In vladpetyuk/LewyBodies.SN.TopDown: What the package does (short line)

MS-Align

library("LewyBodies.SN.TopDown")
library("vp.misc")
library("msmsTests")

Overview and Normalization

data(msal_human_default)
# subset
# m <- m[rowSums(exprs(m) > 0) > 10,]
# m <- m[,m$subject.type != 'control.2']
# levels(m$subject.type) <- droplevels(m$subject.type)
# digitize
exprs(m)[exprs(m) > 0] <- 1
#
dim(m)
image.lewy.counts(m)

PCA

counts.pca(m, facs=pData(m)[,"prepBatch",drop=F], snms=sampleNames(m))

Test Subject Groups

res <- eset_presence_absence(m, "subject.type", test='g', simulate.p.value=T)
res$p.val.adj <- p.adjust(res$p.value)
sum(res$p.val.adj < 0.05, na.rm=T)
head(res[order(res$p.value),], 10)
hist(res$p.value, 50, col='lightgrey')
res[with(res, p.value < 0.05 & abs(effect) > 0.4),]

# best <- rownames(res)[which.min(res$p.value)]
# plot.lewy.count.feature(m, best)
plot.lewy.count.feature(m, 'AQP4_HUMAN_1_321_4632')
plot.lewy.count.feature(m, 'HBA_HUMAN_2_142_15194')
plot.lewy.count.feature(m, 'BASP1_HUMAN_2_227_22758')
plot.lewy.count.feature(m, 'MBP_HUMAN_1_304_8289')
plot.lewy.count.feature(m, 'MBP_HUMAN_1_304_18519')

hist(res$effect, 100)

vladpetyuk/LewyBodies.SN.TopDown documentation built on May 3, 2019, 6:15 p.m.