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Marker extractions in DNA sequences using sub-sequence segmentation tree.January 2005 (has links)
Hung Wah Johnson. / Thesis submitted in: August 2004. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2005. / Includes bibliographical references (leaves 116-121). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgement --- p.iv / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Motivation --- p.1 / Chapter 1.2 --- Problem Statement --- p.3 / Chapter 1.3 --- Outline of the thesis --- p.6 / Chapter 2 --- Background --- p.8 / Chapter 2.1 --- Biological Background --- p.8 / Chapter 2.2 --- Sequence Alignments --- p.9 / Chapter 2.2.1 --- Pairwise Sequences Alignment --- p.11 / Chapter 2.2.2 --- Multiple Sequences Alignment --- p.15 / Chapter 2.3 --- Neighbor Joining Tree --- p.16 / Chapter 2.4 --- Marker Extractions --- p.18 / Chapter 2.5 --- Neural Network --- p.19 / Chapter 2.6 --- Conclusion --- p.22 / Chapter 3 --- Related Work --- p.23 / Chapter 3.1 --- FASTA --- p.23 / Chapter 3.2 --- Suffix Tree --- p.25 / Chapter 4 --- Sub-Sequence Segmentation Tree --- p.28 / Chapter 4.1 --- Introduction --- p.28 / Chapter 4.2 --- Problem Statement --- p.29 / Chapter 4.3 --- Design --- p.33 / Chapter 4.4 --- Time and space complexity analysis --- p.38 / Chapter 4.4.1 --- Performance Evaluation --- p.40 / Chapter 4.5 --- Summary --- p.48 / Chapter 5 --- Applications: Global Sequences Alignment --- p.51 / Chapter 5.1 --- Introduction --- p.51 / Chapter 5.2 --- Problem Statement --- p.53 / Chapter 5.3 --- Pairwise Alignment --- p.53 / Chapter 5.3.1 --- Algorithm --- p.53 / Chapter 5.3.2 --- Time and Space Complexity Analysis --- p.64 / Chapter 5.4 --- Multiple Sequences Alignment --- p.67 / Chapter 5.4.1 --- The Clustalw Algorithm --- p.68 / Chapter 5.4.2 --- MSA Using SSST --- p.70 / Chapter 5.4.3 --- Time and Space Complexity Analysis --- p.70 / Chapter 5.5 --- Experiments --- p.71 / Chapter 5.5.1 --- Experiment Setting --- p.72 / Chapter 5.5.2 --- Experimental Results --- p.72 / Chapter 5.6 --- Summary --- p.80 / Chapter 6 --- Applications: Marker Extractions --- p.81 / Chapter 6.1 --- Introduction --- p.81 / Chapter 6.2 --- Problem Statement --- p.82 / Chapter 6.3 --- The Multiple Sequence Alignment Approach --- p.85 / Chapter 6.3.1 --- Design --- p.85 / Chapter 6.4 --- Reference Sequence Alignment Approach --- p.88 / Chapter 6.4.1 --- Design --- p.90 / Chapter 6.5 --- Time and Space Complexity Analysis --- p.95 / Chapter 6.6 --- Experiments --- p.95 / Chapter 6.7 --- Summary --- p.99 / Chapter 7 --- HBV Application Framework --- p.101 / Chapter 7.1 --- Motivations --- p.101 / Chapter 7.2 --- The Procedure Flow of the Application --- p.102 / Chapter 7.2.1 --- Markers Extractions --- p.103 / Chapter 7.2.2 --- Rules Training and Prediction --- p.103 / Chapter 7.3 --- Results --- p.105 / Chapter 7.3.1 --- Clustering --- p.106 / Chapter 7.3.2 --- Classification --- p.107 / Chapter 7.4 --- Summary --- p.110 / Chapter 8 --- Conclusions --- p.112 / Chapter 8.1 --- Contributions --- p.112 / Chapter 8.2 --- Future Works --- p.114 / Chapter 8.2.1 --- HMM Learning --- p.114 / Chapter 8.2.2 --- Splice Sites Learning --- p.114 / Chapter 8.2.3 --- Faster Algorithm for Multiple Sequences Alignment --- p.115 / Bibliography --- p.121
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Bioinformatics analyses for next-generation sequencing of plasma DNA.January 2012 (has links)
