motifStack 1.24.1
A sequence logo, based on information theory, has been widely used as a graphical representation of sequence conservation (aka motif) in multiple amino acid or nucleic acid sequences. Sequence motif represents conserved characteristics such as DNA binding sites, where transcription factors bind, and catalytic sites in enzymes. Although many tools, such as seqlogo1, have been developed to create sequence motif and to represent it as individual sequence logo, software tools for depicting the relationship among multiple sequence motifs are still lacking. We developed a flexible and powerful open-source R/Bioconductor package, motifStack, for visualization of the alignment of multiple sequence motifs.
You will need ghostscript. The full path to the executable can be set using the environment variable R_GSCMD. If this is unset, environment variable gs (Unix, Linux or Mac) or GSC (Window) will be searched by name on your path. If gs/GSC is unset, GhostScript executable “gswi64c.exe” and “gswin32c.exe” are tried sequentially.
Here is an example on Windows assuming that the gswin32c.exe is installed at C:\ Program Files\ gs\ gs9.06\ bin. In a R session, please try:
Sys.setenv(R_GSCMD=file.path("C:", "Program Files", "gs",
"gs9.06", "bin", "gswin32c.exe"))
Users can select different fonts and colors to draw the sequence logo.
suppressPackageStartupMessages(library(motifStack))
pcm <- read.table(file.path(find.package("motifStack"),
"extdata", "bin_SOLEXA.pcm"))
pcm <- pcm[,3:ncol(pcm)]
rownames(pcm) <- c("A","C","G","T")
motif <- new("pcm", mat=as.matrix(pcm), name="bin_SOLEXA")
##pfm object
#motif <- pcm2pfm(pcm)
#motif <- new("pfm", mat=motif, name="bin_SOLEXA")
opar<-par(mfrow=c(4,1))
plot(motif)
#plot the logo with same height
plot(motif, ic.scale=FALSE, ylab="probability")
#try a different font
plot(motif, font="mono,Courier")
#try a different font and a different color group
motif@color <- colorset(colorScheme='basepairing')
plot(motif,font="Times")
par(opar)
To plot a RNA sequence logo, you only need to change the rowname of the matrix from “T” to “U” as follows.
rna <- pcm
rownames(rna)[4] <- "U"
motif <- new("pcm", mat=as.matrix(rna), name="RNA_motif")
plot(motif)
Given that motifStack allows to use any letters as symbols, it can also be used to draw amino acid sequence logos.
library(motifStack)
protein<-read.table(file.path(find.package("motifStack"),"extdata","cap.txt"))
protein<-t(protein[,1:20])
motif<-pcm2pfm(protein)
motif<-new("pfm", mat=motif, name="CAP",
color=colorset(alphabet="AA",colorScheme="chemistry"))
plot(motif)
It can also be used to draw affinity logos given a position specific affinity matrix (PSAM) as described by Foat et al.2.
library(motifStack)
motif<-matrix(
c(
.846, .631, .593, .000, .000, .000, .434, .410, 1.00, .655, .284, .000, .000, .771, .640, .961,
.625, .679, .773, 1.00, 1.00, .000, .573, .238, .397, 1.00, 1.00, .000, .298, 1.00, 1.00, .996,
1.00, 1.00, 1.00, .228, .000, 1.00, 1.00, .597, .622, .630, .000, 1.00, 1.00, .871, .617, 1.00,
.701, .513, .658, .000, .000, .247, .542, 1.00, .718, .686, .000, .000, .000, .595, .437, .970
), nrow=4, byrow = TRUE)
rownames(motif) <- c("A", "C", "G", "T")
motif<-new("psam", mat=motif, name="affinity logo")
plot(motif)
To show multiple motifs on the same canvas as a sequence logo stack, the distance of motifs need to be calculated first. By default, MotIV3::motifDistances
( R implementation of STAMP4) is used to calculate the distance. After alignment, users can use plotMotifLogoStack
, plotMotifLogoStackWithTree
or plotMotifStackWithRadialPhylog
to draw sequence logos in different layouts. To make it easy to use, we integrated different functionalities into one workflow function named as motifStack
.
suppressPackageStartupMessages(library(motifStack))
#####Input#####
motifs<-importMatrix(dir(file.path(find.package("motifStack"), "extdata"),"pcm$", full.names = TRUE))
## plot stacks
motifStack(motifs, layout="stack", ncex=1.0)
motif2 <- motif
motif2$mat <- motif$mat[, 5:12]
motif2$name <- "logo2"
psamMotifs <- list(motif, motif2)
motifStack(psamMotifs)
## plot stacks with hierarchical tree
motifStack(motifs, layout="tree")
