Sample A: Cover Page of Thesis, Project, or Dissertation Proposal

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A Priori Prediction.................................................................................................................................55 Discussion .................................................................................................................................................58 Inside the Black Box .............................................................................................................................59 Transcript Regions Identified by Signal Probesets................................................................................61 A Priori Prediction.................................................................................................................................63 Modified CDFs for Computational Efficiency......................................................................................63 Sample Cleansing..................................................................................................................................64 Platform Enabled Analysis Flexibility ..................................................................................................64 Conclusion.................................................................................................................................................65 Chapter 3: Down Selection .........................................................................................................................66 Materials and Methods..............................................................................................................................67 Data .......................................................................................................................................................67 Data Analysis Overview........................................................................................................................68 Probe Cleansing Methods......................................................................................................................69 Down-Selection.....................................................................................................................................70 Published Candidate Gene Lists............................................................................................................72 Classification.........................................................................................................................................73 Results .......................................................................................................................................................75 Down Selection .....................................................................................................................................75 Models and Class Predictions................................................................................................................77 Author’s List (Validation) .....................................................................................................................80 Discussion .................................................................................................................................................83 Models and Class Predictions................................................................................................................83 Author’s List (Validation) .....................................................................................................................86 Conclusion.................................................................................................................................................90 Chapter 4: Data Mining.............................................................................................................................92 Materials and Methods..............................................................................................................................93 Feature Selection ...................................................................................................................................94 Survival Curves .....................................................................................................................................95 Classifiers and AUC Performance Metrics............................................................................................95 Results .......................................................................................................................................................96 Latent Structure.....................................................................................................................................96 The ‘On’ and ’Off’ Category of ProbeSets..........................................................................................100 Bonferroni Feature Selection Characteristics ......................................................................................105 Discussion ...............................................................................................................................................108 Conclusion...............................................................................................................................................112 Chapter 5: Data Mining the Multiclass Dataset ....................................................................................114 Materials and Methods............................................................................................................................115 Results .....................................................................................................................................................118 Discussion ...............................................................................................................................................123 Literature Validation of Biological Process ........................................................................................125 vi
Conclusion...............................................................................................................................................129 BIBLIOGRAPHY .....................................................................................................................................149 BIBLIOGRAPHY .....................................................................................................................................150 CURRICULUM VITAE ...........................................................................................................................172 vii
Page 1 and 2: An Adenocarcinoma Case Study of the
Page 3 and 4: DEDICATION The work presented in th
Page 5: TABLE OF CONTENTS LIST OF TABLES ..
Page 9 and 10: LIST OF FIGURES Figure Page Figure
Page 11 and 12: violate the linear correlation rela
Page 13 and 14: Chapter 1: An Introduction to Micro
Page 15 and 16: previously stated, rigorous reagent
Page 17 and 18: Factors influencing Signal Interpre
Page 19 and 20: likelihood that no such structural
Page 21 and 22: hybridization and multiple dye stra
Page 23 and 24: classical reaction equations, modif
Page 25 and 26: prevent the hybridization of probes
Page 27 and 28: platforms are used to deposit them
Page 29 and 30: and chip layout [64]. In particular
Page 31 and 32: whether analyses based upon individ
Page 33 and 34: The process of determining a candid
Page 35 and 36: implemented in order to demonstrate
Page 37 and 38: affecting probe-target duplex forma
Page 39 and 40: It has long been known that the var
Page 41 and 42: probes can thus be reincorporated i
Page 43 and 44: (Carr, ms in review). This ProbeFAT
Page 45 and 46: have specific attributes which can
Page 47 and 48: elow saturation. The investigator m
Page 49 and 50: a. A filter based on how many probe
Page 51 and 52: means. The remaining sets possess s
Page 53 and 54: for the 24 samples in the Lu, et al
Page 55 and 56: Table 2.1: Probe Numbers per filter
Page 57 and 58:
the effect can be. Both the type of
Page 59 and 60:
described above. In Figure 2.3, the
Page 61 and 62:
various data processing stages are
Page 63 and 64:
position of the probe on the transc
Page 65 and 66:
Figure 2.5: BaFL consistency. Demon
Page 67 and 68:
Figure 2.6: Probe-Transcript region
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Table 2.3: ProbeSet behavior predic
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cleansing process. This is demonstr
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Table 2.4: ProbeSet behavior of pro
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A Priori Prediction We demonstrated
Page 77 and 78:
Conclusion We have presented a comp
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mind that they are most aware of th
Page 81 and 82:
Probe Cleansing Methods The BaFL pr
Page 83 and 84:
are significant assume such a data
Page 85 and 86:
cleansing process and were assessed
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sample selection, with replacement,
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Figure 3.1: P value distributions.
