Pitfalls in supermatrix phylogenomics

In the mid-2000s, molecular phylogenetics turned into phylogenomics, a development that improved the resolution of phylogenetic trees through a dramatic reduction in stochastic error. While some then predicted “the end of incongruence”, it soon appeared that analysing large amounts of sequence data...
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Autor*in:	Hervé Philippe [verfasserIn] Damien M. de Vienne [verfasserIn] Vincent Ranwez [verfasserIn] Béatrice Roure [verfasserIn] Denis Baurain [verfasserIn] Frédéric Delsuc [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2017

Schlagwörter:	phylogenomics supermatrix systematic error data quality incongruence

Übergeordnetes Werk:	In: European Journal of Taxonomy - Consortium of European Natural History Museums, 2013, (2017), 283
Übergeordnetes Werk:	year:2017 ; number:283

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.5852/ejt.2017.283

Katalog-ID:	DOAJ058304177

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allfieldsSound	10.5852/ejt.2017.283 doi (DE-627)DOAJ058304177 (DE-599)DOAJa2c7bdc623e3471c941579f8f1149ee1 DE-627 ger DE-627 rakwb eng QL1-991 QK1-989 Hervé Philippe verfasserin aut Pitfalls in supermatrix phylogenomics 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In the mid-2000s, molecular phylogenetics turned into phylogenomics, a development that improved the resolution of phylogenetic trees through a dramatic reduction in stochastic error. While some then predicted “the end of incongruence”, it soon appeared that analysing large amounts of sequence data without an adequate model of sequence evolution amplifies systematic error and leads to phylogenetic artefacts. With the increasing flood of (sometimes low-quality) genomic data resulting from the rise of high-throughput sequencing, a new type of error has emerged. Termed here “data errors”, it lumps together several kinds of issues affecting the construction of phylogenomic supermatrices (e.g., sequencing and annotation errors, contaminant sequences). While easy to deal with at a single-gene scale, such errors become very difficult to avoid at the genomic scale, both because hand curating thousands of sequences is prohibitively time-consuming and because the suitable automated bioinformatics tools are still in their infancy. In this paper, we first review the pitfalls affecting the construction of supermatrices and the strategies to limit their adverse effects on phylogenomic inference. Then, after discussing the relative non-issue of missing data in supermatrices, we briefly present the approaches commonly used to reduce systematic error. phylogenomics supermatrix systematic error data quality incongruence Zoology Botany Damien M. de Vienne verfasserin aut Vincent Ranwez verfasserin aut Béatrice Roure verfasserin aut Denis Baurain verfasserin aut Frédéric Delsuc verfasserin aut In European Journal of Taxonomy Consortium of European Natural History Museums, 2013 (2017), 283 (DE-627)670633690 (DE-600)2633909-2 21189773 nnns year:2017 number:283 https://doi.org/10.5852/ejt.2017.283 kostenfrei https://doaj.org/article/a2c7bdc623e3471c941579f8f1149ee1 kostenfrei http://www.europeanjournaloftaxonomy.eu/index.php/ejt/article/view/407 kostenfrei https://doaj.org/toc/2118-9773 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_267 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2017 283
language	English
source	In European Journal of Taxonomy (2017), 283 year:2017 number:283
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topic_facet	phylogenomics supermatrix systematic error data quality incongruence Zoology Botany
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container_title	European Journal of Taxonomy
authorswithroles_txt_mv	Hervé Philippe @@aut@@ Damien M. de Vienne @@aut@@ Vincent Ranwez @@aut@@ Béatrice Roure @@aut@@ Denis Baurain @@aut@@ Frédéric Delsuc @@aut@@
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callnumber-first	Q - Science
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title	Pitfalls in supermatrix phylogenomics
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abstract	In the mid-2000s, molecular phylogenetics turned into phylogenomics, a development that improved the resolution of phylogenetic trees through a dramatic reduction in stochastic error. While some then predicted “the end of incongruence”, it soon appeared that analysing large amounts of sequence data without an adequate model of sequence evolution amplifies systematic error and leads to phylogenetic artefacts. With the increasing flood of (sometimes low-quality) genomic data resulting from the rise of high-throughput sequencing, a new type of error has emerged. Termed here “data errors”, it lumps together several kinds of issues affecting the construction of phylogenomic supermatrices (e.g., sequencing and annotation errors, contaminant sequences). While easy to deal with at a single-gene scale, such errors become very difficult to avoid at the genomic scale, both because hand curating thousands of sequences is prohibitively time-consuming and because the suitable automated bioinformatics tools are still in their infancy. In this paper, we first review the pitfalls affecting the construction of supermatrices and the strategies to limit their adverse effects on phylogenomic inference. Then, after discussing the relative non-issue of missing data in supermatrices, we briefly present the approaches commonly used to reduce systematic error.
abstractGer	In the mid-2000s, molecular phylogenetics turned into phylogenomics, a development that improved the resolution of phylogenetic trees through a dramatic reduction in stochastic error. While some then predicted “the end of incongruence”, it soon appeared that analysing large amounts of sequence data without an adequate model of sequence evolution amplifies systematic error and leads to phylogenetic artefacts. With the increasing flood of (sometimes low-quality) genomic data resulting from the rise of high-throughput sequencing, a new type of error has emerged. Termed here “data errors”, it lumps together several kinds of issues affecting the construction of phylogenomic supermatrices (e.g., sequencing and annotation errors, contaminant sequences). While easy to deal with at a single-gene scale, such errors become very difficult to avoid at the genomic scale, both because hand curating thousands of sequences is prohibitively time-consuming and because the suitable automated bioinformatics tools are still in their infancy. In this paper, we first review the pitfalls affecting the construction of supermatrices and the strategies to limit their adverse effects on phylogenomic inference. Then, after discussing the relative non-issue of missing data in supermatrices, we briefly present the approaches commonly used to reduce systematic error.
abstract_unstemmed	In the mid-2000s, molecular phylogenetics turned into phylogenomics, a development that improved the resolution of phylogenetic trees through a dramatic reduction in stochastic error. While some then predicted “the end of incongruence”, it soon appeared that analysing large amounts of sequence data without an adequate model of sequence evolution amplifies systematic error and leads to phylogenetic artefacts. With the increasing flood of (sometimes low-quality) genomic data resulting from the rise of high-throughput sequencing, a new type of error has emerged. Termed here “data errors”, it lumps together several kinds of issues affecting the construction of phylogenomic supermatrices (e.g., sequencing and annotation errors, contaminant sequences). While easy to deal with at a single-gene scale, such errors become very difficult to avoid at the genomic scale, both because hand curating thousands of sequences is prohibitively time-consuming and because the suitable automated bioinformatics tools are still in their infancy. In this paper, we first review the pitfalls affecting the construction of supermatrices and the strategies to limit their adverse effects on phylogenomic inference. Then, after discussing the relative non-issue of missing data in supermatrices, we briefly present the approaches commonly used to reduce systematic error.
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