1997年,Dennis等證明胚胎DNA在孕婦母體中存在的事實開啟了產前無創診斷的大門。起初的應用包括性別鑒定和恒河猴血型系統的識別。隨著二代測序的出現和發展,對外周血游離DNA更加成熟的分析和應用應運而生。例如當孕婦懷孕十二周時, 應用二代測序技術在母體外周血DNA中預測胎兒21號染色體是否是三倍體, 其準確性達到98%。本論文的第一部分介紹如何應用母體外周血DNA構建胎兒的全基因組遺傳圖譜。這項研究極具挑戰,原因是孕後12周,胎兒對外周血DNA貢獻很小,大多數在10%左右,另外外周血中的胎兒DNA大多數短於200 bp。目前的演算法和程式都不適合於從母體外周血DNA中構建胎兒的遺傳圖譜。在這項研究中,根據母親和父親的基因型,用生物資訊學手段先構建胎兒可能有的遺傳圖譜,然後將母體外周血DNA的測序資訊比對到這張可能的遺傳圖譜上。如果在母親純和遺傳背景下,決定父親的特異遺傳片段,只要定性檢測父親的特異遺傳片段是否在母體外周血中存在。如果在母親雜合遺傳背景下,決定母親的遺傳特性,就要進行定量分析。我開發了單倍型相對劑量分析方案,統計學上判斷母親外周血中的兩條單倍型相對劑量水準,顯著增加的單倍型即為最大可能地遺傳給胎兒的單倍型。單倍型相對劑量分析方案可以加強測序資訊的分析效率,降低測序數據波動,比單個位點分析更加穩定,強壯。 / 隨著靶標富集測序出現,測序價格急劇下降。第一部分運用母親父親的多態位點基因型的組合加上測序的資訊可以計算出胎兒DNA在母體外周血中的濃度。但是該方法的局限是要利用母親父親的多態位點的基因型,而不能直接從測序的資訊中推測胎兒DNA在母體外周血中的濃度。本論文的第二部分,我開發了基於二項分佈的混合模型直接預測胎兒DNA在母體外周血中的濃度。當混合模型的似然值達到最大的時候,胎兒DNA在母體外周血中的濃度得到最優估算。由於靶標富集測序可以提供高倍覆蓋的測序資訊,從而有機會直接根據概率模型識別出母親是純和而且胎兒是雜合的有特異信息量的位點。 / 除了母體外周血DNA水準分析推動產前無創診斷外,表觀遺傳學的分析也不容忽視。 在本論文的第三部分,我開發了Methyl-Pipe軟體,專門用於全基因組的甲基化的分析。甲基化測序數據分析比一般的基因組測序分析更加複雜。由於重亞硫酸鹽測序文庫的沒有甲基化的胞嘧啶轉化成尿嘧啶,最後以胸腺嘧啶的形式存在PCR產物中, 但是對於甲基化的胞嘧啶則保持不變。 因此,為了實現將重亞硫酸鹽處理過的測序序列比對到參考基因組。首先,分別將Watson和Crick鏈的參考基因組中胞嘧啶轉化成全部轉化為胸腺嘧啶,同時也將測序序列中的胞嘧啶轉化成胸腺嘧啶。然後將轉化後的測序序列比對到參考基因組上。最後根據比對到基因組上的測序序列中的胞嘧啶和胸腺嘧啶的含量推到全基因組的甲基化水準和甲基化特定模式。Methyl-Pipe可以用於識別甲基化水平顯著性差異的基因組區別,因此它可以用於識別潛在的胎兒特異的甲基化位點用於產前無創診斷。 / The presence of fetal DNA in the cell-free plasma of pregnant women was first described in 1997. The initial clinical applications of this phenomenon focused on the detection of paternally inherited traits such as sex and rhesus D blood group status. The development of massively parallel sequencing technologies has allowed more sophisticated analyses on circulating cell-free DNA in maternal plasma. For example, through the determination of the proportional representation of chromosome 21 sequences in maternal plasma, noninvasive prenatal diagnosis of fetal Down syndrome can be achieved with an accuracy of >98%. In the first part of my thesis, I have developed bioinformatics algorithms to perform genome-wide construction of the fetal genetic map from the massively parallel sequencing data of the maternal plasma DNA sample of a pregnant woman. The construction of the fetal genetic map through the maternal plasma sequencing data is very challenging because fetal DNA only constitutes approximately 10% of the maternal plasma DNA. Moreover, as the fetal DNA in maternal plasma exists as short fragments of less than 200 bp, existing bioinformatics techniques for genome construction are not applicable for this purpose. For the construction of the genome-wide fetal genetic map, I have used the genome of the father and the mother as scaffolds and calculated the fractional fetal DNA concentration. First, I looked at the paternal specific sequences in maternal plasma to determine which portions of the father’s genome had been passed on to the fetus. For the determination of the maternal inheritance, I have developed the Relative Haplotype Dosage (RHDO) approach. This method is based on the principle that the portion of maternal genome inherited by the fetus would be present in slightly higher concentration in the maternal plasma. The use of haplotype information can enhance the efficacy of using the sequencing data. Thus, the maternal inheritance can be determined with a much lower sequencing depth than just looking at individual loci in the genome. This algorithm makes it feasible to use genome-wide scanning to diagnose fetal genetic disorders prenatally in a noninvasive way. / As the emergence of targeted massively parallel sequencing, the sequencing cost per base is reducing dramatically. Even though the first part of the thesis has already developed a method to estimate fractional fetal DNA concentration using parental genotype informations, it still cannot be used to deduce the fractional fetal DNA concentration directly from sequencing data without prior knowledge of genotype information. In the second part