## When the number of motifs is too much to be shown in a vertical stack,
## motifStack can draw them in a radial style.
## random sample from MotifDb
library("MotifDb")
## See system.file("LICENSE", package="MotifDb") for use restrictions.
matrix.fly <- query(MotifDb, "Dmelanogaster")
motifs2 <- as.list(matrix.fly)
## use data from FlyFactorSurvey
motifs2 <- motifs2[grepl("Dmelanogaster\\-FlyFactorSurvey\\-",
names(motifs2))]
## format the names
names(motifs2) <- gsub("Dmelanogaster_FlyFactorSurvey_", "",
gsub("_FBgn\\d+$", "",
gsub("[^a-zA-Z0-9]","_",
gsub("(_\\d+)+$", "", names(motifs2)))))
motifs2 <- motifs2[unique(names(motifs2))]
pfms <- sample(motifs2, 50)
## creat a list of object of pfm
motifs2 <- lapply(names(pfms),
function(.ele, pfms){new("pfm",mat=pfms[[.ele]], name=.ele)}
,pfms)
## trim the motifs
motifs2 <- lapply(motifs2, trimMotif, t=0.4)
## setting colors
library(RColorBrewer)
color <- brewer.pal(12, "Set3")
## plot logo stack with radial style
motifStack(motifs2, layout="radialPhylog",
circle=0.3, cleaves = 0.2,
clabel.leaves = 0.5,
col.bg=rep(color, each=5), col.bg.alpha=0.3,
col.leaves=rep(color, each=5),
col.inner.label.circle=rep(color, each=5),
inner.label.circle.width=0.05,
col.outer.label.circle=rep(color, each=5),
outer.label.circle.width=0.02,
circle.motif=1.2,
angle=350)
We can also plot a sequence logo cloud for DNA motifs.
## assign groups for motifs
groups <- rep(paste("group",1:5,sep=""), each=10)
names(groups) <- names(pfms)
## assign group colors
group.col <- brewer.pal(5, "Set3")
names(group.col)<-paste("group",1:5,sep="")
## use MotIV to calculate the distances of motifs
jaspar.scores <- MotIV::readDBScores(file.path(find.package("MotIV"),
"extdata",
"jaspar2010_PCC_SWU.scores"))
d <- MotIV::motifDistances(lapply(pfms, pfm2pwm))
hc <- MotIV::motifHclust(d, method="average")
## convert the hclust to phylog object
phylog <- hclust2phylog(hc)
## reorder the pfms by the order of hclust
leaves <- names(phylog$leaves)
pfms <- pfms[leaves]
## create a list of pfm objects
pfms <- lapply(names(pfms), function(.ele, pfms){
new("pfm",mat=pfms[[.ele]], name=.ele)}
,pfms)
## extract the motif signatures
motifSig <- motifSignature(pfms, phylog, groupDistance=0.01, min.freq=1)
## draw the motifs with a tag-cloud style.
motifCloud(motifSig, scale=c(6, .5),
layout="rectangles",
group.col=group.col,
groups=groups,
draw.legend=TRUE)
Grouped sequence logo can also be plotted in radial phylogeny tree style.
## get the signatures from object of motifSignature
sig <- signatures(motifSig)
## set the inner-circle color for each signature
gpCol <- sigColor(motifSig)
## plot the logo stack with radial style.
plotMotifStackWithRadialPhylog(phylog=phylog, pfms=sig,
circle=0.4, cleaves = 0.3,
clabel.leaves = 0.5,
col.bg=rep(color, each=5), col.bg.alpha=0.3,
col.leaves=rep(rev(color), each=5),
col.inner.label.circle=gpCol,
inner.label.circle.width=0.03,
angle=350, circle.motif=1.2,
motifScale="logarithmic")
We can also plot it with circos style. In circos style, we can plot two group of motifs and with multiple color rings.
## plot the logo stack with cirsoc style.
motifCircos(phylog=phylog, pfms=pfms, pfms2=sig,
col.tree.bg=rep(color, each=5), col.tree.bg.alpha=0.3,
col.leaves=rep(rev(color), each=5),
col.inner.label.circle=gpCol,
inner.label.circle.width=0.03,
col.outer.label.circle=gpCol,
outer.label.circle.width=0.03,
r.rings=c(0.02, 0.03, 0.04),
col.rings=list(sample(colors(), 50),
sample(colors(), 50),
sample(colors(), 50)),
angle=350, motifScale="logarithmic")
We can also plot the motifs in pile style. In pile style, we can plot two group of motifs with multiple types of annotation.
## plot the logo stack with pile style.
motifPiles(phylog=phylog, pfms=pfms, pfms2=sig,
col.tree=rep(color, each=5),
col.leaves=rep(rev(color), each=5),
col.pfms2=gpCol,
r.anno=c(0.02, 0.03, 0.04),
col.anno=list(sample(colors(), 50),
sample(colors(), 50),
sample(colors(), 50)),
motifScale="logarithmic",
plotIndex=TRUE,
groupDistance=0.01)
We can also use motifPiles to plot motifs with a heatmap.
## plot the logo stack with heatmap.
df <- data.frame(A=runif(n = 50), B=runif(n = 50), C=runif(n = 50), D=runif(n = 50))
map2col <- function(x, pal){
rg <- range(x)
pal[findInterval(x, seq(rg[1], rg[2], length.out = length(pal)+1),
all.inside = TRUE)]
}
dl <- lapply(df, map2col, pal=heat.colors(10))
motifPiles(phylog=phylog, pfms=pfms,
col.tree=rep(color, each=5),
col.leaves=rep(rev(color), each=5),
col.pfms2=gpCol,
r.anno=rep(0.02, length(dl)),
col.anno=dl,
motifScale="logarithmic",
plotIndex=TRUE,
groupDistance=0.01)
Interactive plot can be generated using browseMotifs
function which leverages the d3.js library.
