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specific transcript region event, and multiple transcript region events. ProbeSets containing no pattern inversions were deemed to have a statistical issue, meaning that while the pattern was retained the difference in means failed to be significant and this was assumed more likely to be related to the technical variation across the samples. ProbeSets containing single pattern inversions were separated into a distinct category since no other probe confirmed a transcript isoforms event. These ProbeSets need further individual assessment since neighboring probes may have been removed via the filtering process that would provide more support for such events. ProbeSets with more than one probe demonstrating the pattern inversion were subdivided into a single region event or multiple region events, based upon whether the probes in question possessed overlapping alignments. Examples of each category are presented in Figure 2.6. 54
Figure 2.6: Probe-Transcript regions of interest. Examples from the 325 ‘Signal’ ProbeSets, which aggregated as ‘DE’. The red boxplots are the adenocarcinoma samples (T) and the normals are in blue (N); average p values are provided below the x-axis label. Probes of interest are indicated with the green brace. Clockwise from upper left: 37047_s_at the 3 rd probe in the probe-set failed to demonstrate significant difference in means, nor the pseudo-pattern inversion, suggesting that the difference is a matter of statistical importance. The second probe of 32052_at demonstrates stronger evidence of a transcript event; however an absence of neighboring probes complicates the analysis. The first 2 probes and second to last probe in 37028_at demonstrate 2 distinct regions worthy of additional analysis. The example probe 1985_s_at demonstrates the aforementioned 3 (center) probes as a single transcript region displaying transcript isoform phenomena. A Priori Prediction The Bhattacharjee data [47] cleansed via the BaFL pipeline was able to predict the sources of variability in the third Lu dataset [33]; this demonstrates that this is a more robust approach to probe cleansing, rather than either dChip or RMA, which offer no such ability. Presented in Table 2.2 are the true positive and false positive prediction rates for the prediction that a probe 55
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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
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: Figure 2.5: BaFL consistency. Demon
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
Page 87 and 88: sample selection, with replacement,
Page 89 and 90: 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
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
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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
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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
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73. Alter O, Brown PO, Botstein D:
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11. Kumari S, Verma LK, Weller JW:
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38. Michael Stonebraker LAR, Michae
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64. Cropp CS, Lidereau R, Leone A,
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15. Irizarry RA: affy. In.: Biocond
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Chapter 4: 1. Minna JD, Roth JA, Ga
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30. Delaval B, Ferrand A, Conte N,
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27. Bai J, Cederbaum AI: Catalase p
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51. Shouse GP, Cai X, Liu X: Serine
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