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Rebuilt second vignette and added it to package.
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‎.Rbuildignore‎

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^doc$
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^Meta$
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^exampledata$
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^vignettes/IntegratingMultiomics\.Rmd$

‎vignettes/IntegratingMultiomics.R‎

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## ----options, include = FALSE-------------------------------------------------
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knitr::opts_chunk$set(
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collapse = TRUE,
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comment = "##>"
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)
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## ----bulkAnalyseR, include=FALSE----------------------------------------------
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library("bulkAnalyseR")
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## ----load Yang 2019 mRNAseq---------------------------------------------------
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exp.yang <- read.csv(
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system.file("extdata", "expression_matrix_preprocessed.csv", package = "bulkAnalyseR"),
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row.names = 1) %>% as.matrix
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head(exp.yang)
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## ----metadata-----------------------------------------------------------------
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meta <- data.frame(
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srr = colnames(exp.yang),
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timepoint = rep(c("0h", "12h", "36h"), each = 2)
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)
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## ----convert type, include = FALSE, eval = FALSE------------------------------
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# meta$srr = as.character(meta$srr)
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# meta$timepoint = as.character(meta$timepoint)
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## ----str gene expression------------------------------------------------------
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str(exp.yang)
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str(meta)
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## ----gene table coord---------------------------------------------------------
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gene.coord.table <- read.csv(
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url('https://raw.githubusercontent.com/Core-Bioinformatics/bulkAnalyseR/master/exampledata/Yang2019_ChIP/gene_coords_GRCm38.p6.csv'),
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row.names = 1)
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str(gene.coord.table)
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## ----chip coord table---------------------------------------------------------
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chip.coord.table <- read.csv(
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url('https://raw.githubusercontent.com/Core-Bioinformatics/bulkAnalyseR/master/exampledata/Yang2019_ChIP/ChIP_peak_coords.csv'),
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row.names = 1)
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str(chip.coord.table)
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## -----------------------------------------------------------------------------
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cis.integration <- tibble::tibble(
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reference.expression.matrix = 'exp.yang',
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reference.org.db = 'org.Mm.eg.db',
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reference.coord = 'gene.coord.table',
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comparison.coord = 'chip.coord.table',
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reference.table.name = 'mRNAseq',
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comparison.table.name = 'ChIPseq'
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)
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## ----generate cis app, eval=FALSE---------------------------------------------
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# generateShinyApp(
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# expression.matrix = exp.yang,
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# metadata = meta,
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# modality = "RNA",
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# shiny.dir = "shiny_Yang2019_CisIntegration",
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# app.title = "Shiny app for visualisation of three timepoints from the Yang 2019 data",
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# organism = "mmusculus",
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# org.db = "org.Mm.eg.db",
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# cis.integration = cis.integration
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# )
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# shiny::runApp('shiny_Yang2019_CisIntegration')
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## ----CisIntegration, echo = FALSE, out.width = "80%"--------------------------
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knitr::include_graphics("figures/CisIntegrationExample.png")
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## ----yang multiple modality, eval= FALSE--------------------------------------
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# exp.chip <- read.csv(
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# url('https://raw.githubusercontent.com/Core-Bioinformatics/bulkAnalyseR/master/exampledata/Yang2019_ChIP/ChIP_expression_matrix_preprocessed.csv'),
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# row.names = 1) %>% as.matrix
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# meta.chip = data.frame(
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# id = colnames(exp.chip),
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# timepoint = c('0h','12h','36h')
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# )
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# cis.integration.2 <- tibble::tibble(
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# reference.expression.matrix = c('exp.yang','exp.chip'),
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# reference.org.db = c('org.Mm.eg.db','NULL'),
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# reference.coord = c('gene.coord.table','chip.coord.table'),
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# comparison.coord = c('chip.coord.table','gene.coord.table'),
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# reference.table.name = c('mRNAseq','ChIPseq'),
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# comparison.table.name = c('ChIPseq','mRNAseq')
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# )
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# generateShinyApp(
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# expression.matrix = list(exp.yang,exp.chip),
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# metadata = list(meta,meta.chip),
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# modality = c('RNA','ChIP'),
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# shiny.dir = "shiny_Yang2019_CisIntegration2",
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# app.title = "Shiny app for visualisation of three timepoints from the Yang 2019 data",