All motifs on the plot are draggable and the plot can be easily exported as a Scalable Vector Graphics (SVG) file.
browseMotifs(pfms = pfms, phylog = phylog, layout="tree", yaxis = FALSE, baseWidth=6, baseHeight = 15)
Plot the motifs in radialPhylog layout.
browseMotifs(pfms = pfms, phylog = phylog, layout="radialPhylog", yaxis = FALSE, xaxis = FALSE, baseWidth=6, baseHeight = 15)
Docker container allows software to be packaged into containers which can be run in any platform using a virtual machine called boot2docker. To ease the installation of motifStack and its depencies, we have created a docker image containing all the components needed to run motifStack. Users can download the motifStack docker image using the following code snippet.
cd ~ ## in windows, please try cd c:\\ Users\\ username docker pull jianhong/motifstack:latest mkdir tmp4motifstack ## this will be the share folder for your host and container. docker run -ti --rm -v ${PWD}/tmp4motifstack:/volume/data jianhong/motifstack:latest bash In motifstack:latest docker 1 cd /volume/data 2 git clone https://github.com/jianhong/motifStack.documentation.git 3 cd motifStack.documentation/ 4 cp /usr/bin/matalign app/matalign-v4a 5 cp /usr/bin/phylip/neighbor app/neighbor.app/Contents/MacOS/neighbor 6 R cmd -e "rmarkdown::render('suppFigure2.Rmd')" 7 R cmd -e "rmarkdown::render('suppFigure6.Rmd')"
You will see the test.pdf file in the folder of tmp4motifstack.
sessionInfo()
## R version 3.5.1 RC (2018-06-24 r74929)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 16.04.4 LTS
##
## Matrix products: default
## BLAS: /home/biocbuild/bbs-3.7-bioc/R/lib/libRblas.so
## LAPACK: /home/biocbuild/bbs-3.7-bioc/R/lib/libRlapack.so
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_US.UTF-8 LC_COLLATE=C
## [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
## [7] LC_PAPER=en_US.UTF-8 LC_NAME=C
## [9] LC_ADDRESS=C LC_TELEPHONE=C
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
##
## attached base packages:
## [1] stats4 parallel grid stats graphics grDevices utils
## [8] datasets methods base
##
## other attached packages:
## [1] RColorBrewer_1.1-2 MotifDb_1.22.0 motifStack_1.24.1
## [4] Biostrings_2.48.0 XVector_0.20.0 IRanges_2.14.10
## [7] S4Vectors_0.18.3 ade4_1.7-11 MotIV_1.36.0
## [10] BiocGenerics_0.26.0 grImport_0.9-1 XML_3.98-1.12
## [13] BiocStyle_2.8.2
##
## loaded via a namespace (and not attached):
## [1] Rcpp_0.12.17 highr_0.7
## [3] plyr_1.8.4 compiler_3.5.1
## [5] GenomeInfoDb_1.16.0 bitops_1.0-6
## [7] tools_3.5.1 zlibbioc_1.26.0
## [9] digest_0.6.15 jsonlite_1.5
## [11] evaluate_0.11 lattice_0.20-35
## [13] BSgenome_1.48.0 Matrix_1.2-14
## [15] DelayedArray_0.6.1 yaml_2.1.19
## [17] xfun_0.3 seqLogo_1.46.0
## [19] GenomeInfoDbData_1.1.0 rtracklayer_1.40.3
## [21] stringr_1.3.1 knitr_1.20
## [23] htmlwidgets_1.2 rprojroot_1.3-2
## [25] data.table_1.11.4 Biobase_2.40.0
## [27] BiocParallel_1.14.2 rGADEM_2.28.0
## [29] rmarkdown_1.10 bookdown_0.7
## [31] magrittr_1.5 scales_0.5.0
## [33] MASS_7.3-50 matrixStats_0.53.1
## [35] backports_1.1.2 Rsamtools_1.32.2
## [37] htmltools_0.3.6 GenomicRanges_1.32.6
## [39] GenomicAlignments_1.16.0 SummarizedExperiment_1.10.1
## [41] splitstackshape_1.4.4 colorspace_1.3-2
## [43] stringi_1.2.4 munsell_0.5.0
## [45] RCurl_1.95-4.11
1. Bembom, O. SeqLogo: Sequence logos for dna sequence alignments. R package version 1.5.4 (2006).
2. Foat, B. C., Morozov, A. V. & Bussemaker, H. J. Statistical mechanical modeling of genome-wide transcription factor occupancy data by matrixreduce. Bioinformatics 22, e141–e149 (2006).
3. Mercier, E. & Gottardo, R. MotIV: Motif identification and validation. R package version 1.10.0 (2010).
4. S, M. & PV, B. STAMP: A web tool for exploring dna-binding motif similarities. Nucleic Acids Res. 35(Web Server issue), W253–W258 (2007).