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

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Figure 2.3: Statistical analysis of batches. Graphical depiction of array/batch characteristics in a test of average probe signal (top) and of average number of responding probes (bottom) relative to the mean. The numeral shown indicates to which batch the sample belongs (10 is X), the color indicates disease class (blue=Adenocarcinoma, red=Normal, purple=Small Cell Carcinoma, green=Pulmonary, and orange = Squamous), The heavy line in the middle is the mean intensity; lighter dotted lines are 1 and 2 standard deviation boundaries. The red circle emphasizes the divergent behavior of batch 3 in both tests. There are no batches 2 or 9. The affy package [19] results, when graphed, also indicate that there is a significant difference in Batch 3 properties; therefore this outcome is not an artifact of our probe cleansing methodology. To run this analysis, mock CEL files were created, using the mean probe intensity across the arrays in a batch; this process was followed for the original array files for all arrays, for the original data with outlying samples removed, and for the array files in which deprecated probes and sample arrays were removed. Boxplots and histogram densities for the outcomes at 48
various data processing stages are shown in Figure 2.4. The difference in batch 3 is seen in both the boxplot and histogram densities for the original data, as depicted in the graphs on the left. The middle graphs present the effect of removing all of the arrays in batch 3, but applying no additional sample cleansing steps to the data (used as input into the RMA and dCHIP algorithms [23, 58]). The data distributions still demonstrate a substantial skew. The right-most graphs depict our probe cleansed and sample cleansed data, in log2 space. Note that the linear range cut- off enforces a truncation of the data distributions, which is most visible in the boxplots. The improved normality of the data distribution observed in the last density plot is a result of the combination of probe and sample cleansing; no scaling was applied to the data. Removal of batch 3 accounted for 38 samples. 49
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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 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: described above. In Figure 2.3, the
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
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
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for the RMA and dCHIP interpretatio
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was one of them: it is counted as p
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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:
Page 171 and 172:
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,
Page 181 and 182:
27. Bai J, Cederbaum AI: Catalase p
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51. Shouse GP, Cai X, Liu X: Serine
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