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SeqMule: automated pipeline for analysis of human exome/genome sequencing data

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Title: SeqMule: automated pipeline for analysis of human exome/genome sequencing data
Authors: Guo, Yunfei, Ding, Xiaolei, Shen, Yufeng, Lyon, Gholson J., Wang, Kai
Publication Year: 2015
Collection: Columbia University: Academic Commons
Subject Terms: Genomes--Data processing, Genetics, Software engineering, Bioinformatics, Systems biology
Description: Next-generation sequencing (NGS) technology has greatly helped us identify disease-contributory variants for Mendelian diseases. However, users are often faced with issues such as software compatibility, complicated configuration, and no access to high-performance computing facility. Discrepancies exist among aligners and variant callers. We developed a computational pipeline, SeqMule, to perform automated variant calling from NGS data on human genomes and exomes. SeqMule integrates computational-cluster-free parallelization capability built on top of the variant callers, and facilitates normalization/intersection of variant calls to generate consensus set with high confidence. SeqMule integrates 5 alignment tools, 5 variant calling algorithms and accepts various combinations all by one-line command, therefore allowing highly flexible yet fully automated variant calling. In a modern machine (2 Intel Xeon X5650 CPUs, 48 GB memory), when fast turn-around is needed, SeqMule generates annotated VCF files in a day from a 30X whole-genome sequencing data set; when more accurate calling is needed, SeqMule generates consensus call set that improves over single callers, as measured by both Mendelian error rate and consistency. SeqMule supports Sun Grid Engine for parallel processing, offers turn-key solution for deployment on Amazon Web Services, allows quality check, Mendelian error check, consistency evaluation, HTML-based reports. SeqMule is available at http://seqmule.openbioinformatics.org.
Document Type: article in journal/newspaper
Language: English
Relation: https://doi.org/10.7916/D8PC4DW5
DOI: 10.7916/D8PC4DW5
Availability: https://doi.org/10.7916/D8PC4DW5
Accession Number: edsbas.D1E219AF
Database: BASE
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  Data: SeqMule: automated pipeline for analysis of human exome/genome sequencing data
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  Data: <searchLink fieldCode="AR" term="%22Guo%2C+Yunfei%22">Guo, Yunfei</searchLink><br /><searchLink fieldCode="AR" term="%22Ding%2C+Xiaolei%22">Ding, Xiaolei</searchLink><br /><searchLink fieldCode="AR" term="%22Shen%2C+Yufeng%22">Shen, Yufeng</searchLink><br /><searchLink fieldCode="AR" term="%22Lyon%2C+Gholson+J%2E%22">Lyon, Gholson J.</searchLink><br /><searchLink fieldCode="AR" term="%22Wang%2C+Kai%22">Wang, Kai</searchLink>
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  Data: 2015
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  Data: Columbia University: Academic Commons
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  Data: <searchLink fieldCode="DE" term="%22Genomes--Data+processing%22">Genomes--Data processing</searchLink><br /><searchLink fieldCode="DE" term="%22Genetics%22">Genetics</searchLink><br /><searchLink fieldCode="DE" term="%22Software+engineering%22">Software engineering</searchLink><br /><searchLink fieldCode="DE" term="%22Bioinformatics%22">Bioinformatics</searchLink><br /><searchLink fieldCode="DE" term="%22Systems+biology%22">Systems biology</searchLink>
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  Data: Next-generation sequencing (NGS) technology has greatly helped us identify disease-contributory variants for Mendelian diseases. However, users are often faced with issues such as software compatibility, complicated configuration, and no access to high-performance computing facility. Discrepancies exist among aligners and variant callers. We developed a computational pipeline, SeqMule, to perform automated variant calling from NGS data on human genomes and exomes. SeqMule integrates computational-cluster-free parallelization capability built on top of the variant callers, and facilitates normalization/intersection of variant calls to generate consensus set with high confidence. SeqMule integrates 5 alignment tools, 5 variant calling algorithms and accepts various combinations all by one-line command, therefore allowing highly flexible yet fully automated variant calling. In a modern machine (2 Intel Xeon X5650 CPUs, 48 GB memory), when fast turn-around is needed, SeqMule generates annotated VCF files in a day from a 30X whole-genome sequencing data set; when more accurate calling is needed, SeqMule generates consensus call set that improves over single callers, as measured by both Mendelian error rate and consistency. SeqMule supports Sun Grid Engine for parallel processing, offers turn-key solution for deployment on Amazon Web Services, allows quality check, Mendelian error check, consistency evaluation, HTML-based reports. SeqMule is available at http://seqmule.openbioinformatics.org.
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