IMSA pipeline

IMSA specifications

Information


Unique identifier OMICS_15201
Name IMSA
Alternative name Integrated Metagenomic Sequence Analysis
Software type Package/Module
Interface Command line interface
Restrictions to use None
Input data Takes input sequence from high throughput datasets and utilizes a user-defined host database to filter out host sequence.
Output data Assigns a score to each node of the taxonomy based on read frequency, and can output this as a taxonomy report suitable for cluster analysis or as a taxonomy map (TaxMap). IMSA can also output the specific sequence reads assigned to a taxon of interest for downstream analysis.
Operating system Unix/Linux
Programming languages Python
License GNU General Public License version 3.0
Computer skills Advanced
Stability Stable
Maintained Yes

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Maintainer


  • person_outline Aleksey Porollo <>

Publications for Integrated Metagenomic Sequence Analysis

IMSA IN pipelines

 (3)
2014
PMCID: 4102619
PMID: 24608988
DOI: 10.1038/jid.2014.127

[…] priming. libraries were multiplexed and sequenced on an illumina hiseq 2000 platform and 187–242 million 50 bp paired-end reads were obtained per sample., metagenomic analysis was performed with the integrated metagenomic sequence analysis (imsa) package (dimon et al. 2013). the samples were also analyzed by dna microarray and assigned to the intrinsic gene expression subset (milano et al. […]

2014
PMCID: 4102619
PMID: 24608988
DOI: 10.1038/jid.2014.127

[…] on an illumina hiseq 2000 platform and 187–242 million 50 bp paired-end reads were obtained per sample., metagenomic analysis was performed with the integrated metagenomic sequence analysis (imsa) package (dimon et al. 2013). the samples were also analyzed by dna microarray and assigned to the intrinsic gene expression subset (milano et al. 2008). all four of the ssc patients […]

2014
PMCID: 4102619
PMID: 24608988
DOI: 10.1038/jid.2014.127

[…] rna-seq data from these eight patients are available at ncbi geo at accession number gsexxxxx (in process, number will be added in proof)., human reads were filtered from the rna-seq read sets using imsa (dimon et al. 2013). reads were quality filtered to remove any reads with more than 3 bases with a quality score below 15. next, human reads were removed by progressively more stringent […]

IMSA institution(s)
Department of Dermatology, University of California San Francisco, San Francisco, CA, USA; Leeds Institute of Molecular Medicine, St James’s University Hospital, Leeds, UK; Department of Electrical Engineering and Computing Systems, University of Cincinnati, Cincinnati, OH, USA; The Center for Autoimmune Genomics and Etiology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA; Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA; Division of Infectious Diseases, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA
IMSA funding source(s)
This work was supported by the National Institutes of Health [5R01HL119190].

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