# TCGAbiolinks: An R/Bioconductor package for integrative analysis with GDC data

## Documentation for package ‘TCGAbiolinks’ version 2.18.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

colDataPrepare | Create samples information matrix for GDC samples
dmc.non.parametric | Perform non-parametrix wilcoxon test
gaiaCNVplot | Creates a plot for GAIA output (all significant aberrant regions.)
GDCdownload | Download GDC data
GDCprepare | Prepare GDC data
GDCprepare_clinic | Parsing clinical xml files
GDCquery | Query GDC data
GDCquery_ATAC_seq | Retrieve open access ATAC-seq files from GDC server
GDCquery_clinic | Get GDC clinical data
GDCquery_Maf | Retrieve open access maf files from GDC server
get.GRCh.bioMart | Get hg19 or hg38 information from biomaRt
getAdjacencyBiogrid | Get a matrix of interactions of genes from biogrid
getDataCategorySummary | Create a Summary table for each sample in a project saying if it contains or not files for a certain data category
getGDCInfo | Check GDC server status
getGDCprojects | Retrieve all GDC projects
getGistic | Download GISTIC data from firehose
getLinkedOmicsData | Retrieve linkedOmics data
getManifest | Get a Manifest from GDCquery output that can be used with GDC-client
getMC3MAF | Retrieve open access mc3 MAF file from GDC server
getNbCases | Get Number of cases in GDC for a project
getNbFiles | Get Number of files in GDC for a project
getProjectSummary | Get Project Summary from GDC
getResults | Get the results table from query
getSampleFilesSummary | Retrieve summary of files per sample in a project
getTSS | getTSS to fetch GENCODE gene annotation (transcripts level) from Bioconductor package biomaRt If upstream and downstream are specified in TSS list, promoter regions of GENCODE gene will be generated.
get_IDs | Extract information from TCGA barcodes.
gliomaClassifier | Gliomar classifier
isServeOK | Check GDC server status is OK
matchedMetExp | Get GDC samples with both DNA methylation (HM450K) and Gene expression data from GDC databse
PanCancerAtlas_subtypes | Retrieve table with TCGA molecular subtypes
splitAPICall | internal function to break a huge API call into smaller ones so it repects the max character limit of a string
TabSubtypesCol_merged | TCGA samples with their Pam50 subtypes
TCGAanalyze_analyseGRN | Generate network
TCGAanalyze_Clustering | Hierarchical cluster analysis
TCGAanalyze_DEA | Differential expression analysis (DEA) using edgeR or limma package.
TCGAanalyze_DEA_Affy | Differentially expression analysis (DEA) using limma package.
TCGAanalyze_DMC | Differentially methylated regions Analysis
TCGAanalyze_EA | Enrichment analysis of a gene-set with GO [BP,MF,CC] and pathways.
TCGAanalyze_EAcomplete | Enrichment analysis for Gene Ontology (GO) [BP,MF,CC] and Pathways
TCGAanalyze_Filtering | Filtering mRNA transcripts and miRNA selecting a threshold.
TCGAanalyze_LevelTab | Adding information related to DEGs genes from DEA as mean values in two conditions.
TCGAanalyze_networkInference | infer gene regulatory networks
TCGAanalyze_Normalization | normalization mRNA transcripts and miRNA using EDASeq package.
TCGAanalyze_Pathview | Generate pathview graph
TCGAanalyze_Preprocessing | Array Array Intensity correlation (AAIC) and correlation boxplot to define outlier
TCGAanalyze_Stemness | Generate Stemness Score based on RNASeq (mRNAsi stemness index) Malta et al., Cell, 2018
TCGAanalyze_survival | Creates survival analysis
TCGAanalyze_SurvivalKM | survival analysis (SA) univariate with Kaplan-Meier (KM) method.
TCGAbatch_Correction | Batch correction using ComBat and Voom transformation using limma package.

TCGAbiolinks

The aim of TCGAbiolinks is : i) facilitate the TCGA open-access data retrieval, ii) prepare the data using the appropriate pre-processing strategies, iii) provide the means to carry out different standard analyses and iv) allow the user to download a specific version of the data and thus to easily reproduce earlier research results. In more detail, the package provides multiple methods for analysis (e.g., differential expression analysis, identifying differentially methylated regions) and methods for visualization (e.g., survival plots, volcano plots, starburst plots) in order to easily develop complete analysis pipelines.

TCGAprepare_Affy | Prepare CEL files into an AffyBatch.
TCGAquery_MatchedCoupledSampleTypes | Retrieve multiple tissue types from the same patients.
TCGAquery_recount2 | Query gene counts of TCGA and GTEx data from the Recount2 project
TCGAquery_SampleTypes | Retrieve multiple tissue types not from the same patients.
TCGAquery_subtype | Retrieve molecular subtypes for a given tumor
TCGAtumor_purity | Filters TCGA barcodes according to purity parameters
TCGAvisualize_BarPlot | Barplot of subtypes and clinical info in groups of gene expression clustered.
TCGAvisualize_EAbarplot | barPlot for a complete Enrichment Analysis
TCGAvisualize_Heatmap | Heatmap with more sensible behavior using heatmap.plus
TCGAvisualize_meanMethylation | Mean methylation boxplot
TCGAvisualize_oncoprint | Creating a oncoprint
TCGAvisualize_PCA | Principal components analysis (PCA) plot
TCGAvisualize_starburst | Create starburst plot
TCGAvisualize_SurvivalCoxNET | Survival analysis with univariate Cox regression package (dnet)
TCGAVisualize_volcano | Creates a volcano plot for DNA methylation or expression
TCGA_MolecularSubtype | Retrieve molecular subtypes for given TCGA barcodes
Tumor.purity | TCGA samples with their Tumor Purity measures
UseRaw_afterFilter | Use raw count from the DataPrep object which genes are removed by normalization and filtering steps.