of this thesis, I propose a statistical mixture model based method, FetalQuant, which utilizes the maximum likelihood to estimate the fractional fetal DNA concentration directly from targeted massively parallel sequencing of maternal plasma DNA. This method allows fetal DNA concentration estimation superior to the existing methods in term of obviating the need of genotype information without loss of accuracy. Furthermore, by using Bayes’ rule, this method can distinguish the informative SNPs where mother is homozygous and fetus is heterozygous, which is potential to detect dominant inherited disorder. / Besides the genetic analysis at the DNA level, epigenetic markers are also valuable for noninvasive diagnosis development. In the third part of this thesis, I have also developed a bioinformatics algorithm to efficiently analyze genomewide DNA methylation status based on the massively parallel sequencing of bisulfite-converted DNA. DNA methylation is one of the most important mechanisms for regulating gene expression. The study of DNA methylation for different genes is important for the understanding of the different physiological and pathological processes. Currently, the most popular method for analyzing DNA methylation status is through bisulfite sequencing. The principle of this method is based on the fact that unmethylated cytosine residues would be chemically converted to uracil on bisulfite treatment whereas methylated cytosine would remain unchanged. The converted uracil and unconverted cytosine can then be discriminated on sequencing. With the emergence of massively parallel sequencing platforms, it is possible to perform this bisulfite sequencing analysis on a genome-wide scale. However, the bioinformatics analysis of the genome-wide bisulfite sequencing data is much more complicated than analyzing the data from individual loci. Thus, I have developed Methyl-Pipe, a bioinformatics program for analyzing the DNA methylation status of genome-wide methylation status of DNA samples based on massively parallel sequencing. In the first step of this algorithm, an in-silico converted reference genome is produced by converting all the cytosine residues to thymine residues. Then, the sequenced reads of bisulfite-converted DNA sequences are aligned to this modified reference sequence. Finally, post-processing of the alignments removes non-unique and low-quality mappings and characterizes the methylation pattern in genome-wide manner. Making use of this new program, potential fetal-specific hypomethylated regions which can be used as blood biomarkers can be identified in a genome-wide manner. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Jiang, Peiyong. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 100-105). / Abstracts also in Chinese. / Chapter SECTION I : --- BACKGROUND --- p.1 / Chapter CHAPTER 1: --- Circulating nucleic acids and Next-generation sequencing --- p.2 / Chapter 1.1 --- Circulating nucleic acids --- p.2 / Chapter 1.2 --- Next-generation sequencing --- p.3 / Chapter 1.3 --- Bioinformatics analyses --- p.9 / Chapter 1.4 --- Applications of the NGS --- p.11 / Chapter 1.5 --- Aims of this thesis --- p.12 / Chapter SECTION II : --- Mathematically decoding fetal genome in maternal plasma --- p.14 / Chapter CHAPTER 2: --- Characterizing the maternal and fetal genome in plasma at single base resolution --- p.15 / Chapter 2.1 --- Introduction --- p.15 / Chapter 2.2 --- SNP categories and principle --- p.17 / Chapter 2.3 --- Clinical cases and SNP genotyping --- p.20 / Chapter 2.4 --- Sequencing depth and fractional fetal DNA concentration determination --- p.24 / Chapter 2.5 --- Filtering of genotyping