## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE
)
library(easylabel)
## ----eval = FALSE-------------------------------------------------------------
# install.packages("easylabel")
# library(easylabel)
## ----eval = FALSE-------------------------------------------------------------
# devtools::install_github("myles-lewis/easylabel")
# library(easylabel)
## ----eval = FALSE-------------------------------------------------------------
# if (!requireNamespace("BiocManager", quietly = TRUE))
# install.packages("BiocManager")
# BiocManager::install("qvalue")
## ----eval = FALSE-------------------------------------------------------------
# BiocManager::install("AnnotationDbi")
# BiocManager::install("org.Hs.eg.db")
## ----eval = FALSE-------------------------------------------------------------
# data(mtcars)
# easylabel(mtcars, x = 'mpg', y = 'wt',
# colScheme = 'royalblue')
## ----scatter1, echo = FALSE, message=FALSE, fig.align='center', out.width='80%', out.extra='style="border: 0;"'----
knitr::include_graphics("scatter1.png")
## ----eval=FALSE---------------------------------------------------------------
# data(mtcars)
#
# p1 <- easylabel(mtcars, x = 'mpg', y = 'wt', col = 'cyl',
# startLabels = rownames(mtcars)[mtcars$gear == 5],
# output_shiny = FALSE) %>%
# layout(yaxis = list(zeroline = FALSE))
#
# p2 <- easylabel(mtcars, x = 'mpg', y = 'drat', col = 'vs',
# colScheme = c("dodgerblue", "orange"),
# startLabels = rownames(mtcars)[mtcars$gear == 5],
# output_shiny = FALSE) %>%
# layout(xaxis = list(zeroline = FALSE))
#
# plotly::subplot(p1, p2, nrows = 2, shareY = TRUE, titleX = TRUE, margin = 0.05)
## ----plotlyOutput, echo = FALSE, message=FALSE, fig.align='center', out.width='80%', out.extra='style="border: 0;"'----
knitr::include_graphics("plotly_output.png")
## ----eval = FALSE-------------------------------------------------------------
# easylabel(mtcars, x = 'mpg', y = 'wt',
# col = 'cyl')
## ----eval = FALSE-------------------------------------------------------------
# # gapminder data set
# if(!require(gapminder)) {install.packages("gapminder")}
# library(gapminder)
# easylabel(gapminder[gapminder$year == 2007, ], x = 'gdpPercap', y = 'lifeExp',
# col = 'continent', shape = 'continent',
# size = 10,
# labs = 'country',
# zeroline = FALSE)
## ----scatter3, echo = FALSE, message=FALSE, fig.align='center', out.width='80%', out.extra='style="border: 0;"'----
knitr::include_graphics("scatter3.png")
## ----eval = FALSE-------------------------------------------------------------
# library(gapminder)
# easylabel(gapminder[gapminder$year == 2007, ], x = 'gdpPercap', y = 'lifeExp',
# col = 'continent', labs = 'country',
# size = 'pop',
# alpha = 0.6,
# zeroline = FALSE)
## ----bubble, echo = FALSE, message=FALSE, fig.align='center', out.width='80%', out.extra='style="border: 0;"'----
knitr::include_graphics("bubble.png")
## ----eval = FALSE-------------------------------------------------------------
# easylabel(xymatrix, x = 'x', y = 'y', col = 'col',
# colScheme = c('darkgrey', 'green3', 'gold3', 'blue'),
# xlab = expression("log"[2] ~ " fold change post-Rituximab"),
# ylab = expression("log"[2] ~ " fold change post-Tocilizumab"),
# showgrid = TRUE)
## ----plot1, echo = FALSE, message=FALSE, fig.align='center', out.width='80%', out.extra='style="border: 0;"'----
knitr::include_graphics("plot1.png")
