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看图说话系列-RNA-seq data analysis

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发表于 2017-5-19 14:38:15 | 显示全部楼层 |阅读模式
我以前写过一个看图说话:生物信息数据分析文章就是看图说话(http://www.biotrainee.com/thread-601-1-1.html)
最近有看到了一个更经典的:

是不是很清晰呀!!!从测序到分析,到结果的可视化,全部在里面了:
Following data acquisition, RNA-seq analyses typically begin with quality control assessments using analytical tools such as FastQC. Next, for analysis of genic transcripts, splice variants and lncRNAs, short sequencing reads can be aligned to a reference genome using programs such as TopHat or STAR. After alignment, additional quality control assessments can be made with RNA-SeQC and ngs.plot (orange line, RNA-seq plot from a human postmortem brain sample with a high RNA integrity number (RIN = 7.8); green line, RNA-seq plot from a human postmortem brain sample with a low RIN value (RIN = 3) displaying a clear 3′ bias). ngs.plot image used with permission from ref. 28. Finally, to quantify and analyze RNA-seq data, programs such as HTSeq, Cufflinks or MISO are typically used. Depending on experimental purification schemes, researchers may also wish to analyze small ncRNAs from their samples. To do so, after initial quality control analysis, adapters must first be removed from sequence reads using Cutadapt or FASTX, followed by Bowtie alignment to a reference genome and quantitation using a program such as miRanalyzer139. Additional ncRNA-specific analyses can similarly be integrated into miRanalyzer's pipeline, or independent databases (for example, SILVA, piRNABank, etc.) can be used.



文章来源:
Analytical tools and current challenges in the modern era of neuroepigenomics
http://www.nature.com/neuro/journal/v17/n11/full/nn.3816.html





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