeenrich_circo_barenrich_polar_bubbleenrichment_circlizeenrichment_spiral_plotsextract_descriptions_countsextract_ntop_pathwaysextract_positive_pathwaysfacet_density_foldchangefilter_diff_genesfour_degs_venngather_graph_edgegather_graph_nodegene_colorgene_highlightsgene_map_pathwayget_gtex_expget_tcga_exphighlight_by_nodehighlight_geneslimma_analyzelog_transformmerge_density_foldchangemerge_gtex_tcgamerge_id_positionmerge_method_colornew_ggraphpathway_countpathway_descriptionprep_deseq2prep_edgeRprep_limmaprep_wilcoxonprocess_heatdataseek_gtex_organselectPathwaysspiral_newrleWilcoxon_analyze

Dependencies:abindadmiscannotateAnnotationDbiapeaplotashaskpassbackportsbase64encBHBiobaseBiocGenericsBiocParallelBiostringsbitbit64blobbootbroombslibcachemcarcarDatacheckmatecirclizecliclueclustercodetoolscolorspaceComplexHeatmapcorrplotcowplotcpp11crayoncrosstalkcurldata.tableDBIDelayedArrayDerivDESeq2digestdoBydoParalleldplyredgeRevaluateextrafontextrafontdbfansifarverfastmapfontawesomefontBitstreamVerafontLiberationfontquiverforcatsforeachforeignformatRFormulafsfutile.loggerfutile.optionsgdtoolsgenefiltergenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesgeomtextpathGetoptLongggaltggdensityggforceggfunggnewscaleggplot2ggplotifyggpubrggraphggrepelggsciggsignifggtreeggtreeExtraggVennDiagramGlobalOptionsgluegraphlayoutsgridExtragridGraphicsgtablehighrHmischrbrthemeshtmlTablehtmltoolshtmlwidgetshttrigraphIRangesisobanditeratorsjquerylibjsonliteKEGGRESTKernSmoothknitrlabelinglambda.rlaterlatticelazyevallifecyclelimmalme4locfitlubridatemagrittrmapsMASSMatrixMatrixGenericsMatrixModelsmatrixStatsmemoisemgcvmicrobenchmarkmimeminqamodelrmunsellnlmenloptrnnetnumDerivopensslpatchworkpbkrtestpillarpkgconfigplogrplotlypngpolyclippolynomproj4promisespurrrquantregR6rappdirsRColorBrewerRcppRcppArmadilloRcppEigenrjsonrlangrmarkdownrpartRSQLiterstatixrstudioapiRttf2pt1S4ArraysS4VectorssassscalesshapesnowSparseArraySparseMspiralizestatmodstringistringrSummarizedExperimentsurvivalsvasyssystemfontstextshapingtibbletidygraphtidyrtidyselecttidytreetimechangetinytextreeiotweenrUCSC.utilsutf8vctrsvennviridisviridisLitewithrxfunXMLxtableXVectoryamlyulab.utilszlibbioc

TransProR: Analysis and visualization of transcriptomic data are currently in progress. Future directions include multi-modal fusion, sparse learning, and the investigation of spatio-temporal effects.

Rendered fromTransProR.Rmdusingknitr::rmarkdownon Dec 14 2024.