## ----eval = FALSE-------------------------------------------------------------
# # example axis ticks
# if(!require(gapminder)) {install.packages("gapminder")}
# library(gapminder)
# easylabel(gapminder[gapminder$year == 2007, ], x = 'gdpPercap', y = 'lifeExp',
# col = 'continent', shape = 'continent',
# size = 10,
# labs = 'country',
# zeroline = FALSE,
# xaxp = c(0, 50000, 10),
# yaxp = c(40, 85, 9),
# showgrid = TRUE)
## ----eval = FALSE-------------------------------------------------------------
# # example adding a trend line using panel.last
# fit <- lm(xymatrix$y ~ xymatrix$x)
# easylabel(xymatrix, x = 'x', y = 'y', col = 'col',
# colScheme = c('darkgrey', 'green3', 'gold3', 'blue'),
# xlab = expression("log"[2] ~ " fold change post-Rituximab"),
# ylab = expression("log"[2] ~ " fold change post-Tocilizumab"),
# showgrid = TRUE, fullGeneNames = TRUE,
# panel.last = {
# abline(fit, col='red')
# })
## -----------------------------------------------------------------------------
# Example DESeq2 object
head(volc1)
# Example limma object
head(volc2)
## ----eval = FALSE-------------------------------------------------------------
# # Typical DESeq2 workflow
# volc1 <- results(dds)
# easyVolcano(volc1, useQ = TRUE)
## ----eval = FALSE-------------------------------------------------------------
# # Manually specify columns
# easyVolcano(volc1, x = 'log2FoldChange', y = 'pvalue', padj = 'padj')
#
# # To use nominal unadjusted p value for significant genes
# easyVolcano(volc1, x = 'log2FoldChange', y = 'pvalue')
## ----eval = FALSE-------------------------------------------------------------
# easyMAplot(volc2, useQ = TRUE)
## ----easyMAplot1, echo = FALSE, message=FALSE, fig.align='center', out.width='80%', out.extra='style="border: 0;"'----
knitr::include_graphics("MAplot1.png")
## ----eval = FALSE-------------------------------------------------------------
# BiocManager::install("AnnotationDbi")
# BiocManager::install("org.Hs.eg.db")
# easyVolcano(volc1, useQ = TRUE, fullGeneNames = TRUE)
## ----table1, echo = FALSE, message=FALSE, fig.align='center', out.width='100%', out.extra='style="border: 0;"'----
knitr::include_graphics("table1.png")
## ----eval = FALSE-------------------------------------------------------------
# BiocManager::install("org.Mm.eg.db")
# library(org.Mm.eg.db)
# easyVolcano(volc1,
# fullGeneNames = TRUE,
# AnnotationDb = org.Mm.eg.db)
## ----eval = FALSE-------------------------------------------------------------
# easyVolcano(volc2,
# useQ = TRUE,
# fccut = 0,
# main = "Volcano title")
## ----plot7, echo = FALSE, message=FALSE, fig.align='center', out.width='80%', out.extra='style="border: 0;"'----
knitr::include_graphics("plot7.png")
## ----eval = FALSE-------------------------------------------------------------
# easyVolcano(volc1,
# useQ = TRUE, fullGeneNames = TRUE,
# Ltitle = expression(symbol("\254") ~ "Non-responder"),
# Rtitle = expression("Responder" ~ symbol("\256")),
# LRtitle_side = 1,
# cex.lab = 0.9, cex.axis = 0.8,
# fccut = c(1, 2), fdrcutoff = 0.2,
# ylim = c(0, 6), xlim = c(-5, 5),
# colScheme = c('darkgrey', 'blue', 'orange', 'red'))
## ----plot3, echo = FALSE, message=FALSE, fig.align='center', out.width='80%', out.extra='style="border: 0;"'----
knitr::include_graphics("plot3.png")
