Microarray Data Analysis Using BRB-ArrayTools Version 4.2.0 ...

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<strong>Data</strong> filtering optionsGene filters: Gene variation• Fold-change filter: Specify a minimumpercentage of log-expression values which mustmeet a specified fold-change criteria• Log-ratio (or log-intensity) variation filter:Screen genes which do not vary much over theset of samples:1. Significance criterion compares thevariance of each gene against the “average” gene2. Percentile criterion screens a specifiedpercentage of genes with smallest variance66
<strong>Data</strong> filtering optionsGene filters: Gene quality• Missing value filter: Screens out genes whichcontain too many missing values over the set ofsamples• Percent absent filter: For Affymetrix data, canfilter out a probeset if too many expressionvalues had an Absent call• Minimum Intensity: This option is onlyavailable for single channel data. It filters outgenes whose 50 th percentile normalized logintensity is less than the log of the user definedvalue.67
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Microarray Data AnalysisUsing BRB-A
Page 3 and 4:
Part I:What is BRB-ArrayTools?3
Page 5 and 6:
Features of BRB-ArrayTools• Capab
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New to ArrayToolsv4.1• Affy ST ar
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Full Installer• Also available is
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Downloading BRB-ArrayTools• After
Page 13 and 14:
Installing BRB-ArrayTools13
Page 15 and 16: Installing BRB-ArrayTools• Select
Page 17 and 18: Installing BRB-ArrayTools• Procee
Page 19 and 20: Installing BRB-ArrayTools• Instal
Page 21: Excel 2007- loading the add-in• 1
Page 24 and 25: Part II:Getting your data intoBRB-A
Page 26 and 27: Expression data(one or more files)E
Page 28 and 29: Expression dataHorizontally aligned
Page 30 and 31: Gene identifiers• A gene identifi
Page 34 and 35: Experiment descriptorsDescribes the
Page 36 and 37: Gene lists• Genelists are used fo
Page 38 and 39: Gene listsUser-defined text files38
Page 40 and 41: Specify data using thecollate dialo
Page 42 and 43: Affymetrix CEL file importation•
Page 44 and 45: Part III:The collated projectworkbo
Page 46 and 47: [Hands-on instructions][Importing P
Page 52 and 53: • Click “OK”[Hands-on instruc
Page 54 and 55: Collated project workbookOverview
Page 58 and 59: The collated project workbookGene i
Page 60 and 61: The collated project workbookGene a
Page 62 and 63: [Hands-on instructions][Data filter
Page 64 and 65: Data filtering optionsNormalization
Page 68 and 69: Data filtering optionsGene subsets
Page 70 and 71: Scatterplot tools• Scatterplot of
Page 72 and 73: [Optional: Hands-on instructions][S
Page 74 and 75: Analysis Wizard• Finding GenesFin
Page 76 and 77: Tools for finding Genes/Genesetscom
Page 78 and 79: Class Comparison78
Page 80 and 81: Class comparison tool1. Enter the c
Page 82 and 83: Average over replicates• If multi
Page 84 and 85: Find genes lists determined by:84
Page 86 and 87: [Hands-on instructions][Class compa
Page 88 and 89: Class comparison toolMultivariate p
Page 90 and 91: Gene ontology analysis• In the cl
Page 92 and 93: [Hands-on instructions][Significanc
Page 94 and 95: Gene Set ExpressionComparison• Co
Page 96 and 97: Goeman’s s Global test• Tests t
Page 98 and 99: Quantitative trait tool• Selects
Page 100 and 101: Survival Gene Set analysis• This
Page 102 and 103: Hierarchical clustering tools• Cl
Page 104 and 105: [Hands-on instructions - cont’d][
Page 110 and 111: Multidimensional scaling• Rotatin
Page 112 and 113: Analysis Wizard- Prediction• Clas
Page 114 and 115: C1. Gene Selection Criteria• Sele
Page 116 and 117:
C2. Class prediction Methods• Six
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Permutation test• Use a permutati
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Linear classifiers for two classesl
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Diagonal linear discriminant analys
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K-nearest neighbor• May be used f
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Support vector machines(V. Vapnik)
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Prediction Analysis MicroarrayPAM
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[Hands-on instructions ][Class pred
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Included plugins• Analysis of Var
Page 134 and 135:
134
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Further help• We hope this class
Page 138 and 139:
Technical support• For questions
Page 140 and 141:
Feedback on this class• Please fi
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Microarray Data Analysis Using BRB-ArrayTools Version 4.2.0 ...

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