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R

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Kernel: R
options(jupyter.plot_mimetypes ='image/png')

Exercise 1

library(affy)

?mas5

mas5() executes the command for MAS5.0 expression measure. This function converts an instance of AffyBatch into an instance of ExpressionSet using the implementation of Affymetrix's MAS5.0 expression measure. Using mas5(object, normalize = TRUE, sc = 500, analysis = "absolute", ...)

?rma

rma() executes the command for Robust Multi-Array Average expression measure. This function conversts an AffyBatch object into an ExpressionSet object using the RMA expression measure. Using rma(object, subset=NULL, verbose=TRUE, destructive=TRUE, normalize=TRUE, background=TRUE, bgversion=2, ...)

Exercise 2

setwd("~/Autumn2016/Week4/data_wk4")

getwd()
[1] "/projects/ddda6a8e-2bca-47f5-b1d6-79b2c48d0e30/Autumn2016/Week4/data_wk4"

Exercise 3

load("Dilution.RDA")

show(Dilution)
AffyBatch object size of arrays=640x640 features (35221 kb) cdf=HG_U95Av2 (12625 affyids) number of samples=4 number of genes=12625 annotation=hgu95av2 notes=

The data shows the size of the array is 640x640 (35221kb), cdf maps each gene that is in the array (12625 genes), and there are 4 samples.

Exercise 4

eset_rma<-rma(Dilution)
head(eset_rma)
Background correcting Normalizing Calculating Expression
ExpressionSet (storageMode: lockedEnvironment) assayData: 1 features, 4 samples element names: exprs protocolData: none phenoData sampleNames: 20A 20B 10A 10B varLabels: liver sn19 scanner varMetadata: labelDescription featureData: none experimentData: use 'experimentData(object)' Annotation: hgu95av2 
eset_mas5<-mas5(Dilution)
background correction: mas PM/MM correction : mas expression values: mas background correcting...done. 12625 ids to be processed | | |####################| 
e_rma<-exprs(eset_rma)
head(e_rma)
20A 20B 10A 10B 100_g_at 8.039969 7.891522 8.022329 7.910679 1000_at 7.790839 7.661209 7.716827 7.622688 1001_at 5.175568 5.067023 5.082672 5.091804 1002_f_at 5.916532 5.754500 5.816628 5.741990 1003_s_at 6.335194 6.010436 6.198295 6.133995 1004_at 6.390533 6.147808 6.357680 6.260663
e_mas5<-exprs(eset_mas5)
head(e_mas5)
20A 20B 10A 10B 100_g_at 548.98527 433.2680 424.96155 393.97712 1000_at 809.08453 699.3555 808.41458 701.34489 1001_at 70.01311 109.4756 81.87722 90.15127 1002_f_at 161.94720 172.0894 138.57740 166.27219 1003_s_at 52.33766 101.3367 33.09268 31.61867 1004_at 211.22394 148.7227 161.71606 133.46727
par(mfrow=c(1,2))
d1<-density(e_rma)
plot(d1)
d2<-density(e_mas5)
plot(d2)
Image in a Jupyter notebook
par(mfrow=c(1,2))
boxplot(e_rma)
boxplot(e_mas5)
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log2e_mas5<-log2(e_mas5)
head(log2e_mas5)
20A 20B 10A 10B 100_g_at 9.100624 8.759116 8.731189 8.621968 1000_at 9.660147 9.449882 9.658952 9.453980 1001_at 6.129553 6.774465 6.355390 6.494276 1002_f_at 7.339380 7.427014 7.114548 7.377403 1003_s_at 5.709777 6.663013 5.048440 4.982705 1004_at 7.722630 7.216481 7.337319 7.060342
par(mfrow=c(1,2))
log2d<-density(log2e_mas5)
plot(log2d)
boxplot(log2e_mas5)
Image in a Jupyter notebook

Exercise 6

library(puma)
Loading required package: oligo Loading required package: oligoClasses Welcome to oligoClasses version 1.32.0 Attaching package: ‘oligoClasses’ The following object is masked from ‘package:affy’: list.celfiles Loading required package: Biostrings Loading required package: S4Vectors Loading required package: stats4 Loading required package: IRanges Loading required package: XVector ================================================================================ Welcome to oligo version 1.34.2 ================================================================================ Attaching package: ‘oligo’ The following objects are masked from ‘package:affy’: intensity, MAplot, mm, mm<-, mmindex, pm, pm<-, pmindex, probeNames, rma Loading required package: mclust Package 'mclust' version 5.2 Type 'citation("mclust")' for citing this R package in publications. 
setwd("~/Autumn2016/Week4/data_wk4")