## ----eval = FALSE-------------------------------------------------------------
# easyVolcano(volc1, y = 'pvalue', padj = 'pvalue', fdrcutoff = 0.01)
## ----eval = FALSE-------------------------------------------------------------
# colScheme <- c('darkgrey', 'blue', 'lightblue', 'orange', 'red')
# easyVolcano(volc1, fccut = 1, fdrcutoff = 0.2,
# ylim = c(0, 6), xlim = c(-5, 5),
# colScheme = colScheme,
# vline = c(-1, 1))
## ----plot4, echo = FALSE, message=FALSE, fig.align='center', out.width='80%', out.extra='style="border: 0;"'----
knitr::include_graphics("plot4.png")
## ----eval = FALSE-------------------------------------------------------------
# library(RColorBrewer)
# colScheme <- c('darkgrey', brewer.pal(9, 'RdYlBu')[c(9:7, 3:1)])
# easyVolcano(volc1, fccut = c(1, 2), fdrcutoff = 0.2,
# ylim = c(0, 6), xlim = c(-5, 5),
# colScheme = colScheme,
# alpha = 0.75, outline_col = NA)
## ----plot5, echo = FALSE, message=FALSE, fig.align='center', out.width='80%', out.extra='style="border: 0;"'----
knitr::include_graphics("plot5.png")
## ----eval = FALSE-------------------------------------------------------------
# colScheme <- c('darkgrey', brewer.pal(9, 'RdYlBu')[c(7:9, 3:1)])
# easyMAplot(volc2, fdrcutoff = c(0.05, 0.01, 0.001), size = 6, useQ = TRUE,
# alpha = 0.75, outline_col = NA,
# colScheme = colScheme)
## ----easyMAplot2, echo = FALSE, message=FALSE, fig.align='center', out.width='80%', out.extra='style="border: 0;"'----
knitr::include_graphics("MAplot2.png")
## ----eval = FALSE-------------------------------------------------------------
# easyVolcano(volc1, labelDir = "horiz")
# easyMAplot(volc1, labelDir = "vert")
## ----labdirs1, echo = FALSE, message=FALSE, fig.show='hold', out.width='48%', out.extra='style="border: 0;"'----
knitr::include_graphics(c("labdir_horiz.png", "labdir_vert.png"))
## ----eval = FALSE-------------------------------------------------------------
# # Simple outlines
# easyVolcano(volc2, useQ = TRUE, fccut = 0,
# rectangles = TRUE)
#
# # Red outlined labels, rounded ends
# easyVolcano(volc2, useQ = TRUE, fullGeneNames = TRUE,
# rectangles = TRUE,
# padding = 5,
# border_radius = 10,
# line_col = 'red',
# border_col = 'red',
# text_col = 'red')
## ----labrect2, echo = FALSE, message=FALSE, fig.show='hold', out.width='80%', out.extra='style="border: 0;"'----
knitr::include_graphics("rect_red_outline.png")
## ----eval = FALSE-------------------------------------------------------------
# # Transparent grey rectangles, rounded ends
# easyMAplot(volc2, fdrcut = c(0.05, 0.01, 0.001), size = 6, useQ = TRUE,
# alpha = 0.75, outline_col = NA,
# fullGeneNames = TRUE,
# colScheme = c('darkgrey', brewer.pal(9, 'RdYlBu')[c(7:9, 3:1)]),
# rectangles = TRUE,
# border_col = NA,
# padding = 5,
# rect_col = adjustcolor('grey', alpha.f = 0.6),
# border_radius = 20)
#
# # White text on black background, no rounding
# easyVolcano(volc2, useQ = TRUE, fullGeneNames = TRUE,
# fccut = 0,
# rectangles = TRUE,
# padding = 4,
# border_radius = 0,
# rect_col = 'black',
# text_col = 'white',
# border_col = NA)
## ----labrect4, echo = FALSE, message=FALSE, fig.show='hold', out.width='80%', out.extra='style="border: 0;"'----
knitr::include_graphics("rect_invert.png")
## ----eval = FALSE-------------------------------------------------------------
# # Label text and label lines match point colours
# easylabel(gapminder[gapminder$year == 2007, ], x = 'gdpPercap', y = 'lifeExp',
# col = 'continent', labs = 'country',
# size = 'pop',
# alpha = 0.6,
# line_col = "match", text_col = "match",
# zeroline = FALSE, showgrid = "y")
## ----labmatch1, echo = FALSE, message=FALSE, fig.show='hold', out.width='80%', out.extra='style="border: 0;"'----
knitr::include_graphics("match1.png")
