正向遺傳學(xué)研究中的候選基因識(shí)別
發(fā)布時(shí)間：2019-03-07 22:08
【摘要】：隨著測序技術(shù)的發(fā)展,高通量測序的精準(zhǔn)度不斷提高,成本逐年下降,相關(guān)的應(yīng)用亦越來越廣,本文以高通量測序技術(shù)為基礎(chǔ),利用測序數(shù)據(jù),提出鑒定家系遺傳病的候選基因的方法。在實(shí)際操作上需面臨流程參數(shù)設(shè)定,顯隱性假設(shè),以及候選基因是抑制子或激活子的假設(shè)等問題。對(duì)研究者而言如何選擇更優(yōu)的參數(shù),針對(duì)各種遺傳假設(shè)快速合理地得到分析結(jié)果,是充滿挑戰(zhàn)性的。為了更好地解決這一問題,基于二代測序技術(shù)的基因識(shí)別軟件GIPS應(yīng)運(yùn)而生,他為研究者提供了四種指導(dǎo)性參數(shù),并成功地應(yīng)用于水稻測序數(shù)據(jù)上。本文統(tǒng)籌考慮了家系遺傳病中各種可能出現(xiàn)的情況,在第一代GIPS的基礎(chǔ)上增加了新的家系過濾算法,ANNOVAR注釋軟件接口,曼哈頓圖譜繪制功能,以及底層的背景突變率算法的重定義和公式改進(jìn)。進(jìn)一步增加該軟件的實(shí)用性,可擴(kuò)展性,生物學(xué)可靠性以及精準(zhǔn)度。并為提高運(yùn)行效率,推出了快速獲得候選基因列表的新命令。針對(duì)第二代GIPS軟件的優(yōu)化。首先,討論了在家系遺傳病中可能存在的各種情況,如待研究病癥的顯隱性,候選基因是抑制子或是激活子。并根據(jù)每種情況,利用不同SNP在基因座上的基因型,進(jìn)行家系篩選。為了使得用戶更直觀地了解基因組上所有基因與表型的相關(guān)程度,繪制出基因組上每一個(gè)基因與表型相關(guān)聯(lián)的顯著性的曼哈頓圖譜。亦可更直觀的反應(yīng)出通過閾值篩選的候選基因數(shù)目。通過改進(jìn)背景突變率的算法,我們得到更為精確的評(píng)估標(biāo)準(zhǔn),文中亦對(duì)前后兩種背景突變率作了詳細(xì)的比較,為了更多的從生物學(xué)角度改進(jìn)該算法,我們還可以綜合不同類型的打分軟件,從不同角度(例如序列保守程度,理化性質(zhì)等),指導(dǎo)SNP的篩選。為此新一代的GIPS在原來的基礎(chǔ)上增加了新的打分軟件的接口,以上這些新增功能均成功應(yīng)用在水稻數(shù)據(jù)和耳聾等家系遺傳病數(shù)據(jù)上,并已發(fā)表文章于SCI 期刊 Plant Physiology。網(wǎng)址:http://www.plantphysiol.org/content/170/4/1929
[Abstract]:With the development of sequencing technology, the precision of high-throughput sequencing has been improved, the cost of high-throughput sequencing has been reduced year by year, and the related applications have also become more and more extensive. This paper is based on high-throughput sequencing technology and uses sequencing data. A method for identifying candidate genes for hereditary diseases in families was proposed. In practice, some problems such as process parameter setting, recessive hypothesis and hypothesis that candidate genes are suppressors or activators are needed. It is challenging for researchers to choose better parameters and get the analysis results quickly and reasonably according to a variety of genetic assumptions. In order to solve this problem, GIPS, a gene recognition software based on second-generation sequencing technology, emerged as the times require. He provides four guiding parameters for researchers and has been successfully applied to rice sequencing data. In this paper, a new family filtering algorithm, ANNOVAR annotation software interface and Manhattan map drawing function are added on the basis of the first generation of GIPS, considering all kinds of possible conditions in family genetic diseases. And the redefinition and formula improvement of the underlying background mutation rate algorithm. Further increase the practicability, expansibility, biological reliability and precision of the software. In order to improve the operation efficiency, a new command was proposed to quickly obtain candidate gene list. Optimization of the second generation GIPS software. First of all, the possible conditions of familial genetic diseases are discussed, such as the recessive of the disease to be studied, and the candidate genes are suppressors or activators. According to each situation, different genotypes of SNP at the locus were used to screen the families. In order to make users understand the correlation degree of all genes and phenotypes in the genome more intuitively, the Manhattan map of the correlation between each gene and phenotype in the genome is plotted. It can also more intuitively reflect the number of candidate genes screened by threshold. By improving the algorithm of background mutation rate, we get more accurate evaluation criteria. We also make a detailed comparison between the two kinds of background mutation rate, in order to improve the algorithm more from the biological point of view. We can also integrate different scoring software to guide the screening of SNP from different angles (such as conservative degree of sequence, physical and chemical properties, etc.). To this end, the new generation of GIPS has added a new interface to the scoring software. These new functions have been successfully applied to rice data and deafness data in pedigrees, and have been published in the SCI journal Plant Physiology.. Web site: http://www.plantphysiol.org/content/170/4/1929
