دورية أكاديمية
Rna-Sequencing Applications: Gene Expression Quantification And Methylator Phenotype Identification
| العنوان: | Rna-Sequencing Applications: Gene Expression Quantification And Methylator Phenotype Identification |
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| المؤلفون: | Cai, Guoshuai |
| المصدر: | Dissertations and Theses (Open Access) |
| بيانات النشر: | DigitalCommons@TMC |
| سنة النشر: | 2013 |
| المجموعة: | Houston Academy of Medicine-Texas Medical Center (HAM-TMC): DigitalCommons@The Texas Medical Center |
| مصطلحات موضوعية: | RNA-Seq, overdispersion, random hexamer primering. Differential expression analysis, CpG island methylator phenotype (CIMP), integration, Bioinformatics, Computational Biology, Life Sciences, Medicine and Health Sciences |
| الوصف: | My dissertation focuses on two aspects of RNA sequencing technology. The first is the methodology for modeling the overdispersion inherent in RNA-seq data for differential expression analysis. This aspect is addressed in three sections. The second aspect is the application of RNA-seq data to identify the CpG island methylator phenotype (CIMP) by integrating datasets of mRNA expression level and DNA methylation status. Section 1: The cost of DNA sequencing has reduced dramatically in the past decade. Consequently, genomic research increasingly depends on sequencing technology. However it remains elusive how the sequencing capacity influences the accuracy of mRNA expression measurement. We observe that accuracy improves along with the increasing sequencing depth. To model the overdispersion, we use the beta-binomial distribution with a new parameter indicating the dependency between overdispersion and sequencing depth. Our modified beta-binomial model performs better than the binomial or the pure beta-binomial model with a lower false discovery rate. Section 2: Although a number of methods have been proposed in order to accurately analyze differential RNA expression on the gene level, modeling on the base pair level is required. Here, we find that the overdispersion rate decreases as the sequencing depth increases on the base pair level. Also, we propose four models and compare them with each other. As expected, our beta binomial model with a dynamic overdispersion rate is shown to be superior. Section 3: We investigate biases in RNA-seq by exploring the measurement of the external control, spike-in RNA. This study is based on two datasets with spike-in controls obtained from a recent study. We observe an undiscovered bias in the measurement of the spike-in transcripts that arises from the influence of the sample transcripts in RNA-seq. Also, we find that this influence is related to the local sequence of the random hexamer that is used in priming. We suggest a model of the inequality between samples and to ... |
| نوع الوثيقة: | text |
| وصف الملف: | application/pdf |
| اللغة: | unknown |
| العلاقة: | https://digitalcommons.library.tmc.edu/utgsbs_dissertations/386Test; https://digitalcommons.library.tmc.edu/context/utgsbs_dissertations/article/1423/viewcontent/Dissertation_v2_final.pdfTest |
| الإتاحة: | https://digitalcommons.library.tmc.edu/utgsbs_dissertations/386Test https://digitalcommons.library.tmc.edu/context/utgsbs_dissertations/article/1423/viewcontent/Dissertation_v2_final.pdfTest |
| رقم الانضمام: | edsbas.BE063F7D |
| قاعدة البيانات: | BASE |
| الوصف غير متاح. |