A computational genomics pipeline for prokaryotic sequencing projects
Supporting Files
-
Jun 02 2010
-
File Language:
English
Details
-
Alternative Title:Bioinformatics
-
Personal Author:Kislyuk, Andrey O. ; Katz, Lee S. ; Agrawal, Sonia ; Hagen, Matthew S. ; Conley, Andrew B. ; Jayaraman, Pushkala ; Nelakuditi, Viswateja ; Humphrey, Jay C. ; Sammons, Scott A. ; Govil, Dhwani ; Mair, Raydel D. ; Tatti, Kathleen M. ; Tondella, Maria L. ; Harcourt, Brian H. ; Mayer, Leonard W. ; Jordan, I. King
-
Description:New sequencing technologies have accelerated research on prokaryotic genomes and have made genome sequencing operations outside major genome sequencing centers routine. However, no off-the-shelf solution exists for the combined assembly, gene prediction, genome annotation and data presentation necessary to interpret sequencing data. The resulting requirement to invest significant resources into custom informatics support for genome sequencing projects remains a major impediment to the accessibility of high-throughput sequence data.|We present a self-contained, automated high-throughput open source genome sequencing and computational genomics pipeline suitable for prokaryotic sequencing projects. The pipeline has been used at the Georgia Institute of Technology and the Centers for Disease Control and Prevention for the analysis of Neisseria meningitidis and Bordetella bronchiseptica genomes. The pipeline is capable of enhanced or manually assisted reference-based assembly using multiple assemblers and modes; gene predictor combining; and functional annotation of genes and gene products. Because every component of the pipeline is executed on a local machine with no need to access resources over the Internet, the pipeline is suitable for projects of a sensitive nature. Annotation of virulence-related features makes the pipeline particularly useful for projects working with pathogenic prokaryotes.|The pipeline is licensed under the open-source GNU General Public License and available at the Georgia Tech Neisseria Base (http://nbase.biology.gatech.edu/). The pipeline is implemented with a combination of Perl, Bourne Shell and MySQL and is compatible with Linux and other Unix systems.
-
Subjects:
-
Source:Bioinformatics. 2010; 26(15):1819-1826.
-
Pubmed ID:20519285
-
Pubmed Central ID:PMC2905547
-
Document Type:
-
Funding:
-
Place as Subject:
-
Volume:26
-
Issue:15
-
Collection(s):
-
Main Document Checksum:urn:sha256:f7647defd74da8531b0001c92f662fe56454bb510cb9803d5a1d8bd83d43d77d
-
Download URL:
-
File Type:
Supporting Files
-
html
File Language:
English
ON THIS PAGE
CDC STACKS serves as an archival repository of CDC-published products including
scientific findings,
journal articles, guidelines, recommendations, or other public health information authored or
co-authored by CDC or funded partners.
As a repository, CDC STACKS retains documents in their original published format to ensure public access to scientific information.
As a repository, CDC STACKS retains documents in their original published format to ensure public access to scientific information.
You May Also Like
COLLECTION
CDC Public Access