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# organism = list("mmusculus",NA),
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# org.db = list("org.Mm.eg.db",NA),
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# cis.integration = cis.integration.2
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# )
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# shiny::runApp('shiny_Yang2019_CisIntegration2')
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## ----li data------------------------------------------------------------------
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exp.mirna <- read.csv(
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url('https://raw.githubusercontent.com/Core-Bioinformatics/bulkAnalyseR/master/exampledata/Li2021_miRNA_mRNA/expression_matrix_miRNA_preprocessed.csv'),
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row.names = 1) %>% as.matrix
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str(exp.mirna)
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exp.mrna <- read.csv(
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url('https://raw.githubusercontent.com/Core-Bioinformatics/bulkAnalyseR/master/exampledata/Li2021_miRNA_mRNA/expression_matrix_mRNA_preprocessed.csv'),
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row.names = 1) %>% as.matrix
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str(exp.mrna)
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meta.trans = data.frame(id = paste0(rep(c('control_','IDD_'),each = 3),1:3),
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rep = rep(1:3,2),
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type = rep(c('control','IDD'),each = 3))
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meta.trans
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## ----li trans app, eval=FALSE-------------------------------------------------
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# generateShinyApp(
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# shiny.dir = 'shiny_Li_2021',
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# app.title = 'Li 2021 Trans Regulatory Example',
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# modality=list('mRNA','miRNA'),
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# metadata = meta.trans,
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# expression.matrix = list(exp.mrna,exp.mirna),
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# org.db = list('org.Hs.eg.db',NA),
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# organism=list('hsapiens',NA),
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# trans.integration = tibble::tibble(
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# reference.expression.matrix='exp.mrna',
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# reference.org.db='org.Hs.eg.db',
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# comparison.expression.matrix='exp.mirna',
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# comparison.org.db='NULL',
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# reference.table.name='mRNA',
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# comparison.table.name='miRNA'
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# )
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# )
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# shiny::runApp('shiny_Li_2021')
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## ----TransIntegration, echo = FALSE, out.width = "80%"------------------------
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knitr::include_graphics("figures/TransIntegrationExample.png")
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## ---- messages = FALSE, eval = FALSE------------------------------------------
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# mirtarbase.comparison.table <- preprocess_miRTarBase(organism.code = 'mmu', org.db = 'org.Mm.eg.db')
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## ---- messages=FALSE, eval=FALSE----------------------------------------------
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# mirtarbase.comparison.table <- preprocess_miRTarBase(
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# organism.code = 'mmu',
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# org.db = 'org.Mm.eg.db',
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# print.support.types = TRUE,
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# print.validation.methods = TRUE
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# )
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## ---- eval=FALSE--------------------------------------------------------------
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# custom.integration <- tibble::tibble(
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# reference.expression.matrix = 'exp.yang',
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# reference.org.db = 'org.Mm.eg.db',
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# comparison.table = 'mirtarbase.comparison.table',
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# reference.table.name = 'RNA',
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# comparison.table.name = 'miRTarBase'
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# )
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# generateShinyApp(
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# expression.matrix = exp.yang,
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# metadata = meta,
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# modality = "RNA",
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# shiny.dir = "shiny_Yang2019_CustomIntegration",
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# app.title = "Shiny app for visualisation of three timepoints from the Yang 2019 data",
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# organism = "mmusculus",
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# org.db = "org.Mm.eg.db",
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# custom.integration = custom.integration
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# )
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# shiny::runApp('shiny_Yang2019_CustomIntegration')
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## ----CustomIntegration, echo = FALSE, out.width = "80%"-----------------------
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knitr::include_graphics("figures/CustomIntegrationExample.png")
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## ----EnrichmentIntegration, echo = FALSE, out.width = "80%"-------------------
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knitr::include_graphics("figures/EnrichmentIntegrationExample.png")
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## ----sessionInfo--------------------------------------------------------------
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sessionInfo()
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‎vignettes/IntegratingMultiomics.Rmd‎

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As an example, we consider a subset of the mRNAseq and h3k4me3 ChIPseq data from an experiment included in [a 2019 paper by Yang et al](https://www.sciencedirect.com/science/article/pii/S2405471219301152). The preprocessed mRNAseq data is included in the *bulkAnalyseR* package and can be loaded by running:
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```{r bulkAnalyseR, include=FALSE}
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devtools::load_all('../')
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library("bulkAnalyseR")
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```
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```{r load Yang 2019 mRNAseq}

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