inst/doc/manhattanly.R

In manhattanly: Interactive Q-Q and Manhattan Plots Using 'plotly.js'

## ----setup, include=FALSE, echo=TRUE, message=FALSE---------------------------
# library(plotly)
#library(manhattanly)
library(knitr)
options(rmarkdown.html_vignette.check_title = FALSE)
knitr::opts_chunk$set(echo = TRUE, 
                      eval=TRUE,
                      tidy = FALSE, 
                      cache = FALSE, 
                      warning = FALSE,
                      message = FALSE,
                      dpi = 60)
                      #comment = "#>")
#knitr::opts_knit$set(eval.after = 'fig.cap')

## ---- message=TRUE, eval=TRUE-------------------------------------------------
# load the manhattanly library
library(manhattanly)
set.seed(12345)
HapMap.subset <- subset(HapMap, CHR %in% 4:7)
# for highlighting SNPs of interest
significantSNP <- sample(HapMap.subset$SNP, 20)
head(HapMap.subset)
dim(HapMap.subset)

## ---- eval=FALSE--------------------------------------------------------------
#  manhattanly(HapMap.subset, snp = "SNP", gene = "GENE")

## ---- eval=FALSE--------------------------------------------------------------
#  qqly(HapMap.subset, snp = "SNP", gene = "GENE")

## ---- eval=FALSE--------------------------------------------------------------
#  volcanoly(HapMap.subset, snp = "SNP", gene = "GENE", effect_size = "EFFECTSIZE")

## ---- eval=FALSE--------------------------------------------------------------
#  manhattanly(HapMap.subset, snp = "SNP", gene = "GENE", highlight = significantSNP)

## ---- eval = FALSE------------------------------------------------------------
#  manhattanly(HapMap.subset, snp = "SNP", gene = "GENE",
#              annotation1 = "DISTANCE", annotation2 = "EFFECTSIZE",
#              highlight = significantSNP)

## ---- eval=FALSE--------------------------------------------------------------
#  library(magrittr)
#  
#  p <- manhattanly(HapMap.subset, snp = "SNP", gene = "GENE",
#              annotation1 = "DISTANCE", annotation2 = "EFFECTSIZE",
#              highlight = significantSNP)
#  
#  # get the x and y coordinates from the pre-processed data
#  plotData <- manhattanr(HapMap.subset, snp = "SNP", gene = "GENE")[["data"]]
#  
#  # annotate the smallest p-value
#  annotate <- plotData[which.min(plotData$P),]
#  
#  # x and y coordinates of SNP with smallest p-value
#  xc <- annotate$pos
#  yc <- annotate$logp
#  
#  p %>% plotly::layout(annotations = list(
#    list(x = xc, y = yc,
#         text = paste0(annotate$SNP,"<br>","GENE: ",annotate$GENE),
#         font = list(family = "serif", size = 10))))
#  

## ---- eval=FALSE, echo=TRUE---------------------------------------------------
#  Sys.setenv("plotly_username"="your_plotly_username")
#  Sys.setenv("plotly_api_key"="your_api_key")

## ---- eval=FALSE--------------------------------------------------------------
#  library(plotly)
#  # p is the interactive manhattan plot we saved earlier
#  plotly::api_create(p, filename = "r-docs/manhattan", world_readable=TRUE)

## -----------------------------------------------------------------------------
# create an object of class `manhattanr`
manhattanrObject <- manhattanr(HapMap)

# whats in there
str(manhattanrObject)

# the data used for plotting is a data.frame
# this data.frame can be used with any graphics function such as in base R
# you do not need to use plotly
head(manhattanrObject[["data"]])
is.data.frame(manhattanrObject[["data"]])

## ---- eval=FALSE--------------------------------------------------------------
#  manhattanly(manhattanrObject)

## -----------------------------------------------------------------------------
# create an object of class `manhattanr`
manhattanrObject <- manhattanr(HapMap, snp = "SNP", gene = "GENE",
            annotation1 = "DISTANCE", annotation2 = "EFFECTSIZE")

# the annotation columns are now part of the data.frame
head(manhattanrObject[["data"]])
is.data.frame(manhattanrObject[["data"]])

## -----------------------------------------------------------------------------
qqrObject <- qqr(HapMap)
str(qqrObject)
head(qqrObject[["data"]])

## ---- eval=FALSE--------------------------------------------------------------
#  qqly(qqrObject)

## -----------------------------------------------------------------------------
volcanorObject <- volcanor(HapMap, 
                        p = "P",
                        effect_size = "EFFECTSIZE",
                        snp = "SNP",
                        gene = "GENE")
str(volcanorObject)
head(volcanorObject[["data"]])

## ---- eval=FALSE--------------------------------------------------------------
#  volcanoly(volcanorObject, effect_size_line = c(-1, 0.5))