Large Molecular Datasets Research Articles

Imaging Informatics: Toward Capturing and Processing Semantic Information in Radiology Images

To identify challenges and opportunities in imaging informatics that can lead to the use of images for discovery, and that can potentially improve the diagnostic accuracy of imaging professionals. Recent articles on imaging informatics and related articles from PubMed were reviewed and analyzed. Some new developments and challenges that recent research in imaging informatics will meet are identified and discussed. While much literature continues to be devoted to traditional imaging informatics topics of image processing, visualization, and computerized detection, three new trends are emerging: (1) development of ontologies to describe radiology reports and images, (2) structured reporting and image annotation methods to make image semantics explicit and machine-accessible, and (3) applications that use semantic image information for decision support to improve radiologist interpretation performance. The informatics methods being developed have similarities and synergies with recent work in the biomedical informatics community that leverage large high-throughput data sets, and future research in imaging informatics will build on these advances to enable discovery by mining large image databases. Imaging informatics is beginning to develop and apply knowledge representation and analysis methods to image datasets. This type of work, already commonplace in biomedical research with large scale molecular and clinical datasets, will lead to new ways for computers to work with image data. The new advances hold promise for integrating imaging with the rest of the patient record as well as molecular data, for new data-driven discoveries in imaging analogous to that in bioinformatics, and for improved quality of radiology practice.

The carbon versus mass diagram to visualize and exploit FTICR‐MS data of natural organic matter

A two-dimensional diagram is proposed, in which the carbon number of each formula is plotted against its nominal mass, to visualize large sets of molecular formula data that can be derived from data generated by ultrahigh-resolution Fourier transform ion cyclotron resonance-MS. In such a carbon versus mass (CvM) diagram, each formula (C(c)H(h)O(o)) is unambiguously described by c, its (nominal) mass and the parameter i = c + o. Calculations of chemically allowable formulas illustrate that organic molecules occupy only certain spaces in such a diagram. The extension of these spaces increases with molecular mass in x-direction (hydrogenation) and y-direction (oxygenation). The data sets of molecules determined in natural organic matter(NOM) occupy only a certain range of the allowable space. The intensity of the mass spectrometric signals can be included as the third dimension into a CvM diagram. Separate CvM diagrams can be plotted for NOM molecules that include different heteroatoms. The benefits of the CvM diagram are illustrated by application onto data sets of fulvic acids from riverine and marine origin, of secondary organic aerosol, including organosulfates and organonitrates, as well as of ozonation of fulvic acids. The CvM diagram is a useful tool to visualize the elemental regularities in NOM isolates as well as the differences between isolates. It may also be applicable to large sets of molecular formula data generated in other disciplines such as petroleum biogeochemistry or metabolomics.

When phylogenetic assumptions are violated: base compositional heterogeneity and among-site rate variation in beetle mitochondrial phylogenomics

The ability to generate large molecular datasets for phylogenetic studies benefits biologists, but such data expansion introduces numerous analytical problems. A typical molecular phylogenetic study implicitly assumes that sequences evolve under stationary, reversible and homogeneous conditions, but this assumption is often violated in real datasets. When an analysis of large molecular datasets results in unexpected relationships, it often reflects violation of phylogenetic assumptions, rather than a correct phylogeny. Molecular evolutionary phenomena such as base compositional heterogeneity and among-site rate variation are known to affect phylogenetic inference, resulting in incorrect phylogenetic relationships. The ability of methods to overcome such bias has not been measured on real and complex datasets. We investigated how base compositional heterogeneity and among-site rate variation affect phylogenetic inference in the context of a mitochondrial genome phylogeny of the insect order Coleoptera. We show statistically that our dataset is affected by base compositional heterogeneity regardless of how the data are partitioned or recoded. Among-site rate variation is shown by comparing topologies generated using models of evolution with and without a rate variation parameter in a Bayesian framework. When compared for their effectiveness in dealing with systematic bias, standard phylogenetic methods tend to perform poorly, and parsimony without any data transformation performs worst. Two methods designed specifically to overcome systematic bias, LogDet and a Bayesian method implementing variable composition vectors, can overcome some level of base compositional heterogeneity, but are still affected by among-site rate variation. A large degree of variation in both noise and phylogenetic signal among all three codon positions is observed. We caution and argue that more data exploration is imperative, especially when many genes are included in an analysis.

