Evidence map›Paper›PMID 42867778›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2027

A Simplified Guide to Whole-Genome Sequence Analysis of Salmonella on the Command Line.

Menuka Bhandari, Jelmer W Poelstra, Gireesh Rajashekara

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Article in Methods in molecular biology (Clifton, N.J.), 2027. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Menuka BhandariResearch and Analytical Service Cores, College of Food, Agricultural and Environmental Sciences, The Ohio State University, Wooster, OH, USA.ORCID http://orcid.org/0009-0004-0630-0837
Jelmer W PoelstraResearch and Analytical Service Cores, College of Food, Agricultural and Environmental Sciences, The Ohio State University, Wooster, OH, USA.ORCID http://orcid.org/0000-0002-3514-7462
Gireesh RajashekaraDepartment of Pathobiology, College of Veterinary Medicine, University of Illinois, Urbana-Champaign, Urbana, IL, USA. gireesh2@illinois.edu.ORCID http://orcid.org/0000-0003-2443-6733

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the rapid development of sequencing technologies, whole-genome sequencing (WGS) is now easily accessible across various domains. Bacterial WGS has started to be routinely used in research and public health laboratories for clinical diagnostics, outbreak risk prediction, and pathogen characterization. WGS of foodborne pathogens allows for rapid, accurate identification and typing of pathogens, and detailed characterization of genomic features such as antimicrobial resistance genes, virulence genes, and plasmids. Salmonella, an important foodborne pathogen, is the leading cause of deaths associated with foodborne illness in the United States, with almost 420 deaths reported annually. Due to the affordability of short-read WGS and its higher discriminatory power, many public health laboratories and regulatory agencies have replaced traditional identification and typing techniques with WGS of Salmonella. However, there is a lack of easy-to-follow guides to analyze WGS datasets and generate reproducible results. This chapter provides detailed step-by-step commands for the analysis of the short-read WGS data of Salmonella, from quality control, trimming of unwanted sequences, genome assembly and annotation, to multi-locus sequence typing, serotyping, antimicrobial resistance gene identification, virulence gene identification, and phylogenetic tree construction, all using programs executed from the Unix shell command line. As such, this chapter serves as a user-friendly guide for WGS data analysis in Salmonella. Moreover, most of the bioinformatics programs described in this chapter can also be used to analyze WGS data of other Gram-positive and Gram-negative bacteria.

Indexed as

Genome, BacterialSalmonellaWhole Genome SequencingComputational BiologyGenomicsMultilocus Sequence TypingSoftwareBacteriaBioinformatic programsCommandsSalmonellaWhole-genome sequencing

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.