Snippets

Dénes Türei LiMa membranes clustering

Created by Dénes Türei last modified
membrane_clustering.r
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#!/usr/bin/env Rscript

# Denes Turei EMBL 2017
# turei.denes@gmail.com

require(dplyr)
require(tidyr)
require(readr)
require(tibble)
require(gplots)

infile <- '171004_matrix_semisupervisedclustering.csv'

d <- suppressMessages(read_csv(infile))

d0 <- d %>%
    group_by(protein, membrane) %>%
    mutate(m = mean(norm_filt__binding)) %>%
    summarise_all(first) %>%
    ungroup() %>%
    select(protein, membrane, m) %>%
    spread(protein, m) %>%
    remove_rownames() %>%
    as.data.frame() %>%
    column_to_rownames('membrane')

dst <- dist(d0)
cl <- hclust(dst, method = 'ward.D2')
mem_ordr <- cl$labels[cl$order]

d_ord <- d %>%
    mutate(
        membrane = factor(membrane, levels = mem_ordr, ordered = TRUE),
        concentration = factor(concentration, levels = c(NA, 2, 5, 10), ordered = TRUE)
    ) %>%
    arrange(membrane, protein, concentration)

d_ord_m <- d_ord %>%
    spread(protein, norm_filt__binding) %>%
    mutate(membrane = paste(membrane, concentration, sep = '_')) %>%
    remove_rownames() %>%
    as.data.frame()

rownames(d_ord_m) <- d_ord_m[,1]
d_ord_m <- d_ord_m[,-c(1,2)]

pal <- colorRampPalette(c("white", "dark blue"), space="rgb")

cairo_pdf('lima_clustering.pdf', width = 18, height = 12)

FDS_heatmap <- heatmap.2(
    as.matrix(t(d_ord_m)),
    Rowv=TRUE,
    Colv=FALSE,
    cexRow=0.6,
    cexCol=0.6,
    symm = FALSE,
    distfun = function(FDS) dist(FDS,method = "euclidean"),
    hclustfun = function(FDS) hclust(FDS,method = "ward.D2"),
    dendrogram = c("row"),
    trace=c("none"),
    colsep=0:ncol(d_ord_m),
    rowsep=0:nrow(d_ord_m),
    sepwidth=c(0.001, 0.001),
    sepcolor="light grey",
    symkey=FALSE,
    keysize = 0.8,
    key.title="none",
    key.xlab="log normalized NBI",
    key.ylab="none",
    key.par=list(cex.lab=1,
                 cex.axis=0.8),
    density.info="none",
    symbreaks=FALSE,
    breaks = seq(0, 2.5, length.out = 60),
    na.color = "grey",
    col = pal(59),
    scale="none",
    margins=c(9,9),
    main="Recruitment of LTP on membrane surrogates",
    xlab = "membranes",
    ylab = "sfGFP fusion proteins"
)

dev.off()

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