Page 91 and 92:
Figure 3.2: Down selection models-
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cleansing methods were used to gene
Page 95 and 96:
Discussion A striking result from t
Page 97 and 98:
Figure 3.6: Concordance summary. Th
Page 99 and 100:
whole model analysis without permut
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change, apparently the greater vari
Page 103 and 104:
though in Chapter 2 we showed that
Page 105 and 106:
Although a list of 325 candidate ge
Page 107 and 108:
was determined to consist of 30 Pro
Page 109 and 110:
Figure 4.1: Non-traditional PCA ana
Page 111 and 112:
for the RMA and dCHIP interpretatio
Page 113 and 114:
was one of them: it is counted as p
Page 115 and 116:
Figure 4.5: Kaplan-Meyer survival c
Page 117 and 118:
Figure 4.7: Low grade tumor surviva
Page 119 and 120:
The candidate gene list values were
Page 121 and 122:
ejecting the null hypothesis [8], a
Page 123 and 124:
Figure 4.9: GO connectivity of cand
Page 125 and 126:
under linear and non-linear dimensi
Page 127 and 128:
sample cleansing process and these
Page 129 and 130:
averaged to give a final approximat
Page 131 and 132:
119 Table 5.1: : NSCLC candidate ge
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Figure 5.1: NSCLC ProbeSet gain sel
Page 135 and 136:
Figure 5.3: NSCLC refined average p
Page 137 and 138:
statistical criterion, but it appea
Page 139 and 140:
lacking p53 mutations [30]. While,
Page 141 and 142:
Kruppel-like factor 5 (KLF5) has al
Page 143 and 144:
Appendix A # This is the main drive
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def Driver(usr, pswd, db, logfile,
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def DriverXH(usr, pswd, db, logfile
Page 149 and 150:
fp.write('\tTable '), fp.write(msk[
Page 151 and 152:
#determine outliers lowrs1=nonzero(
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tmp="update sample_mask set exclude
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fp.write('\n'+msk[ptr[j]]+' exclude
Page 157 and 158:
cur, conn=UpdateWorkReg(cur, conn,
Page 159 and 160:
Appendix E # The result of permutin
Page 161 and 162:
BIBLIOGRAPHY 149
Page 163 and 164:
13. Bowtell DD: Options available--
Page 165 and 166:
method addressing dye, intensity-de
Page 167 and 168:
73. Alter O, Brown PO, Botstein D:
Page 169 and 170:
11. Kumari S, Verma LK, Weller JW:
Page 171 and 172:
38. Michael Stonebraker LAR, Michae
Page 173 and 174:
64. Cropp CS, Lidereau R, Leone A,
Page 175 and 176:
15. Irizarry RA: affy. In.: Biocond
Page 177 and 178:
Chapter 4: 1. Minna JD, Roth JA, Ga
Page 179 and 180:
30. Delaval B, Ferrand A, Conte N,
Page 181 and 182:
27. Bai J, Cederbaum AI: Catalase p
Page 183 and 184:
51. Shouse GP, Cai X, Liu X: Serine
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