Evidence map›Paper›PMID 30241460›Full record

ArticleBMC bioinformatics2018

Progressive multiple sequence alignment with indel evolution.

Massimo Maiolo, Xiaolei Zhang, Manuel Gil, Maria Anisimova

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2018. 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
1.2field-weighted citation impact, top 21% of its field
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, 27 citations in OpenAlex.

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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

4 authors at 3 institutions in 2 countries.

Massimo MaioloInstitute of Applied Simulation, School of Life Sciences and Facility Management, Zurich University of Applied Sciences (ZHAW), Grüentalstrasse 14, P.O. Box, Waedenswil, CH-8820, Switzerland.
Xiaolei ZhangNational Heart and Lung Institute, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK.
Manuel GilInstitute of Applied Simulation, School of Life Sciences and Facility Management, Zurich University of Applied Sciences (ZHAW), Grüentalstrasse 14, P.O. Box, Waedenswil, CH-8820, Switzerland.
Maria AnisimovaInstitute of Applied Simulation, School of Life Sciences and Facility Management, Zurich University of Applied Sciences (ZHAW), Grüentalstrasse 14, P.O. Box, Waedenswil, CH-8820, Switzerland. maria.anisimova@zhaw.ch.
ZHAW Zurich University of Applied Sciences · CHImperial College London · GBSIB Swiss Institute of Bioinformatics · CH

Funding

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung 31003A_157064Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung 31003A_176316
6 · The paper itself

Abstract

backgroundSequence alignment is crucial in genomics studies. However, optimal multiple sequence alignment (MSA) is NP-hard. Thus, modern MSA methods employ progressive heuristics, breaking the problem into a series of pairwise alignments guided by a phylogeny. Changes between homologous characters are typically modelled by a Markov substitution model. In contrast, the dynamics of indels are not modelled explicitly, because the computation of the marginal likelihood under such models has exponential time complexity in the number of taxa. But the failure to model indel evolution may lead to artificially short alignments due to biased indel placement, inconsistent with phylogenetic relationship.

resultsRecently, the classical indel model TKF91 was modified to describe indel evolution on a phylogeny via a Poisson process, termed PIP. PIP allows to compute the joint marginal probability of an MSA and a tree in linear time. We present a new dynamic programming algorithm to align two MSAs -represented by the underlying homology paths- by full maximum likelihood under PIP in polynomial time, and apply it progressively along a guide tree. We have corroborated the correctness of our method by simulation, and compared it with competitive methods on an illustrative real dataset.

conclusionsOur MSA method is the first polynomial time progressive aligner with a rigorous mathematical formulation of indel evolution. The new method infers phylogenetically meaningful gap patterns alternative to the popular PRANK, while producing alignments of similar length. Moreover, the inferred gap patterns agree with what was predicted qualitatively by previous studies. The algorithm is implemented in a standalone C++ program: https://github.com/acg-team/ProPIP . Supplementary data are available at BMC Bioinformatics online.

Indexed as

AlgorithmsEvolution, MolecularINDEL MutationPhylogenyHumansProbabilitySequence AlignmentDynamic programmingIndelPhylogenyPoisson processSequence alignment

Identifiers

PMID30241460
PMCPMC6151001
OpenAlexW2890963022

What OpenQuestion 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 OpenQuestion graph.