MELT specifications

Information


Unique identifier OMICS_12626
Name Mobile Element Locator Tool
Software type Package/Module
Interface Command line interface
Restrictions to use Academic or non-commercial use
Biological technology Illumina
Operating system Unix/Linux
Programming languages Java
Computer skills Advanced
Version 2.0.2
Stability Stable
Requirements Bowtie2
Maintained Yes

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Additional information


http://melt.igs.umaryland.edu/manual.php

MELT article

MELT citation

2017
PMCID: 5389967

[…] genomic copies. based on the low divergence exhibited by these groups (novick et al., 2009), and our intention to generate a conservative estimate, we selected an acceptable error rate of 2%., mobile element locator tool operates on bwa-aligned re-sequenced genomes, so for each anolis sample, quality-trimmed fastq reads were aligned to the anocar2.0 genome using the bwa-mem short read […]

MELT institution(s)
Program in Molecular Medicine, University of Maryland School of Medicine, Baltimore, MD, USA; Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA; Greenebaum Cancer Center, University of Maryland School of Medicine, Baltimore, MD, USA; Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA; Division of Gastroenterology, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA; Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA; Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA; Department of Human Genetics, University of Michigan Medical School, Ann Arbor, MI, USA
MELT funding source(s)
Supported by grants: F31 HG009223, T32 DK067872, R01 CA166661, and R01 HG002898.

MELT reviews

 (2)
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Robert P. Ruggiero

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Desktop
We have been using MELT on non-model genomes and it's been great (http://journal.frontiersin.org/article/10.3389/fgene.2017.00044/full).
MELT is easy to work with and gives consistent reliable results.

Daniel Webber

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Desktop
MELT was easy to install and run on SGE! It called our Alu and L1 RIPs accurately to the bp. It does a great job at integrating prior calls, and its genotyping is consistent between samples. It is more accurate then the other tools that we have used for calling transposable elements.

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