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## ----include=FALSE--------------------------------------------------------------
library(knitr)
opts_chunk$set(concordance = TRUE, comment = NA)
options(scipen = 1, digits = 2, warn = -1, width = 82)
## ----Install,message=FALSE,eval=FALSE-------------------------------------------
# if (!requireNamespace("BiocManager", quietly = TRUE))
# install.packages("BiocManager")
# BiocManager::install("ASpediaFI")
## ----LoadPackage,message=FALSE--------------------------------------------------
#Load the ASpediaFI package
library(ASpediaFI)
names(getSlots("ASpediaFI"))
## ----detectEvent,message=FALSE--------------------------------------------------
#Create ASpediaFI object
bamWT <- system.file("extdata/GSM3167290.subset.bam", package = "ASpediaFI")
GSE114922.ASpediaFI <- ASpediaFI(sample.names = "GSM3167290",
bam.files = bamWT, conditions = "WT")
#Detect and annotate AS events from a subset of the hg38 GTF file
gtf <- system.file("extdata/GRCh38.subset.gtf", package = "ASpediaFI")
GSE114922.ASpediaFI <- annotateASevents(GSE114922.ASpediaFI,
gtf.file = gtf, num.cores = 1)
sapply(events(GSE114922.ASpediaFI), length)
head(events(GSE114922.ASpediaFI)$SE)
## ----quantifyEvent,message=FALSE------------------------------------------------
#Compute PSI values of AS events
GSE114922.ASpediaFI <- quantifyPSI(GSE114922.ASpediaFI, read.type = "paired",
read.length = 100, insert.size = 300,
min.reads = 3, num.cores = 1)
tail(assays(psi(GSE114922.ASpediaFI))[[1]])
## ----loadData,message=FALSE-----------------------------------------------------
#Load PSI and gene expression data
data("GSE114922.fpkm")
data("GSE114922.psi")
#Update the "samples" and "psi" fields
psi(GSE114922.ASpediaFI) <- GSE114922.psi
samples(GSE114922.ASpediaFI) <- as.data.frame(colData(GSE114922.psi))
head(samples(GSE114922.ASpediaFI))
## ----prepareQuery,message=FALSE-------------------------------------------------
#Choose query genes based on differential expression
library(limma)
design <- cbind(WT = 1, MvsW = samples(GSE114922.ASpediaFI)$condition == "MUT")
fit <- lmFit(log2(GSE114922.fpkm + 1), design = design)
fit <- eBayes(fit, trend = TRUE)
tt <- topTable(fit, number = Inf, coef = "MvsW")
query <- rownames(tt[tt$logFC > 1 &tt$P.Value < 0.1,])
head(query)
## ----analyzeFI,message=FALSE,fig.height=5,fig.cap="Cross-validation performance of DRaWR",fig.pos="H"----
#Perform functional interaction analysis of AS events
GSE114922.ASpediaFI <- analyzeFI(GSE114922.ASpediaFI, query = query,
expr = GSE114922.fpkm, restart = 0.9,
num.folds = 5, num.feats = 200,
low.expr = 1, low.var = 0, prop.na = 0.05,
prop.extreme = 1, cor.threshold = 0.3)
## ----tables,message=FALSE-------------------------------------------------------
#Table of AS nodes in the final subnetwork
as.table(GSE114922.ASpediaFI)[1:5,]
#Table of GS nodes in the final subnetwork
pathway.table(GSE114922.ASpediaFI)[1:5,]
## ----Network,message=FALSE------------------------------------------------------
#Extract AS-gene interactions from the final subnetwork
library(igraph)
edges <- as_data_frame(network(GSE114922.ASpediaFI))
AS.gene.interactions <- edges[edges$type == "AS", c("from", "to")]
head(AS.gene.interactions)
## ----Export,message=FALSE-------------------------------------------------------
#Export a pathway-specific subnetwork to GML format
exportNetwork(GSE114922.ASpediaFI, node = "HALLMARK_HEME_METABOLISM",
file = "heme_metabolism.gml")
## ----VizAS,message=FALSE,fig.pos="H",fig.cap="AS event visualization",fig.height=5.5----
#Check if any event on the HMBS gene is included in the final subnetwork
as.nodes <- as.table(GSE114922.ASpediaFI)$EventID
HMBS.event <- as.nodes[grep("HMBS", as.nodes)]
#Visualize event
visualize(GSE114922.ASpediaFI, node = HMBS.event, zoom = FALSE)
## ----VizGS,message=FALSE,fig.pos="H",fig.cap="Pathway visulization",fig.height=5----
#Visualize nework pertaining to specific pathway
visualize(GSE114922.ASpediaFI, node = "HALLMARK_HEME_METABOLISM", n = 10)
## ----sessionInfo----------------------------------------------------------------
sessionInfo()
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