Example report using bumphunter results

In regionReport: Generate HTML or PDF reports for a set of genomic regions or DESeq2/edgeR results

r Biocpkg('bumphunter') example

The r Biocpkg('bumphunter') package can be used for methylation analyses where you are interested in identifying differentially methylated regions. The vignette explains in greater detail the data set we are using in this example.

## Load bumphunter
library("bumphunter")

## Create data from the vignette
pos <- list(
    pos1 = seq(1, 1000, 35),
    pos2 = seq(2001, 3000, 35),
    pos3 = seq(1, 1000, 50)
)
chr <- rep(paste0("chr", c(1, 1, 2)), times = sapply(pos, length))
pos <- unlist(pos, use.names = FALSE)

## Find clusters
cl <- clusterMaker(chr, pos, maxGap = 300)

## Build simulated bumps
Indexes <- split(seq_along(cl), cl)
beta1 <- rep(0, length(pos))
for (i in seq(along = Indexes)) {
    ind <- Indexes[[i]]
    x <- pos[ind]
    z <- scale(x, median(x), max(x) / 12)
    beta1[ind] <- i * (-1)^(i + 1) * pmax(1 - abs(z)^3, 0)^3 ## multiply by i to vary size
}

## Build data
beta0 <- 3 * sin(2 * pi * pos / 720)
X <- cbind(rep(1, 20), rep(c(0, 1), each = 10))
set.seed(23852577)
error <- matrix(rnorm(20 * length(beta1), 0, 1), ncol = 20)
y <- t(X[, 1]) %x% beta0 + t(X[, 2]) %x% beta1 + error

## Perform bumphunting
tab <- bumphunter(y, X, chr, pos, cl, cutoff = .5)

## Explore data
lapply(tab, head)

Once we have the regions we can proceed to build the required GRanges object.

library("GenomicRanges")

## Build GRanges with sequence lengths
regions <- GRanges(
    seqnames = tab$table$chr,
    IRanges(start = tab$table$start, end = tab$table$end),
    strand = "*", value = tab$table$value, area = tab$table$area,
    cluster = tab$table$cluster, L = tab$table$L, clusterL = tab$table$clusterL
)

## Assign chr lengths
seqlengths(regions) <- seqlengths(
    getChromInfoFromUCSC("hg19", as.Seqinfo = TRUE)
)[
    names(seqlengths(regions))
]

## Explore the regions
regions

Now that we have identified a set of differentially methylated regions we can proceed to creating the HTML report. Note that this report has less information than the DiffBind example because we don't have a p-value variable.

## Load regionReport
library("regionReport")

## Now create the report
report <- renderReport(regions, "Example bumphunter",
    pvalueVars = NULL,
    densityVars = c(
        "Area" = "area", "Value" = "value",
        "Cluster Length" = "clusterL"
    ), significantVar = NULL,
    output = "bumphunter-example", outdir = "bumphunter-example",
    device = "png"
)

You can view the final report at bumphunter-example/bumphunter-example.html or here.

In case the link does not work, a pre-compiled version of this document and its corresponding report are available at leekgroup.github.io/regionReportSupp/.

Reproducibility

## Date generated:
Sys.time()

## Time spent making this page:
proc.time()

## R and packages info:
options(width = 120)
sessioninfo::session_info()

regionReport documentation built on Dec. 20, 2020, 2:01 a.m.