【學(xué)位授予單位】：浙江大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：Q78
本文編號(hào)：2436496
[Abstract]:With the development of sequencing technology, the precision of high-throughput sequencing has been improved, the cost of high-throughput sequencing has been reduced year by year, and the related applications have also become more and more extensive. This paper is based on high-throughput sequencing technology and uses sequencing data. A method for identifying candidate genes for hereditary diseases in families was proposed. In practice, some problems such as process parameter setting, recessive hypothesis and hypothesis that candidate genes are suppressors or activators are needed. It is challenging for researchers to choose better parameters and get the analysis results quickly and reasonably according to a variety of genetic assumptions. In order to solve this problem, GIPS, a gene recognition software based on second-generation sequencing technology, emerged as the times require. He provides four guiding parameters for researchers and has been successfully applied to rice sequencing data. In this paper, a new family filtering algorithm, ANNOVAR annotation software interface and Manhattan map drawing function are added on the basis of the first generation of GIPS, considering all kinds of possible conditions in family genetic diseases. And the redefinition and formula improvement of the underlying background mutation rate algorithm. Further increase the practicability, expansibility, biological reliability and precision of the software. In order to improve the operation efficiency, a new command was proposed to quickly obtain candidate gene list. Optimization of the second generation GIPS software. First of all, the possible conditions of familial genetic diseases are discussed, such as the recessive of the disease to be studied, and the candidate genes are suppressors or activators. According to each situation, different genotypes of SNP at the locus were used to screen the families. In order to make users understand the correlation degree of all genes and phenotypes in the genome more intuitively, the Manhattan map of the correlation between each gene and phenotype in the genome is plotted. It can also more intuitively reflect the number of candidate genes screened by threshold. By improving the algorithm of background mutation rate, we get more accurate evaluation criteria. We also make a detailed comparison between the two kinds of background mutation rate, in order to improve the algorithm more from the biological point of view. We can also integrate different scoring software to guide the screening of SNP from different angles (such as conservative degree of sequence, physical and chemical properties, etc.). To this end, the new generation of GIPS has added a new interface to the scoring software. These new functions have been successfully applied to rice data and deafness data in pedigrees, and have been published in the SCI journal Plant Physiology.. Web site: http://www.plantphysiol.org/content/170/4/1929
【學(xué)位授予單位】：浙江大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：Q78
【參考文獻(xiàn)】
相關(guān)碩士學(xué)位論文 前1條
1 朱忠旭;基于表型測序的功能基因識(shí)別[D];浙江大學(xué);2015年
，本文編號(hào)：2436496
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