## ----eval = FALSE-------------------------------------------------------------
# # Rectangle fill colour and label line match point colours, rounded rectangles
# easylabel(gapminder[gapminder$year == 2007, ], x = 'gdpPercap', y = 'lifeExp',
# col = 'continent', labs = 'country',
# size = 'pop',
# alpha = 0.6,
# line_col = "match", text_col = "white",
# rectangles = TRUE, border_col = NA,
# rect_col = "match", border_radius = 20, padding = 5,
# zeroline = FALSE, showgrid = "y")
## ----labmatch2, echo = FALSE, message=FALSE, fig.show='hold', out.width='80%', out.extra='style="border: 0;"'----
knitr::include_graphics("match2.png")
## ----eval = FALSE-------------------------------------------------------------
# # Manhattan plot using SLE GWAS data from Bentham et al 2015
# # FTP download full summary statistics from
# # https://www.ebi.ac.uk/gwas/studies/GCST003156
# library(data.table)
# SLE_gwas <- fread('../bentham_2015_26502338_sle_efo0002690_1_gwas.sumstats.tsv')
# # Simple Manhattan plot
# easyManhattan(SLE_gwas)
#
# # 4 colours for chromosomes
# easyManhattan(SLE_gwas, chromCols = RColorBrewer::brewer.pal(4, 'Paired'))
## ----manhat, echo = FALSE, message=FALSE, fig.show='hold', out.width='80%', out.extra='style="border: 0;"'----
knitr::include_graphics("manhattan.png")
## ----eval = FALSE-------------------------------------------------------------
# # Examples
# # 12 colours for chromosomes, no separate colour for significant points
# easyManhattan(SLE_gwas, chromCols = RColorBrewer::brewer.pal(12, 'Paired'),
# sigCol = NA)
#
# # Label peaks automatically, add horizontal gridlines
# easyManhattan(SLE_gwas, npeaks = 20, showgrid = "y")
#
# # Vertical version
# easyManhattan(SLE_gwas, transpose = TRUE, height = 1000, width = 600)
#
# # Chr1 only
# easyManhattan(SLE_gwas[SLE_gwas$chrom == 1, ])
#
# # Add symbols for the significant SNPs
# easyManhattan(SLE_gwas, chromCols = RColorBrewer::brewer.pal(4, 'Paired'),
# size = 8,
# shape = 'col',
# shapeScheme = c(rep(20, 4), 18))
## ----eval=FALSE---------------------------------------------------------------
# # Create a locus plot over one chromosomal region
# library(plotly)
# p1 = easyManhattan(SLE_gwas[SLE_gwas$chrom == 6 &
# SLE_gwas$pos >= 28e6 &
# SLE_gwas$pos <= 34e6, ],
# output_shiny = FALSE, labs = "rsid",
# startLabels=c("rs115466242", "rs2853999"),
# npeaks = 3)
#
#
#
# # To annotate genes in that region
# source("https://raw.githubusercontent.com/KatrionaGoldmann/BioOutputs/master/R/bio_gene_locations.R")
# library(ggbio)
# library(gginnards)
# library(ggrepel)
# if (! "EnsDb.Hsapiens.v75" %in% rownames(installed.packages()))
# BiocManager::install("EnsDb.Hsapiens.v75")
#
# p2 = bio_gene_locations(6, c(28e6, 34e6),
# subset_genes = c('HLA-F', 'HLA-G', 'HLA-A', 'HLA-E',
# 'HLA-C', 'HLA-B', 'HLA-DRA',
# 'HLA-DRB5', 'HLA-DRB1', 'HLA-DQA1',
# 'HLA-DQB1', 'HLA-DQA2', 'HLA-DQB2',
# 'HLA-DOB', 'HLA-DMB', 'HLA-DMA',
# 'HLA-DOA', 'HLA-DPA1', 'HLA-DPB1'))
#
# plotly::subplot(p1, p2$plotly_location %>% layout(yaxis=list(range=c(0.25, 2))),
# shareY = T, titleX = T, margin=0.05,
# nrows=2, heights=c(0.7, 0.3))
#
## ----locusOutput, echo = FALSE, message=FALSE, fig.align='center', out.width='80%', out.extra='style="border: 0;"'----
knitr::include_graphics("locus.png")