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

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Gene ontology analysis• In the class comparison, class prediction,survival analysis, or quantitative traits analysisoutput, the observed vs. expected frequency iscomputed for each Gene Ontology classrepresented in the selected genelist, as well asfor each upstream Gene Ontology class. Bydefault, results are printed only for classesrepresented by at least five genes in the selectedgenelist, and with an observed versus expectedratio of at least 2.90
Class comparisonSignificance Analysis of Microarrays (SAM)• SAM is another popular method for false discoverycontrol, which controls the average proportion offalse discoveries rather than the probability of a givennumber or proportion of false discoveries.• It is a slightly less stringent control than themultivariate permutation test for controlling falsediscoveries used in the other class comparison tools,but is included in BRB-ArrayTools because of itspopularity.91
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Microarray Data AnalysisUsing BRB-A
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Part I:What is BRB-ArrayTools?3
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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
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Installing BRB-ArrayTools13
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Installing BRB-ArrayTools• Select
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Installing BRB-ArrayTools• Procee
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Installing BRB-ArrayTools• Instal
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Excel 2007- loading the add-in• 1
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Part II:Getting your data intoBRB-A
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Expression data(one or more files)E
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Expression dataHorizontally aligned
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Gene identifiers• A gene identifi
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Expression data(one or more files)E
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Experiment descriptorsDescribes the
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Gene lists• Genelists are used fo
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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 56 and 57: Expression data(one or more files)E
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 66 and 67: Data filtering optionsGene filters:
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 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
Page 118 and 119: Permutation test• Use a permutati
Page 120 and 121: Linear classifiers for two classesl
Page 122 and 123: Diagonal linear discriminant analys
Page 124 and 125: K-nearest neighbor• May be used f
Page 126 and 127: Support vector machines(V. Vapnik)
Page 128 and 129: Prediction Analysis MicroarrayPAM
Page 130 and 131: [Hands-on instructions ][Class pred
Page 132 and 133: Included plugins• Analysis of Var
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Page 136 and 137: 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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