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

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methylation regulatory control, and multiple cellular functions, for which well documented methods exist. We believe that the BaFL cleansing process has provided the basis for an intriguing elucidation of distinct differences in disease mechanism for two histologically distinct NSCLC lung tissue tumor types. 130
Appendix A # This is the main driver function in the CleansingPrep_6_23.py file which prepares the ProbeFATE system for the BaFL filter cleansing # tables parameter is a list of files to import or create # example files are in the Supplementary Materials: 1) MissingQuantitation.csv quantitation types which I add to the system 2) Known.csv calculates or uses previously calculated deltaG (OligoArrayAux ) values for probes with known sequences, flag meth[0] differentiates 3) SampleMask.csv a file which describes the data (abbrev. sample sd, orig sample id, the associated .cel file, disease class, and the file source for this information 4) SNP_by_pos.csv a file created w/ Sunita.py, which parses the information from AffyMAPSDetector output 5) probe_mapping.csv file is created through ENSEMBL mappings or probes, flag[1] indicates whether the latest ENSEMBL build is used otherwise the build needs to be provided def prepareCleansing(db, usr, pswd, fpath, logfile, tables, meth): # tables = [added_qts, sample_info, snp_info, xhybrid_info] # add new qts i=0 CreateNew_QTs(db, usr, pswd, tables[0], logfile) i+=1 # map known chip sequence info if lower(meth[0])=='copy': Copy_deltaG(db, usr, pswd, tables[1], logfile) i+=1 elif lower(meth[0][:4])=='calc': Calc_deltaG(db, usr, pswd, fpath, logfile) else: print 'Method:', meth[0], 'does not exist.' return -1 # set sample mask Sample_mask(db, usr, pswd, logfile, tables[i]) i+=1 # map SNP info SNP_mask(db, usr, pswd, tables[i], logfile) i+=1 # map xhybridization info if lower(meth[1])=='new': new_Xhybrid(db, usr, pswd, tables[i], logfile) else: version_Xhybrid(db, usr, pswd, tables[i], logfile, meth[1]) Mod_wk_registry(db, usr, pswd) print '\nXHYBRID INFO MAPPED\n' print '\n\tALMOST READY TO PROBE CLEANSE\n' 131
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An Adenocarcinoma Case Study of the
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DEDICATION The work presented in th
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TABLE OF CONTENTS LIST OF TABLES ..
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Conclusion.........................
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LIST OF FIGURES Figure Page Figure
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violate the linear correlation rela
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Chapter 1: An Introduction to Micro
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previously stated, rigorous reagent
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Factors influencing Signal Interpre
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likelihood that no such structural
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hybridization and multiple dye stra
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classical reaction equations, modif
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prevent the hybridization of probes
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platforms are used to deposit them
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and chip layout [64]. In particular
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whether analyses based upon individ
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The process of determining a candid
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implemented in order to demonstrate
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affecting probe-target duplex forma
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It has long been known that the var
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probes can thus be reincorporated i
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(Carr, ms in review). This ProbeFAT
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have specific attributes which can
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elow saturation. The investigator m
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a. A filter based on how many probe
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means. The remaining sets possess s
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for the 24 samples in the Lu, et al
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Table 2.1: Probe Numbers per filter
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the effect can be. Both the type of
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described above. In Figure 2.3, the
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various data processing stages are
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position of the probe on the transc
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Figure 2.5: BaFL consistency. Demon
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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
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Conclusion We have presented a comp
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mind that they are most aware of th
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Probe Cleansing Methods The BaFL pr
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are significant assume such a data
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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-
Page 93 and 94: 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
Page 101 and 102: 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
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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
Page 133 and 134: 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: Kruppel-like factor 5 (KLF5) has al
Page 145 and 146: def Driver(usr, pswd, db, logfile,
Page 147 and 148: def DriverXH(usr, pswd, db, logfile
Page 149 and 150: fp.write('\tTable '), fp.write(msk[
Page 151 and 152: #determine outliers lowrs1=nonzero(
Page 153 and 154: tmp="update sample_mask set exclude
Page 155 and 156: 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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