Abstracts

Oral Presentation Abstracts
n S4:6
CFSAN SNP PIPELINE: A WHOLE GENOME
SEQUENCE DATA ANALYSIS PIPELINE FOR
FOOD-BORNE PATHOGENS
Y. Luo, J. Pettengill, J. Baugher, H. Rand, S.
Davis;
FDA/CFSAN, College Park, MD.
In support of the analysis of whole genome sequence
data (WGS) for closely related pathogens
in food-borne outbreaks, the Center for
Food Safety and Applied Nutrition (CFSAN)
at the FDA has developed a reference-based
software pipeline for high quality SNP identification
and analysis. This software pipeline
combines into a single package the mapping of
WGS reads to a reference genome, processing
of those mapping files, identification of variant
sites, and production of a SNP matrix. Additional
features include a summary table of the
results, soft-links to minimize data storage, and
the ability to switch between workstations and
computer clusters with minimal effort. The CF-
SAN SNP Pipeline is currently used in production
mode to analyze WGS data from isolates
related to food-borne illnesses. The pipeline is
used when outbreak investigations are ongoing
to link samples and to provide information for
decision-makers. It is also used retrospectively
to aid in the analysis of closed outbreaks. The
CFSAN SNP Pipeline is reference-based,
and so a reference must be provided. Isolate
sequence data must be in fastq format but can
either be paired-end or single-read data. All
analysis steps are run automatically, and only
depend on the proper organization of the input
files and identification of a suitable reference.
Additionally, each of the analysis steps can be
run using individual shell scripts. The addition
of new samples is very straightforward, and result
files from previous portions of the analysis
that do not need to be regenerated are reused.
This greatly reduces the computational time
when adding new samples as the mapping and
pileup steps are not redone. The pipeline will
run without problems on current workstations,
and will run on high performance computing
clusters with either Torque or Grid Engine job
schedulers. The CFSAN SNP Pipeline is written
in a combination of Bash and Python. The
code is designed to run on Linux platforms
with bash and python. BioPython must be
installed in tandem with three executable software
dependencies, Bowtie2, SAMtools, and
VarScan. Substantial effort has been devoted to
making the software robust, well-documented,
and easy to use. The following links provide
for access to the source code, the documentation,
and the Python package. Also provided is
the current publication reference. Source code:
https://github.com/CFSAN-Biostatistics/snppipeline.
Documentation: http://snp-pipeline.
rtfd.org. PyPI package: https://pypi.python.
org/pypi/snp-pipeline. Reference publication:
Pettengill JB, Luo Y, Davis S, Chen Y, Gonzalez-Escalona
N, Ottesen A, Rand H, Allard
MW, Strain​ E An evaluation of alternative
methods for constructing phylogenies from
whole genome sequence data: A case study
with Salmonella.
n S4:7
ASSEMBLING WHOLE GENOMES FROM
MIXED MICROBIAL COMMUNITIES USING
HI-C
I. Liachko 1 , J. N. Burton 1 , L. Sycuro 2 , A. H.
Wiser 2 , D. N. Fredricks 2 , M. J. Dunham 1 , J.
Shendure 1 ;
1
University of Washington, Seattle, WA, 2 Fred
Hutchinson Cancer Research Center, Seattle,
WA.
Assembly of whole genomes from next-generation
sequencing is inhibited by the lack of
contiguity information in short-read sequencing.
This limitation also impedes metagenome
assembly, since one cannot tell which sequences
originate from the same species within
a population. We have overcome these bottlenecks
by adapting a chromosome conformation
capture technique (Hi-C) for the deconvolution
of metagenomes and the scaffolding of de novo
assemblies of individual genomes. In modeling
the 3D structure of a genome, chromosome
ASM Conference on Rapid Next-Generation Sequencing and Bioinformatic
Pipelines for Enhanced Molecular Epidemiologic Investigation of Pathogens
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