seer specifications

Information


Unique identifier OMICS_21699
Name seer
Alternative names Sequence Element EnRichment, pyseer
Software type Pipeline/Workflow
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages C++, Perl, Python
License GNU General Public License version 3.0
Computer skills Advanced
Version 1.1.4
Stability Stable
Requirements
gzstream, armadillo, boost, dlib, HDF5, gcc, gcc libstdc++
Maintained Yes

Download


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Versioning


No version available

Documentation


Maintainer


  • person_outline Jukka Corander

Additional information


A python implementation is available at https://github.com/mgalardini/pyseer http://pyseer.readthedocs.io/en/master/

Publications for Sequence Element EnRichment

seer citations

 (2)
library_books

Horizontal antimicrobial resistance transfer drives epidemics of multiple Shigella species

2018
Nat Commun
PMCID: 5899146
PMID: 29654279
DOI: 10.1038/s41467-018-03949-8

[…] Sequence element enrichment analysis was run on all 357 UK cross-sectional isolates with the 103 isolates belonging to MSMA sublineages being a binary phenotype. Assemblies were generated using a pipe […]

library_books

Monomorphic genotypes within a generalist lineage of Campylobacter jejuni show signs of global dispersion

2016
Microb Genom
PMCID: 5359405
PMID: 28348829
DOI: 10.1099/mgen.0.000088

[…] To identify genetic signals overrepresented in strains originating from Finland and the Baltic countries (analysed as a group designated ‘Baltic’) or the UK, GWAS was performed using sequence element enrichment analysis as described in , with the minimum and maximum length of k-mers equal to 10 and 100, respectively. The population structure was accounted for by the hierBAPS clust […]

seer institution(s)
Department of Microbiology, New York University School of Medicine, New York, NY, USA; European Bioinformatics Institute (EMBL-EBI), Hinxton, UK; Infection Genomics, Wellcome Sanger Institute, Hinxton, UK; Department of Biostatistics, University of Oslo, Oslo, Norway; Helsinki Institute of Information Technology (HIIT), Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
seer funding source(s)
Supported by grants from the United States Public Health Service (AI038446 and AI105168) and by the ERC (grant no. 742158).

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