errors for maternal genotypes --- p.26 / Chapter 2.6 --- Constructing fetal genetic map in maternal plasma --- p.27 / Chapter 2.7 --- Sequencing error estimation --- p.36 / Chapter 2.8 --- Paternal-inherited alleles --- p.38 / Chapter 2.9 --- Maternally-derived alleles by RHDO analysis --- p.39 / Chapter 2.1 --- Recombination breakpoint simulation and detection --- p.49 / Chapter 2.11 --- Prenatal diagnosis of β- thalassaemia --- p.51 / Chapter 2.12 --- Discussion --- p.53 / Chapter SECTION III : --- Statistical model for fractional fetal DNA concentration estimation --- p.56 / Chapter CHAPTER 3: --- FetalQuant: deducing the fractional fetal DNA concentration from massively parallel sequencing of maternal plasma DNA --- p.57 / Chapter 3.1 --- Introduction --- p.57 / Chapter 3.2 --- Methods --- p.60 / Chapter 3.2.1 --- Maternal-fetal genotype combinations --- p.60 / Chapter 3.2.2 --- Binomial mixture model and likelihood --- p.64 / Chapter 3.2.3 --- Fractional fetal DNA concentration fitting --- p.66 / Chapter 3.3 --- Results --- p.71 / Chapter 3.3.1 --- Datasets --- p.71 / Chapter 3.3.2 --- Evaluation of FetalQuant algorithm --- p.75 / Chapter 3.3.3 --- Simulation --- p.78 / Chapter 3.3.4 --- Sequencing depth and the number of SNPs required by FetalQuant --- p.81 / Chapter 3.5 --- Discussion --- p.85 / Chapter SECTION IV : --- NGS-based data analysis pipeline development --- p.88 / Chapter CHAPTER 4: --- Methyl-Pipe: Methyl-Seq bioinformatics analysis pipeline --- p.89 / Chapter 4.1 --- Introduction --- p.89 / Chapter 4.2 --- Methods --- p.89 / Chapter 4.2.1 --- Overview of Methyl-Pipe --- p.90 / Chapter 4.3 --- Results and discussion --- p.96 / Chapter SECTION V : --- CONCLUDING REMARKS --- p.97 / Chapter CHAPTER 5: --- Conclusion and future perspectives --- p.98 / Chapter 5.1 --- Conclusion --- p.98 / Chapter 5.2 --- Future perspectives --- p.99 / Reference --- p.100
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High throughput study of the translational effect of human single nucleotide polymorphismsLu, Yang, 1972- January 2008 (has links)
Introduction: As a part of the Gene Regulators in Disease project (GRID), this study aims to create a novel high throughput method to discover the genetic effect on gene translation, taking advantage of the rationale that efficiently translated mRNAs associate with multiple ribosomes, while less active ones with fewer or none. / Methods: Lymphoblastoid cell lines (LCLs) from 44 HapMap European individuals were used for polyribosomal fractionation and establishing the sample bank for the future study. The fractionated mRNA samples of 10 out of the 44 individuals were run on an Illumina GoldenGate Beadarray to detect allelic imbalance (developed by the group of T.J. Hudson and T.M. Pastinen). / Results: This study established a high-quality RNA bank, including 1,100 RNA fraction samples. By the Illumina chip, translational imbalance was detected in 75 out of 1483 (5.06%) assays, and 63 out of269 (23.4%) genes. The translational effect was well replicable by the resequencing method. / Conclusion: This study found that genetic effect on gene translation is a common mechanism of expression regulation. Our best hit found in the integrin beta 1 binding protein 1 gene (ITGB1BP1 ) highlights the role of mRNA 3'UTR secondary structure in gene translation. / Keywords: Gene translation, High throughput genotyping, Human genetics, Polyribosome, RNA, Single nucleotide polymorphism
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High throughput study of the translational effect of human single nucleotide polymorphismsLu, Yang, 1972- January 2008 (has links)
No description available.
