Programação
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Introduction to gene expression technology/Introduction to R
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Homework is due in 2 weeks from today and there’s two parts. First part is generating plots from the first 3 lectures. The other half involves bioinformatics analysis. The dataset has ~38 patients and ~28000 data sets. Need to find the outlier(s). The code is done in the first 3 lectures.
Second part, you will use the Spellman dataset. You will use the cdc28 and I won’t give the reference you have to find it yourself. I will give you the function to run some of the problem. Question 11, is right from lecture 3 notes. All the codes are in lecture notes. Q14, you need to cluster the genes and you want to determine the like genes and to fill in the missing data.
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#1-7
source("http://bioconductor.org/biocLite.R")biocLite(“marray”)
library(marray)
data(swirl)
#8-12
biocLite(c(“affy”, “affydata”, “limma”))
library(affy)#loads limma also
library(affydata)
data(Dilution)
Homework #2
Be sure to install sma manually. Need version 0.5.17
http://braju.com/R/repos/sma_0.5.17.tar.gz
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Mariana M.
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Visit GEO and pick a gene expression dataset that contains two different class. Download the data, process, analyze and identify genes that are significantly associated with one class vs. another. Perform a ontology analysis on the genes that are most associated with one class. Present your analysis (methods and results).