LAST pipeline

LAST specifications

Information


Unique identifier OMICS_15813
Name LAST
Interface Web user interface
Restrictions to use None
Input data The reference sequence(s), the query sequence(s).
Input format FASTA/FASTQ
Output data The alignment results.
Biological technology Oxford Nanopore
Programming languages C++
License GNU General Public License version 3.0
Computer skills Basic
Stability Stable
Maintained Yes

Subtool


  • LAST-TRAIN

Documentation


Maintainer


  • person_outline Martin Frith <>

Information


Unique identifier OMICS_15813
Name LAST
Software type Package/Module
Interface Command line interface
Restrictions to use None
Input data The reference sequence(s), the query sequence(s).
Output data The alignment results.
Operating system Unix/Linux
Programming languages C++
License GNU General Public License version 3.0
Computer skills Advanced
Version 833.0
Stability Stable
Maintained Yes

Subtool


  • LAST-TRAIN

Download


Versioning


Add your version

Documentation


Maintainer


  • person_outline Martin Frith <>

Publications for LAST

LAST IN pipelines

 (2)
2017
PMCID: 5726485
PMID: 29117310
DOI: 10.1093/dnares/dsx027

[…] (-b1); and 4) last with a gap existence cost of 12 (-a12), insertion existence cost of 15 (-a15), gap extension cost of 4 (-b4) and insertion extension cost of 4 (-b4) as determined according to the last-train.18 last uses the fastq quality data (with -q1) to obtain more accurate alignments.19 the gap costs correspond to a statistical model of the specific probabilities of opening and extending […]

2017
PMCID: 5726485
PMID: 29117310
DOI: 10.1093/dnares/dsx027

[…] quality data (with -q1) to obtain more accurate alignments.19 the gap costs correspond to a statistical model of the specific probabilities of opening and extending insertions and deletions. the last-train determines the probabilities (and therefore costs) that fit the given sequence data. in these data, insertions are rarer than deletions; thus, their cost is higher., using last […]

LAST institution(s)
Department of Computational Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany; Computational Biology Research Center, Tokyo, Japan; Graduate School of Frontier Sciences, University of Tokyo, Chiba, Japan
LAST funding source(s)
This work was supported by the German National Genome Research Network (NGFN-Plus, grant no. 01GS0815) and by INTEC Systems Institute, Inc.

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