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Plasma DNA sequencing: a tool for noninvasive prenatal diagnosis and research into circulating nucleic acids. / CUHK electronic theses & dissertations collectionJanuary 2010 (has links)
In the first part of this thesis, two chromosome Y specific genes ( SRYand TSPY) were chosen as the molecular targets to investigate the characteristics of fetal-specific DNA fragments in maternal plasma. By employing the touch down ligation-mediated PCR coupled with cloning and sequencing, the end property and the fragment species of fetal DNA were studied. / Noninvasive prenatal detection of fetal chromosomal aneuploidies is a much sought-after goal in fetomaternal medicine. The discovery of fetal DNA in the plasma of pregnant women has offered new opportunities for this purpose. However, the fact that fetal DNA amounts to just a minor fraction of all DNA in maternal plasma makes it challenging for locus-specific DNA assays to detect the small increase in sequences derived from a trisomic chromosome. On the other hand, although the clinical applications of plasma DNA for prenatal diagnosis are expanding rapidly, the biological properties of circulating DNA in plasma remain unclear. Recently, next-generation sequencing technologies have transformed the landscape of biomedical research through the ultra-high-throughput sequence information generated in a single run. Massively parallel sequencing allows us to study plasma DNA at an unprecedented resolution and also precisely detect fetal chromosomal aneuploidies in a locus-independent way. / Our group has demonstrated the use of massively parallel sequencing to quantify maternal plasma DNA sequences for the noninvasive prenatal detection of fetal trisomy 21. In the second part of this thesis, the clinical utility of this new sequencing approach was extended to the prenatal detection of fetal trisomy 18 and 13. A region-selection method was developed to minimize the effects of GC content on the diagnostic sensitivity and precision for the prenatal diagnosis of trisomy 13. To facilitate the next-generation sequencing-based maternal plasma DNA analysis for clinical implementation, two measures, i.e., lowering the starting volume of maternal plasma and barcoding multiple maternal plasma samples, were investigated. / Taken together, the results presented in this thesis have demonstrated the clinical utility of massively parallel sequencing of maternal plasma DNA and have also provided us a better understanding of the biology of circulating DNA molecules. / The third part of this thesis focuses on the massively parallel paired-end sequencing of plasma DNA. By analyzing millions of sequenced DNA fragments, the biological properties of maternal plasma DNA were elucidated, such as the size distribution of fetal-derived and maternally-contributed DNA molecules and the potential effect of epigenetic modification on DNA fragmentation. Moreover, the plasma DNA from hematopoietic stem cell transplant patients was characterized by paired-end sequencing approach. These sequencing data not only confirmed the predominant hematopoietic origin of cell-free DNA but also revealed the size difference between hematologically-derived and other tissue-derived DNA molecules in plasma. / Zheng, Wenli. / Adviser: Lo Yu Ming Dennis. / Source: Dissertation Abstracts International, Volume: 73-03, Section: B, page: . / Thesis (Ph.D.)--Chinese University of Hong Kong, 2010. / Includes bibliographical references (leaves 261-275). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [201-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.
