April 2022
Beginner to intermediate
486 pages
10h 22m
Chinese
Content preview from 云端基因组学
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撰写可完全复现的论文
｜
453
并从我们所面对的巨大数据堆中抽取我们认为有用的信息。这将生成测过序的区域
的变异识别结果，这个长列表记录的是一个个体的基因组和一个相当随意的参考基
因组的差异列表。列表本身并不提供任何真正洞察力；它只是数据。这时分析过程
就该出马：我们开始询问关于数据的特定问题，如一切顺利，分析过程将生成我们
所研究生物系统某一方面的洞察力。
处理 分析
匹配和
变异发现
效果预测和
聚类分析
我们应更进一步
研究哪些遗传变异？
该阶段，我们得到一个
相对于参考基因组的偏差
大列表（很多变异和一些
错 误 ）。
•
SnpEff + Gemini
•
OMIM、GERP、1000G、ExAC数据库
•
在ExAC数据库中，MAF ≤0.001
•
CADD≥20
•
统计和测试
•
MUGQIC GenPipes DNAseq包括：
•
Trimmomatic
•
BWA 0.6.2（b37/hg19）
•
GATK 3.2 HaplotypeCaller
•
QS (QUAL) > 100
图
14
-
8
：论文背后的研究工作分为处理和分析两个阶段，两者可总结为图中信息
我们重视该区别是因为它是我们判断我们需多接近才能复现原研究所用方法的一个
关键因素。一起深入研究工作，你就会明白我们的用心。
14.3.1
匹配和变异发现
我们马上就会遇到一个重要偏差。原研究始于
FASTQ
格式的外显子组测序数据，
在其他研究工作开始之前，该数据需做好匹配工作。然而，当我们生成合成外显子
组数据集时，生成的是
BAM
文件，它存放的是已做过匹配且做好处理准备的测序 ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.