title: [Automatic analysis pipeline of next-generation sequencing data].
abstract: The development of next-generation sequencing has generated high demand for data processing and analysis. Although there are a lot of software for analyzing next-generation sequencing data, most of them are designed for one specific function (e.g., alignment, variant calling or annotation). Therefore, it is necessary to combine them together for data analysis and to generate interpretable results for biologists. This study designed a pipeline to process Illumina sequencing data based on Perl programming language and SGE system. The pipeline takes original sequence data (fastq format) as input, calls the standard data processing software (e.g., BWA, Samtools, GATK, and Annovar), and finally outputs a list of annotated variants that researchers can further analyze. The pipeline simplifies the manual operation and improves the efficiency by automatization and parallel computation. Users can easily run the pipeline by editing the configuration file or clicking the graphical interface. Our work will facilitate the research projects using the sequencing technology.
authors.affiliation: State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Disease, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China.
authors.forename: Li
authors.initials: L
authors.lastname: Wenke
authors.affiliation: State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Disease, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China; College of Biomedical Engineering, South-Central University for Nationalities, Wuhan 430074, China.
authors.forename: Li
authors.initials: L
authors.lastname: Fengyu
authors.affiliation: State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Disease, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China.
authors.forename: Zhang
authors.initials: Z
authors.lastname: Siyao
authors.affiliation: State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Disease, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China.
authors.forename: Cai
authors.initials: C
authors.lastname: Bin
authors.affiliation: State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Disease, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China.
authors.forename: Zheng
authors.initials: Z
authors.lastname: Na
authors.affiliation: State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Disease, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China.
authors.forename: Nie
authors.initials: N
authors.lastname: Yu
authors.affiliation: College of Biomedical Engineering, South-Central University for Nationalities, Wuhan 430074, China.
authors.forename: Zhou
authors.initials: Z
authors.lastname: Dao
authors.affiliation: State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Disease, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China.
authors.forename: Zhao
authors.initials: Z
authors.lastname: Qian
mesh_terms: D001331:Automation / Q000295:instrumentation / Q000379:methods*; D019295:Computational Biology / Q000295:instrumentation*; D057225:Data Mining / Q000379:methods*; D003628:Database Management Systems / Q000295:instrumentation; D030541:Databases, Genetic; D059014:High-Throughput Nucleotide Sequencing