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Development of bioinformatics algorithms for trisomy 13 and 18 detection by next generation sequencing of maternal plasma DNA.January 2011 (has links)
Chen, Zhang. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references (p. 109-114). / Abstracts in English and Chinese. / ABSTRACT --- p.I / 摘要 --- p.III / ACKNOWLEDGEMENTS --- p.IV / PUBLICATIONS --- p.VI / CONTRIBUTORS --- p.VII / TABLE OF CONTENTS --- p.VIII / LIST OF TABLES --- p.XIII / LIST OF FIGURES --- p.XIV / LIST OF ABBREVIATIONS --- p.XVI / Chapter SECTION I : --- BACKGROUND --- p.1 / Chapter CHAPTER 1: --- PRENATAL DIAGNOSIS OF FETAL TRISOMY BY NEXT GENERATION SEQUENCING TECHNOLOGY --- p.2 / Chapter 1.1 --- FETAL TRISOMY --- p.2 / Chapter 1.2 --- CONVENTIONAL PRENATAL DIAGNOSIS OF FETAL TRISOMIES --- p.3 / Chapter 1.3 --- CELL FREE FETAL D N A AND ITS APPLICATION IN PRENATAL DIAGNOSIS --- p.5 / Chapter 1.4 --- NEXT GENERATION SEQUENCING TECHNOLOGY --- p.5 / Chapter 1.5 --- SUBSTANTIAL BIAS IN THE NEXT GENERATION SEQUENCING PLATFORM --- p.9 / Chapter 1.6 --- PRENATAL DIAGNOSIS OF TRISOMY BY NEXT GENERATION SEQUENCING --- p.10 / Chapter 1.7 --- AIMS OF THIS THESIS --- p.11 / Chapter SECTION I I : --- MATERIALS AND METHODS --- p.13 / Chapter CHAPTER 2: --- METHODS FOR NONINVASIVE PRENATAL DIAGNOSIS OF FETAL TRISOMY MATERNAL PLASMA DNA SEQUENCING --- p.14 / Chapter 2.1 --- STUDY DESIGN AND PARTICIPANTS --- p.14 / Chapter 2.1.1 --- Ethics Statement --- p.14 / Chapter 2.1.2 --- "Study design, setting and participants" --- p.14 / Chapter 2.2 --- MATERNAL PLASMA D N A SEQUENCING --- p.17 / Chapter 2.3 --- SEQUENCING DATA ANALYSIS --- p.18 / Chapter SECTION I I I : --- TRISOMY 13 AND 18 DETECTION BY THE T21 BIOINFORMATICS ANALYSIS PIPELINE --- p.21 / Chapter CHAPTER 3: --- THE T21 BIOINFORMATICS ANALYSIS PIPELINE FOR TRISOMY 13 AND 18 DETECTION --- p.22 / Chapter 3.1 --- INTRODUCTION --- p.22 / Chapter 3.2 --- METHODS --- p.23 / Chapter 3.2.1 --- Bioinformatics analysis pipeline for trisomy 13 and 18 detection --- p.23 / Chapter 3.3 --- RESULTS --- p.23 / Chapter 3.3.1 --- Performance of the T21 bioinformatics analysis pipeline for trisomy 13 and 18 detection --- p.23 / Chapter 3.3.2 --- The precision of quantifying chrl 3 and chrl 8 --- p.27 / Chapter 3.4 --- DISCUSSION --- p.29 / Chapter SECTION IV : --- IMPROVING THE T21 BIOINFORMATICS ANALYSIS PIPELINE FOR TRISOMY 13 AND 18 DETECTION --- p.30 / Chapter CHAPTER 4: --- IMPROVING THE ALIGNMENT --- p.31 / Chapter 4.1 --- INTRODUCTION --- p.31 / Chapter 4.2 --- METHODS --- p.32 / Chapter 4.2.1 --- Allowing mismatches in the index sequences --- p.32 / Chapter 4.2.2 --- Calculating the mappability of the human reference genome --- p.33 / Chapter 4.2.3 --- Aligning reads to the non-repeat masked human reference genome --- p.34 / Chapter 4.2.4 --- Trisomy 13 and 18 detection --- p.34 / Chapter 4.3 --- RESULTS --- p.34 / Chapter 4.3.1 --- Increasing read numbers by allowing mismatches in the index sequences --- p.34 / Chapter 4.3.2 --- Increasing read numbers by using the non-masked reference genome for alignment . --- p.38 / Chapter 4.3.3 --- Allowing mismatches in the