人结肠癌第二代 RNA 测序数据的计算生物学研究流程

王文渊; 江华; 潘海霞; 杨浩; 彭谨; 周志远

doi:10.16689/j.cnki.cn11-9349/r.2016.03.013

肿瘤代谢与营养电子杂志 >

2016 , Vol. 3 >Issue 3: 178 - 183

DOI: https://doi.org/10.16689/j.cnki.cn11-9349/r.2016.03.013

论著

人结肠癌第二代 RNA 测序数据的计算生物学研究流程

王文渊 ,
江华 ,
潘海霞 ,
杨浩 ,
彭谨 ,
周志远

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川北医学院，四川省医学科学院 / 四川省人民医院 / 急诊医学与灾难医学研究所 / 创伤代谢组多学科实验室，南开大学数学科学学院，西南医科大学生物化学系

网络出版日期: 2016-09-02

基金资助

四川省科技厅项目（2011SZ0336，2012SZ0181 和 2015SZ0110）

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The computation biology analysis protocol of next-generation high-throughput RNA-sequencing data from human colon cancer

WANG Wen-yuan ,
JIANG Hua ,
PAN Hai-xia ,
YANG Hao ,
PENG Jin ,
ZHOU Zhi-yuan

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North Sichuan Medical College, Metabolomics and Multidisciplinary Laboratory for Trauma Research, Institute for Emergency and Disaster Medicine, Sichuan Provincial People’s Hospital, Sichuan Academy of Medical Science, School of Mathematical Sciences, Nankai University, Department of Biochemistry, Southwest Medical University

Online published: 2016-09-02

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摘要

摘要：目的以人结肠癌 RNA 测序数据分析为例，介绍新一代高通量中的 RNA 测序（RNA-sequencing， RNA-seq）
技术在转录组与基因表达谱方面的应用。方法基于 Linux 平台的开源分析软件和人结肠癌 RNA 测序数据，建立完整的
RNA-seq 测序数据处理和分析流程，并对其中的软件选择、质量控制、下游分析进行讨论。结果基于现有主流的 RNA-seq
计算生物学分析技术，建立起了一套免费开源的 RNA 测序计算生物学处理和分析流程，并从中鉴定出了数个在结肠癌表
达中存在显著差异的基因。结论这项研究为 RNA-seq 数据清理、计算建模和分析提供了具有良好操作性的方案。作为一
个临床肿瘤 RNA-seq 研究范本，以供从事于类似研究的临床科研工作者参考。

关键词： 结肠癌; RNA 测序; 下一代测序技术; 转录组; 计算生物学

本文引用格式

王文渊 , 江华 , 潘海霞 , 杨浩 , 彭谨 , 周志远 . 人结肠癌第二代 RNA 测序数据的计算生物学研究流程[J]. 肿瘤代谢与营养电子杂志, 2016 , 3(3) : 178 -183 . DOI: 10.16689/j.cnki.cn11-9349/r.2016.03.013

Abstract

Abstract: Objective To introduce an application of the next-generation high-throughput RNA-sequencing (RNA-seq) technology on transcriptomes and gene expression profiles research, based on the RNA-seq data from human colon cancer. Methods Based on the open-source analysis software of Linux platform and RNA-seq data from human colon cancer tissue, the complete workflow of RNA-seq data processing and analysis protocol would be established. And the software selection, quality control and downstream analysis in this workflow would be discussed. Results By using the mainstream RNA-seq computation biology techniques, a set of free and open-source RNA-seq data processing and analysis computational biology protocol have been established. And there were several difference-expressed genes were identified from this human colon cancer RNA-seq data analysis workflow. Conclusions This study provided an easy-to-use protocol for RNA-seq data clean, computation modeling and analysis. As an example of clinical oncology research, it could be referenced for the clinical investigators working on similar study.

Key words： Colon cancer; RNA sequencing; Next-generation sequencing; Transcriptomes; Computation biology

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