Transcriptional Characterization of Glioma Neural Stem Cells Diva ...

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5.4 Quantitative Real Time-PCR Validation Methods PCR. This gene set comprises 82 validation targets from Tag-seq analysis, eight glioma and developmental markers, and three endogenous control genes - 18S ribosomal RNA, TUBB and NDUFB10. The 18S gene was chosen because used by ABI as a manufacturing control, while TUBB and NDUFB10 were selected because they are present in our Tag-seq dataset and show low varia- tion of expression across GNS and NS cell lines in an independent microarray expression dataset [404]. The 93 genes were interrogated using 96 different TaqMan assays (three of the validation targets required two different primer and probe sets to cover all known transcript isoforms matching differentially expressed tags). cDNA was generated using SuperScript III (Invitrogen) and real-time PCR carried out using TaqMan fast universal PCR master mix. The absence of a no-template control (NTC) amplification (horizontal slope) en- sured that random contamination and reagent contamination were not affect- ing our samples. In complying with the minimum information for publication of quantitative real-time PCR experiments (MIQE) [78], a full assay list with raw and normalised threshold cycle (Ct) values is provided in Appendix A.3. The data analysis was performed using the R package HTqPCR [131], which handles high-throughput qPCR data with a focus on data from Taqman low density arrays. Ct values were normalised to the average of the three control genes and potential outliers identified and filtered out using the plotCtBoxes function (Fig 5.2). Figure 5.3 shows the effect of the normalisation method Figure 5.2: Boxplot of normalised Ct values identifies outliers (empty circles). 102
5.4 Quantitative Real Time-PCR Validation Methods Figure 5.3: Correlation scatter plot showing the effect of the normalization method on the raw Ct values measured for the three endogenous controls. employed on the endogenous controls rearranging the Ct values to a smaller dynamic range. To capture biological variability within cell lines, we measured up to four independent RNA samples per line (indicated with the letters A, B, C, D in tables A.3 and A.4 in Appendix A.3). Figure 5.4 shows that the concordance between all our A, B biological replicates is very high and few outliers can be observed - identified with a gene name and highlighted in red in the figure. Differentially expressed genes were identified by the Wilcoxon rank sum test after averaging replicates. 103
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Transcriptional Characterization of
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This dissertation is my own work an
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Acknowledgements I would like to th
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5.9 External Dataset Expression Cor
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Introduction 1
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1.1 Glial Cells in the Central Nerv
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1.2 Glioblastoma Multiforme Introdu
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1.3 Primary and Secondary Glioblast
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1.4 Pathways Involved in Glioblasto
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1.5 Pathway Crosstalk Introduction
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Chapter 2 Neurogenesis Contents 2.1
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2.1 Radial Glia Introduction VZ adj
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2.2 Neural Stem Cells Introduction
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6.7 Isoform Differential Expression
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6.7 Isoform Differential Expression
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6.8 Long ncRNA Differential Express
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6.8 Long ncRNA Differential Express
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Chapter 7 Dataset Correlation Analy
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7.1 Enrichment Analysis Results Tab
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7.1 Enrichment Analysis Results Fig
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7.1 Enrichment Analysis Results Tab
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7.2 Glioblastoma Expression Signatu
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7.3 Tumour Expression Correlation R
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7.4 Survival Analysis Results Table
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7.4 Survival Analysis Results 867 g
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7.5 Glioblastoma Pathway Analysis R
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8.1 Principles Results say, this is
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8.3 Databases Results Figure 8.1: O
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8.3 Databases Results Figure 8.3: W
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8.4 Filters Results Bayesian method
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8.5 Target Prediction Ensemble Anal
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9.1. Digital Profiling of GNS Cell
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9.2. MicroRNA Target Prediction Ana
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9.3. Concluding Remarks Appendix pr
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A.1 Differential Expression Appendi
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A.2 Classified Differential Express
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A.3 Quantitative RT-PCR Appendix Ta
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A.3 Quantitative RT-PCR Appendix We
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A.3 Quantitative RT-PCR Appendix Ta
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A.3 Quantitative RT-PCR Appendix We
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A.4 Tag-seq vs qRT-PCR Correlation
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Appendix "BEX5", "DIAPH2", "GBP3",
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End Select End If End Sub Appendix
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If NameStr.ToLower().Equals("query"
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Appendix C Long ncRNAs We detected
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C. Long ncRNAs Appendix Tag Accessi
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D.1 Pathway Interactions Appendix F
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D.2 Pathway Images Appendix Figure
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D.2 Pathway Images Appendix Figure
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E. Exon Array Data Appendix Average
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F. MicroRNA Array Data Appendix Tab
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F. MicroRNA Array Data Appendix GNS
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F. MicroRNA Array Data Appendix GNS
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Ln Natural logarithm LOH Loss of He
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3.3 Schematisation of cell cycle ph
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8.3 Workflows at the core of the pr
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7.1 Selected Gene Ontology terms an
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