read alignment --- p.42 / Chapter 4.3.4 --- The performance of trisomy 13 and 18 detection after improving the alignment --- p.47 / Chapter 4.4 --- DISCUSSION --- p.50 / Chapter CHAPTER 5: --- REDUCING THE GC BIAS BY CORRECTION OF READ COUNTS --- p.53 / Chapter 5.1 --- INTRODUCTION --- p.53 / Chapter 5.2 --- METHODS --- p.54 / Chapter 5.2.1 --- Read alignment --- p.54 / Chapter 5.2.2 --- Calculating the correlation between GC content and read counts --- p.55 / Chapter 5.2.3 --- GC correction in read counts --- p.55 / Chapter 5.2.4 --- Trisomy 13 and 18 detection --- p.56 / Chapter 5.3 --- RESULTS --- p.56 / Chapter 5.3.1 --- GC bias in plasma DNA sequencing --- p.56 / Chapter 5.3.2 --- Correcting the GC bias in read counts by linear regression --- p.59 / Chapter 5.3.3 --- Correcting the GC bias in read counts by LOESS regression --- p.65 / Chapter 5.3.4 --- Bin size --- p.72 / Chapter 5.4 --- DISCUSSION --- p.75 / Chapter CHAPTER 6: --- REDUCING THE GC BIAS BY MODIFYING THE GENOMIC REPRESENTATION CALCULATION --- p.77 / Chapter 6.1 --- INTRODUCTION --- p.77 / Chapter 6.2 --- METHODS --- p.78 / Chapter 6.2.1 --- Modifying the genomic representation calculation --- p.78 / Chapter 6.2.2 --- Trisomy 13 and 18 detection --- p.78 / Chapter 6.2.3 --- Combining GC correction and modified genomic representation --- p.78 / Chapter 6.3 --- RESULTS --- p.79 / Chapter 6.3.1 --- Reducing the GC bias by modifying genomic representation calculation --- p.79 / Chapter 6.3.2 --- Combining GC correction and modified genomic representation --- p.86 / Chapter 6.4 --- DISCUSSION --- p.89 / Chapter CHAPTER 7: --- IMPROVING THE STATISTICS FOR TRISOMY 13 AND 18 DETECTION --- p.91 / Chapter 7.1 --- INTRODUCTION --- p.91 / Chapter 7.2 --- METHODS --- p.92 / Chapter 7.2.1 --- Comparing chrl 3 or chrl8 with other chromosomes within the sample --- p.92 / Chapter 7.2.2 --- Comparing chrl 3 or chrl 8 with the artificial chromosomes --- p.92 / Chapter 7.3 --- RESULTS --- p.93 / Chapter 7.3.1 --- Determining the trisomy 13 and 18 status by comparing chromosomes within the samples --- p.93 / Chapter 7.3.2 --- Determining the trisomy 13 and 18 status by comparing chrl3 or chrl 8 with artificial chromosomes --- p.97 / Chapter 7.4 --- DISCUSSION --- p.100 / Chapter SECTION V : --- CONCLUDING REMARKS --- p.102 / Chapter CHAPTER 8: --- CONCLUSION AND FUTURE PERSPECTIVES --- p.103 / Chapter 8.1 --- THE PERFORMANCE OF THE T21 BIOINFORMATICS ANALYSIS PIPELINE DEVELOPED FOR TRISOMY 21 DETECTION IS SUBOPTIMAL FOR TRISOMY 13 AND 18 DETECTION --- p.103 / Chapter 8.2 --- THE ALIGNMENT COULD BE IMPROVED BY ALLOWING ONE MISMATCH IN THE INDEX AND USING THE NON-REPEAT MASKED HUMAN REFERENCE GENOME AS THE ALIGNMENT REFERENCE --- p.104 / Chapter 8.3 --- THE PRECISION OF QUANTIFYING CHR13 AND CHR18 COULD BE IMPROVED BY THE G C CORRECTION OR THE MODIFIED GENOMIC REPRESENTATION --- p.104 / Chapter 8.4 --- THE STATISTICS FOR TRISOMY 13 AND 18 DETECTION COULD BE IMPROVED BY COMPARING CHR13 OR CHR18 WITH ARTIFICIAL CHROMOSOMES WITHIN THE SAMPLE --- p.105 / Chapter 8.5 --- PROSPECTS FOR FUTURE WORK --- p.106 / REFERENCE --- p.109
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