load("Dilution.RDA")
show(Dilution)
AffyBatch object size of arrays=640x640 features (35221 kb) cdf=HG_U95Av2 (12625 affyids) number of samples=4 number of genes=12625 annotation=hgu95av2 notes= 
eset_mmgmos<-mmgmos(Dilution)
Model optimising .......................... Expression values calculating .......................... Done. 
e_puma<-exprs(eset_mmgmos)
head(e_puma)
20A 20B 10A 10B 100_g_at 6.001526 5.722812 5.815477 5.307755 1000_at 7.127891 7.079451 7.074755 6.822553 1001_at 4.647841 4.768898 4.076775 4.134697 1002_f_at 5.622159 5.522768 5.307126 5.423579 1003_s_at 1.640298 1.524951 1.961328 1.091461 1004_at 4.719888 4.156653 5.027276 4.164188
par(mfrow=c(1,2))
pumad<-density(e_puma)
plot(pumad)
boxplot(e_puma)
Image in a Jupyter notebook
e_puma[e_puma < 0]<- 0

par(mfrow=c(1,2))
pumad<-density(e_puma)
plot(pumad)
boxplot(e_puma)
Image in a Jupyter notebook
setwd("~/Autumn2016/Week4/data_wk4")

load("affybatch.estrogen.RDA")
show(affybatch.estrogen)
AffyBatch object size of arrays=640x640 features (19 kb) cdf=HG_U95Av2 (12625 affyids) number of samples=8 number of genes=12625 annotation=hgu95av2 notes= 
pData(affybatch.estrogen) <- data.frame(
"estrogen"=c("absent","absent","present","present"
,"absent","absent","present","present")
, "time.h"=c("10","10","10","10","48","48","48","48")
, row.names=rownames(pData(affybatch.estrogen)))

eset_estrogen_mmgmos<-mmgmos(affybatch.estrogen)
Model optimising .......................... Expression values calculating .......................... Done. 
e_puma<-exprs(eset_estrogen_mmgmos)
head(e_puma)
low10-1.cel low10-2.cel high10-1.cel high10-2.cel low48-1.cel 100_g_at 4.5636890 5.0542649 4.3147335 3.323781455 4.1293564 1000_at 7.0441500 6.7470287 6.1633587 6.023999895 5.9510488 1001_at -1.5355806 -1.4367264 -1.9746399 -0.097707515 1.1476384 1002_f_at -1.4571550 -0.9999348 -1.9062753 -1.185054088 -2.2071496 1003_s_at -2.0247799 -0.5052158 -0.1332393 0.889561658 0.6175251 1004_at 0.0781212 0.1790070 -0.3844425 -0.006124629 1.9511443 low48-2.cel high48-1.cel high48-2.cel 100_g_at 4.5447948 4.039069 4.1924974 1000_at 5.9870338 5.940411 5.6196507 1001_at -0.3794378 -2.924452 1.0317169 1002_f_at -1.9164036 -1.300294 -1.9311610 1003_s_at 2.0123121 1.550318 0.5264854 1004_at 1.3045113 2.029137 2.5490697 
detach(package:puma, unload = TRUE)

library(affy)

setwd("~/Autumn2016/Week4/data_wk4")

load("affybatch.estrogen.RDA")
show(affybatch.estrogen)
AffyBatch object size of arrays=640x640 features (19 kb) cdf=HG_U95Av2 (12625 affyids) number of samples=8 number of genes=12625 annotation=hgu95av2 notes= 
eset_estrogen_rma <- rma(affybatch.estrogen)
Error in (function (classes, fdef, mtable) : unable to find an inherited method for function ‘rma’ for signature ‘"AffyBatch"’ Traceback: 1. rma(affybatch.estrogen) 2. (function (classes, fdef, mtable) . { . methods <- .findInheritedMethods(classes, fdef, mtable) . if (length(methods) == 1L) . return(methods[[1L]]) . else if (length(methods) == 0L) { . cnames <- paste0("\"", vapply(classes, as.character, . ""), "\"", collapse = ", ") . stop(gettextf("unable to find an inherited method for function %s for signature %s", . sQuote(fdef@generic), sQuote(cnames)), domain = NA) . } . else stop("Internal error in finding inherited methods; didn't return a unique method", . domain = NA) . })(list(structure("AffyBatch", package = "affy")), structure(function (object, . ...) . standardGeneric("rma"), generic = structure("rma", package = "oligo"), package = "oligo", group = list(), valueClass = character(0), signature = "object", default = `\001NULL\001`, skeleton = (function (object, . ...) . stop("invalid call in method dispatch to 'rma' (no default method)", . domain = NA))(object, ...), class = structure("standardGeneric", package = "methods")), . <environment>) 3. stop(gettextf("unable to find an inherited method for function %s for signature %s", . sQuote(fdef@generic), sQuote(cnames)), domain = NA)