What slots does this object contain? How many probes does the microarray contain? Ask for help about the corresponding class What does the assayData slot contain? Have a look at the method associated to this class What does the exprs method returns? What are the dimensions? Does the expression matrix contains as many rows as the number of cells on the array? Solution is affy. Check the dimensions of the expression matrix dim exprs affy.
Given that the phenoData slot of affy. AnnotatedDataFrame to our affy. Solution pheno. Generate a pseudo image of the first and second arrays using the image function. Solution image affy. Use the function barplot. What can we conclude about the PM and MM values for these probesets? Create an object named affyLog2, which will contain the expression values transformed in logarithmic scale base 2. Display the distribution of the first array using the hist function use the affyLog object.
Use the plotDensity function to display microarray distributions use the affyLog object. Solution Perform a log2 transformation of expression values for the 13 samples affyLog2 Interpretation The first histogram showed the largely asymmetrical distribution of raw expression values. The logarithmic transformation is a classical way to normalize data.
The histogram of log-transformed values gives us a better perception of the distribution, because it emphasizes the lower values. We however notice that this log-transformed distribution is still far from "normal" i. The plot obtained with plotDensity reveals another typical problem: samples differ by the global range of their distribution: some samples have a shifted or wider distribution than other samples.
One reason for normalizing expression data will be to ensure consistency between these distributions. The box plots provide us with a synthetic vision of the distributions across samples. The thick bar indicates the mean value for a given sample, and the rectangle marks the limits of the first and third quartiles. The dotted lines delimited by horizontal bars indicate a confidence interval.
Values falling outside of this interval are considered as "outliers", i. In this case outilers indicate genes expressed at a particularly high level. Note that the level of expression is not a very interesting criterion per se : the goal of this experiment is to detect genes differentially expressed between different cancer types, irrespective of the fact that these genes are expressed at high, intermediate or moderate levels.
What object is returned by rma? Which slots does the object contain? Ask for some help about the class of this object. What are the slot contained within this object? Use the smoothScatter function library geneplotter to compare normalized values from the first and second microarray. Solution is eset? Solution For each array, each probe is compared to its corresponding median signal. Calculate A For older versions of R, please refer to the appropriate Bioconductor release.
To view documentation for the version of this package installed in your system, start R and enter:. Follow Installation instructions to use this package in your R session. Support ». Please read the posting guide. Post questions about Bioconductor to one of the following locations:. Home Bioconductor 3. Makes heavy use of the affy library. Also has some basic scatter plot functions and mechanisms for generating high resolution journal figures To view documentation for the version of this package installed in your system, start R and enter:.
Follow Installation instructions to use this package in your R session. Support ». Please read the posting guide. Post questions about Bioconductor to one of the following locations:.
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