Evidence map›Paper›PMID 25883146›Full record

ArticleNucleic acids research2015

GUIDANCE2: accurate detection of unreliable alignment regions accounting for the uncertainty of multiple parameters.

Itamar Sela, Haim Ashkenazy, Kazutaka Katoh, Tal Pupko

Abstract read
In one paragraph

Article in Nucleic acids research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 380 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
380citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

380 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  8. Taxonomy and Phylogeny of Two NewAnimals : an open access journal from MDPI · 2026
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320 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors.

Itamar SelaDepartment of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel-Aviv University, Tel-Aviv 6997801, Israel.
Haim AshkenazyDepartment of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel-Aviv University, Tel-Aviv 6997801, Israel.
Kazutaka KatohImmunology Frontier Research Center, Osaka University, Suita, Osaka 565-0871, Japan Computational Biology Research Center, The National Institute of Advanced Industrial Science and Technology (AIST), Tokyo 135-0064, Japan.
Tal PupkoDepartment of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel-Aviv University, Tel-Aviv 6997801, Israel talp@post.tau.ac.il.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Inference of multiple sequence alignments (MSAs) is a critical part of phylogenetic and comparative genomics studies. However, from the same set of sequences different MSAs are often inferred, depending on the methodologies used and the assumed parameters. Much effort has recently been devoted to improving the ability to identify unreliable alignment regions. Detecting such unreliable regions was previously shown to be important for downstream analyses relying on MSAs, such as the detection of positive selection. Here we developed GUIDANCE2, a new integrative methodology that accounts for: (i) uncertainty in the process of indel formation, (ii) uncertainty in the assumed guide tree and (iii) co-optimal solutions in the pairwise alignments, used as building blocks in progressive alignment algorithms. We compared GUIDANCE2 with seven methodologies to detect unreliable MSA regions using extensive simulations and empirical benchmarks. We show that GUIDANCE2 outperforms all previously developed methodologies. Furthermore, GUIDANCE2 also provides a set of alternative MSAs which can be useful for downstream analyses. The novel algorithm is implemented as a web-server, available at: http://guidance.tau.ac.il.

Indexed as

SoftwareAlgorithmsInternetSequence AlignmentUncertainty

Identifiers

PMID25883146
PMCPMC4489236

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Registered trials

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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.