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Summary and normal samples, as cleansed by the methodology presented in Chapter 2. K-means clustering was used to calculate the information gain of the cleansed ProbeSets. The gain criterion demonstrates an efficient methodology to down select to a manageable candidate gene list. This candidate gene lists demonstrates accurate prediction rates for the three disease groups, for kNN and LDA classification algorithms. More importantly what is known about the biology of these genes suggests intriguing differences in cell cycle control mechanisms in the different groups. In particular, the findings suggest the occurrence of aberrant cytokinesis, which may underlie or be resultant in DNA damage elucidating the p53 dependent pathway in the squamous cell carcinoma samples. Microarray experiments assess the concentration of a samples’ transcript levels at a given point in time. These measurements are the result of a semi-quantitative interpretation of the amount of fluorescence at a given probe spot. The probes at these spots are present in sufficient concentration to drive the expected duplex product formation, but the variation in the response cannot be assessed since most commercial platforms do not provide spot replicates. The measurements of fluorescent intensity are interpreted to represent the concentrations of specific regions of a transcript and for those platforms like Affymetrix that provide multiple measurements over a transcript this redundancy is meant to be equivalent to the spot replicate feature. These platforms have sacrificed measurement replication, ignored scanner limitations, have problematic background correction design and pay inadequate attention to known factors 24
affecting probe-target duplex formation. Several such factors include the presence of SNPs in the transcript region of interest, cross-hybridization abilities of similar transcript regions having high sequence similarity, and secondary and tertiary structures yielding inaccessible probes and target transcript regions. An additional level of confusion arises from the presence of alternate alleles, whether as uncharacterized SNPs, larger indels and copy number variations, or alternate transcript forms. In order for the results of Microarray experiments to have scientific merit, a significant effort must be made to identify the potential source of deficiencies in probe sensitivities due to any and all of these causes, preferably explicitly, in order to provide more reliable and thereby more reproducible measurements. 25
Page 1 and 2: An Adenocarcinoma Case Study of the
Page 3 and 4: DEDICATION The work presented in th
Page 5 and 6: TABLE OF CONTENTS LIST OF TABLES ..
Page 7 and 8: Conclusion.........................
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: implemented in order to demonstrate
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
Page 69 and 70: Table 2.3: ProbeSet behavior predic
Page 71 and 72: cleansing process. This is demonstr
Page 73 and 74: Table 2.4: ProbeSet behavior of pro
Page 75 and 76: A Priori Prediction We demonstrated
Page 77 and 78: Conclusion We have presented a comp
Page 79 and 80: 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.
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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
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whole model analysis without permut
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change, apparently the greater vari
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though in Chapter 2 we showed that
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Although a list of 325 candidate ge
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was determined to consist of 30 Pro
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Figure 4.1: Non-traditional PCA ana
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for the RMA and dCHIP interpretatio
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was one of them: it is counted as p
Page 115 and 116:
Figure 4.5: Kaplan-Meyer survival c
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Figure 4.7: Low grade tumor surviva
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The candidate gene list values were
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ejecting the null hypothesis [8], a
Page 123 and 124:
Figure 4.9: GO connectivity of cand
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under linear and non-linear dimensi
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sample cleansing process and these
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averaged to give a final approximat
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119 Table 5.1: : NSCLC candidate ge
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Figure 5.1: NSCLC ProbeSet gain sel
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Figure 5.3: NSCLC refined average p
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statistical criterion, but it appea
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lacking p53 mutations [30]. While,
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Kruppel-like factor 5 (KLF5) has al
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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
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fp.write('\tTable '), fp.write(msk[
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#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
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cur, conn=UpdateWorkReg(cur, conn,
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Appendix E # The result of permutin
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BIBLIOGRAPHY 149
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13. Bowtell DD: Options available--
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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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