PGAP: pan-genomes analysis pipeline
By Yongbing Zhao, Jiayan Wu, Junhui Yang, Shixiang Sun, Jingfa Xiao, Jun Yu. Bioinform., 2011
451 citations recorded by the source corpus.
Summary: With the rapid development of DNA sequencing technology, increasing bacteria genome data enable the biologists to dig the evolutionary and genetic information of prokaryotic species from pan-genome sight. Therefore, the high-efficiency pipelines for pan-genome analysis are mostly needed. We have developed a new pan-genome analysis pipeline (PGAP), which can perform five analytic functions with only one command, including cluster analysis of functional genes, pan-genome profile analysis, genetic variation analysis of functional genes, species evolution analysis and function enrichment analysis of gene clusters. PGAP's performance has been evaluated on 11 Streptococcus pyogenes strains. Availability:PGAP is developed with Perl script on the Linux Platform and the package is freely available from http://pgap.sf.net. Contact: junyu@big.ac.cn; xiaojingfa@big.ac.cn Supplementary information: Supplementary data are available at Bioinformatics online.
Subfields: Food Science, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/3ed7a7fe317879001daf72c8f8c12d2f7556c514
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In Food Science
In Molecular Biology
- Julian Parkhill
- Daniel Falush
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- Chitra Dutta
- Jacqueline A. Keane
- Narendrakumar M. Chaudhari
- Martin Hunt
- Robert C. Edgar
Citations in the corpus
- GET_HOMOLOGUES, a Versatile Software Package for Scalable and Robust Microbial Pangenome Analysis (2013, unknown): “Unlike similar tools (43–45), which require the user to provide precomputed sequencesimilarityresults,GET_HOMOLOGUESexplicitlytakes careofBLASTandoptionalPfamsearches.”
- Roary: rapid large-scale prokaryote pan genome analysis (2015, methodology): “PanOCT and PGAP require an all-against-all comparison using BLAST, which means the running time grows non-linearly with the size of input data and is computationally infeasible with large datasets.”
- BPGA- an ultra-fast pan-genome analysis pipeline (2016, methodology): “S1) 28 .”