Evidence map›Paper›PMID 27597435›Full record

ArticleBMC bioinformatics2016

LMAP: Lightweight Multigene Analyses in PAML.

Emanuel Maldonado, Daniela Almeida, Tibisay Escalona, Imran Khan, Vitor Vasconcelos, Agostinho Antunes

Abstract readEvaluation Study
In one paragraph

Article in BMC bioinformatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

11 citing papers in PubMed.

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4 · The record

Corrections and comments

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

6 authors.

Emanuel MaldonadoCIIMAR/CIMAR - Interdisciplinary Centre of Marine and Environmental Research, University of Porto, Terminal de Cruzeiros do Porto de Leixões, Avenida General Norton de Matos, s/n, 4450-208, Matosinhos, Portugal.
Daniela AlmeidaCIIMAR/CIMAR - Interdisciplinary Centre of Marine and Environmental Research, University of Porto, Terminal de Cruzeiros do Porto de Leixões, Avenida General Norton de Matos, s/n, 4450-208, Matosinhos, Portugal.
Tibisay EscalonaCIIMAR/CIMAR - Interdisciplinary Centre of Marine and Environmental Research, University of Porto, Terminal de Cruzeiros do Porto de Leixões, Avenida General Norton de Matos, s/n, 4450-208, Matosinhos, Portugal.
Imran KhanCIIMAR/CIMAR - Interdisciplinary Centre of Marine and Environmental Research, University of Porto, Terminal de Cruzeiros do Porto de Leixões, Avenida General Norton de Matos, s/n, 4450-208, Matosinhos, Portugal.
Vitor VasconcelosCIIMAR/CIMAR - Interdisciplinary Centre of Marine and Environmental Research, University of Porto, Terminal de Cruzeiros do Porto de Leixões, Avenida General Norton de Matos, s/n, 4450-208, Matosinhos, Portugal.
Agostinho AntunesCIIMAR/CIMAR - Interdisciplinary Centre of Marine and Environmental Research, University of Porto, Terminal de Cruzeiros do Porto de Leixões, Avenida General Norton de Matos, s/n, 4450-208, Matosinhos, Portugal. aantunes@ciimar.up.pt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundUncovering how phenotypic diversity arises and is maintained in nature has long been a major interest of evolutionary biologists. Recent advances in genome sequencing technologies have remarkably increased the efficiency to pinpoint genes involved in the adaptive evolution of phenotypes. Reliability of such findings is most often examined with statistical and computational methods using Maximum Likelihood codon-based models (i.e., site, branch, branch-site and clade models), such as those available in codeml from the Phylogenetic Analysis by Maximum Likelihood (PAML) package. While these models represent a well-defined workflow for documenting adaptive evolution, in practice they can be challenging for researchers having a vast amount of data, as multiple types of relevant codon-based datasets are generated, making the overall process hard and tedious to handle, error-prone and time-consuming.

resultsWe introduce LMAP (Lightweight Multigene Analyses in PAML), a user-friendly command-line and interactive package, designed to handle the codeml workflow, namely: directory organization, execution, results gathering and organization for Likelihood Ratio Test estimations with minimal manual user intervention. LMAP was developed for the workstation multi-core environment and provides a unique advantage for processing one, or more, if not all codeml codon-based models for multiple datasets at a time. Our software, proved efficiency throughout the codeml workflow, including, but not limited, to simultaneously handling more than 20 datasets.

conclusionsWe have developed a simple and versatile LMAP package, with outstanding performance, enabling researchers to analyze multiple different codon-based datasets in a high-throughput fashion. At minimum, two file types are required within a single input directory: one for the multiple sequence alignment and another for the phylogenetic tree. To our knowledge, no other software combines all codeml codon substitution models of adaptive evolution. LMAP has been developed as an open-source package, allowing its integration into more complex open-source bioinformatics pipelines. LMAP package is released under GPLv3 license and is freely available at http://lmapaml.sourceforge.net/ .

Indexed as

CodonComputational BiologyInternetPhylogenyProteinsSequence AlignmentSoftwareCodonProteinsAdaptive evolutioncodemlCodon substitution modelsMulti-coreMultigenePAMLSoftware package

Identifiers

PMID27597435
PMCPMC5011788

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.