Missing data and the design of phylogenetic analyses

By John J. Wiens. Journal of Biomedical Informatics, 2006

469 citations recorded by the source corpus.

Subfields: Genetics, Molecular Biology, Paleontology

View Paper: https://www.semanticscholar.org/paper/e4116a4495799c8923f5fb4ea462b3fb5bbcd7ed

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Genetics

1. Q. Xiang
2. A. Harris
3. P. B. Matheny
4. G. Weiblen
5. W. Clement
6. E. Vellinga
7. C. Mitter
8. D. Hibbett

In Molecular Biology

1. A. Harris
2. Q. Xiang
3. G. Weiblen
4. W. Clement
5. P. B. Matheny
6. E. Vellinga
7. C. Fišer
8. P. Trontelj

In Paleontology

1. P. B. Matheny
2. Q. Xiang
3. A. Harris
4. C. Fišer
5. P. Trontelj
6. B. Šket
7. G. Weiblen
8. W. Clement

Citations in the corpus

• Implied weighting and its utility in palaeontological datasets: a study using modelled phylogenetic matrices (2016, unknown): “…a strong signal (Wiens 2003b), and that characters with high levels of missing data can still improve phylogenetic accuracy under many conditions (Wiens 1998, 2003a, 2006; Edgecombe 2010; Wiens & Morrill 2011), while ignoring characters because of missing data can lead to loss of resolution…”
• Morphological and molecular evidence for phylogeny and classification of South American pitvipers, genera Bothrops, Bothriopsis, and Bothrocophias (Serpentes: Viperidae) (2009, unknown): “Wiens JJ. 2006.”
• Increased gene sampling yields robust support for higher‐level clades within Bombycoidea (Lepidoptera) (2011, background): “…that higher-level groups are still multiply sampled, and that no previous data are excluded, but the resulting data matrix will thereby have blocks of missing data, which may (Lemmon et al., 2009) or may not (Wiens, 2003, 2006) compromise phylogenetic accuracy by introducing a nonphylogenetic bias.”
• Estimating ancestral distributions of lineages with uncertain sister groups: a statistical approach to Dispersal–Vicariance Analysis and a case using Aesculus L. (Sapindaceae) including fossils (2009, methodology): “…DNA data is available, have been C© 2009 Institute of Botany, Chinese Academy of Sciences discussed (Nixon & Wheeler, 1992; Kearney, 2002; Kearney & Clark, 2003; Wiens, 2003, 2006) and observed in empirical studies (e.g. Rothwell & Nixon, 2006; Harris et al., 2009; but see Manos et al., 2007).”
• A fossil‐calibrated relaxed clock for Ephedra indicates an Oligocene age for the divergence of Asian and New World clades and Miocene dispersal into South America (2009, unknown): “Recent studies have found that reliable topologies may be obtained even in the face of large amounts of missing data (e.g. Wiens, 2003, 2006; McMahon & Sanderson, 2006; Smith et al., 2009).”
• A phylogenetic perspective on 160 years of troubled taxonomy of Niphargus (Crustacea: Amphipoda) (2008, background): “Incomplete data sets have been systematically investigated by Wiens (1998, 2003, 2005, 2006), who suggests that missing data does not per se hamper phylogenetic reconstructions.”
• A new subfamilial and tribal classification of the pantropical flowering plant family Annonaceae informed by molecular phylogenetics (2012, unknown): “Wiens JJ. 2006.”
• Major clades of Agaricales: a multilocus phylogenetic overview (2006, background): “Simulation studies show that the addition of taxa, despite large amounts of missing data, can benefit phylogenetic reconstructions (Wiens 2006).”
• Morphological Evolution in the Mulberry Family (Moraceae) (2009, background): “Moraceae have been divided into five tribes: Moreae, Artocarpeae, Dorstenieae, Castilleae, and Ficeae ( Berg 1977b ; Berg 2001 ).”
• A Total-Evidence Approach to Dating with Fossils, Applied to the Early Radiation of the Hymenoptera (2012, background): “On the other hand, such detrimental effects of missing data are probably weaker in the presence of a strong phylogenetic signal, and thus might have little impact when there is enough decisive data available (Lemmon et al. 2009; Wiens 2006; Wiens et al. 2010).”
• The revised classification of eukaryotes (2012, background): “Broader taxonomic sampling is likely the most important factor in alleviating these kinds of systematic biases (Heath et al. 2008; Hedtke et al. 2006; Zwickl and Hillis 2002), although adding more taxa may also introduce additional missing sequence data (Wiens 2006).”
• Missing data and the accuracy of Bayesian phylogenetics (2008, background): “Concerns about missing data may often determine what characters and taxa will be included in an analysis ( Wiens, 2006 ), even if this is not always stated explicitly by researchers.”
• Molecular Evolution of Zika Virus during Its Emergence in the 20th Century (2014, methodology): “This is in line with the use of Maximum Likelihood approaches, which is fairly robust to the introduction of gaps [64,65].”