Last update: 2024-04-10
Started: 2023-10-30

Readme and manuals

Help Manual

Help pageTopics
Add a boxplot layer to a `ggtree` plotadd_boxplot
Add a new tile layer with dynamic scales to a `ggtree` plotadd_new_tile_layer
Adjust Alpha Scale for Data Visualizationadjust_alpha_scale
Adjust Color Tone by Modifying Saturation and Luminanceadjust_color_tone
Adjust and Export Pathway Analysis Resultsadjust_export_pathway
All DEGs Venn Diagram Dataall_degs_venn
Add multiple layers to a `ggtree` plot for visualizing gene expression and enrichment datacircos_fruits
Process and Correct Batch Effects in TCGA's normal tissue and GTEX DataCombat_Normal
Process and Correct Batch Effects in Tumor Datacombat_tumor
Compare and merge specific columns from two DEG data framescompare_merge
Function to Create a Venn Diagram of DEGs with Custom ColorsContrast_Venn
Create a base plot with gene expression data on a phylogenetic treecreate_base_plot
Function to Filter Differentially Expressed Genes (DEGs)deg_filter
Differential Gene Expression Analysis using 'DESeq2'DESeq2_analyze
Draw Dual-Sided Legends on a PlotdrawLegends
Differential Gene Expression Analysis using 'edgeR'edgeR_analyze
Combine and Visualize Data with Circular Bar Chartenrich_circo_bar
Enrichment Polar Bubble Plotenrich_polar_bubble
Draw Chord Diagram with Legendsenrichment_circlize
Create Spiral Plots with Legends Using 'spiralize' and 'ComplexHeatmap'enrichment_spiral_plots
Extract and Count Descriptions with Specified Colorextract_descriptions_counts
Extract and Store Top Pathways for Each Sampleextract_ntop_pathways
Extract Positive Pathways from SSGSEA Results and Select Random Samplesextract_positive_pathways
Create faceted high-density region plots with optional points and density contoursfacet_density_foldchange
Filter Differentially Expressed Genesfilter_diff_genes
Function to Create a Venn Diagram of DEGsfour_degs_venn
Gather graph edge from data frame Please note that this function is from the 'ggraph' package and has not been altered in functionality, but it has been optimized and iterated. It is not original content of 'TransProR'. However, since 'ggraph' caused frequent GitHub Action errors during the creation of 'TransProR', the author directly referenced the involved functions in 'TransProR'. This is not the author's original creation. All users please be aware!gather_graph_edge
Gather graph nodes from a data frame Please note that this function is from the 'ggraph' package and has not been altered in functionality, but it has been optimized and iterated. It is not original content of 'TransProR'. However, since 'ggraph' caused frequent GitHub Action errors during the creation of 'TransProR', the author directly referenced the involved functions in 'TransProR'. This is not the author's original creation. All users please be aware!gather_graph_node
Merge Genes with Color Information Based on Up/Down Regulationgene_color
Add gene highlights to a ggtree objectgene_highlights
Create Pathway-Gene Mapping Data Framegene_map_pathway
Get GTEx Expression Data for Specific Organget_gtex_exp
TCGA Expression Data Processingget_tcga_exp
Phylogenetic Tree Objectgtree
Highlight Nodes in a Phylogenetic Tree with Custom Fill Colors and Transparencyhighlight_by_node
Add Highlights for Genes on a Phylogenetic Treehighlight_genes
Differential Gene Expression Analysis using limma and voomlimma_analyze
Log transformation decision and application on datalog_transform
Create high-density region plot with optional points, density rugs, and contoursmerge_density_foldchange
Merge gene expression data from GTEx and TCGA datasetsmerge_gtex_tcga
Merge Data Frames by Common Row Names with Additional Columnsmerge_id_position
Merge Data Frames with Specific Method and Color Columnsmerge_method_color
Generate a graphical representation of pathway gene mapsnew_ggraph
Count Genes Present in Pathways Above a Thresholdpathway_count
Describe Genes Present in Selected Pathwayspathway_description
Prepare DESeq2 data for plottingprep_deseq2
Prepare edgeR DEG data for plottingprep_edgeR
Prepare limma-voom DEG data for plottingprep_limma
Prepare Wilcoxon DEG data for plottingprep_wilcoxon
Process Heatmap Data with Various Selection Optionsprocess_heatdata
Load and Process GTEX Phenotype Data to Retrieve Primary Site Countsseek_gtex_organ
Randomly Select Pathways with Limited Word CountselectPathways
Render a Spiral Plot Using Run-Length Encodingspiral_newrle
Differential Gene Expression Analysis Using Wilcoxon Rank-Sum TestWilcoxon_analyze