Entering edit mode
8.3 years ago
majuang66
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140
PART I - From Data import to Normalization in Microarray Analysis using in R (Part I)
PART II - From Genefiltering to Results storgae in Microarray Analysis using in R (Part II) - FARMS
I prepared the data from PART II. I think that data presentation is important for understanding the results in large data. I display clustering results through MeV software (free).
From PART II, I selected 212 genes using FARMS and genefiltering (Standard Deviation) at GSE4536 data.
# Open MeV software (version 4.9 - http://www.tm4.org/mev.html)
# File -> Load Data -> Single-color Array select -> mydata_GSE4536_xxx_xxx.txt. text file upload
# Load Annotation Data -> Automatically download -> Homo sapiens -> hgu133plus2
# Expression Table -> first row x first column values click -> Load Click!
# Clustering Click -> Hierarchial Clustering (HC) -> Tree Selection (check Gene Tree and Sample Tree) ->
Distance Metric Selection (Current Metric -> Euclidean Distance) -> Linkage Method (Complete linkage clustering) -> OK click!!
# For identifying significant genes between groups, I perform statistics, SAM analysis.
# Statistics click -> Significance Analysis of Microarrays (SAMs) click -> Two-class unpaired -> Cluster Selection (green - Group 1, blue - Group 2) -> check HC -> Tree Selection (check Gene Tree and Sample Tree) ->
Distance Metric Selection (Current Metric -> Euclidean Distance) -> Linkage Method (Complete linkage clustering) -> OK click!!
# We will show SAM graph and HC as below
# Next, I usually organize top gene list through Excel.
Use the "tutorial" category for these guides.
It would also be useful to provide links for previous part in series (at the top of this post) and next part (at end, if there is one).