A new dimension in combining data? The use of morphology and phylogenomic data in metazoan systematics

AbstractGiribet, G. 2010. A new dimension in combining data? The use of morphology and phylogenomic data in metazoan systematics. —Acta Zoologica (Stockholm) 91: 11–19Animal phylogenies have been traditionally inferred by using the character state information derived from the observation of a diverse array of morphological and anatomical features, but the incorporation of molecular data into the toolkit of phylogenetic characters has shifted drastically the way researchers infer phylogenies. A main reason for this is the ease at which molecular data can be obtained, compared to, e.g., traditional histological and microscopical techniques. Researchers now routinely use genomic data for reconstructing relationships among animal phyla (using whole genomes or Expressed Sequence Tags) but the amount of morphological data available to study the same phylogenetic patterns has not grown accordingly. Given the disparity between the amounts of molecular and morphological data, some authors have questioned entire morphological programs. In this review I discuss issues related to the combinability of genomic and morphological data, the informativeness of each set of characters, and conclude with a discussion of how morphology could be made scalable by utilizing new techniques that allow for non‐intrusive examination of large amounts of preserved museum specimens. Morphology should therefore remains a strong field in evolutionary and comparative biology, as it continues to provide information for inferring phylogenetic patterns, is an important complement for the patterns derived from the molecular data, and it is the common nexus that allows studying fossil taxa with large data sets of molecular data.

Physicochemical property space distribution among human metabolites, drugs and toxins

BackgroundThe current approach to screen for drug-like molecules is to sieve for molecules with biochemical properties suitable for desirable pharmacokinetics and reduced toxicity, using predominantly biophysical properties of chemical compounds, based on empirical rules such as Lipinski's "rule of five" (Ro5). For over a decade, Ro5 has been applied to combinatorial compounds, drugs and ligands, in the search for suitable lead compounds. Unfortunately, till date, a clear distinction between drugs and non-drugs has not been achieved. The current trend is to seek out drugs which show metabolite-likeness. In identifying similar physicochemical characteristics, compounds have usually been clustered based on some characteristic, to reduce the search space presented by large molecular datasets. This paper examines the similarity of current drug molecules with human metabolites and toxins, using a range of computed molecular descriptors as well as the effect of comparison to clustered data compared to searches against complete datasets.ResultsWe have carried out statistical and substructure functional group analyses of three datasets, namely human metabolites, drugs and toxin molecules. The distributions of various molecular descriptors were investigated. Our analyses show that, although the three groups are distinct, present-day drugs are closer to toxin molecules than to metabolites. Furthermore, these distributions are quite similar for both clustered data as well as complete or unclustered datasets.ConclusionThe property space occupied by metabolites is dissimilar to that of drugs or toxin molecules, with current drugs showing greater similarity to toxins than to metabolites. Additionally, empirical rules like Ro5 can be refined to identify drugs or drug-like molecules that are clearly distinct from toxic compounds and more metabolite-like. The inclusion of human metabolites in this study provides a deeper insight into metabolite/drug/toxin-like properties and will also prove to be valuable in the prediction or optimization of small molecules as ligands for therapeutic applications.

Conflict and resolution between phylogenies inferred from molecular and phenotypic data sets for hagfish, lampreys, and gnathostomes

One of the most problematic issues in vertebrate phylogenetics is the disagreement between phenotypic and molecular inferences regarding the relationships among hagfishes, lampreys, and gnathostomes. Phenotypic characters support monophyly of lampreys and gnathostomes, whereas nearly all published analyses of molecular data sets support monophyly of hagfishes and lampreys. In this study I present results of phylogenetic analyses of combined phenotypic and molecular data sets that focus on relationships among hagfishes, lampreys, and gnathostomes. Maximum parsimony analyses of 115 phenotypic characters combined with 4,638 rRNA sites and more than 10,000 amino acids each result in monophyly of lampreys and gnathostomes, demonstrating that the addition of relatively few phenotypic characters can alter phylogenetic inferences from large molecular data sets. On the other hand, Bayesian analyses of the combined data sets support monophyly of hagfish and lampreys, indicating that model-based analyses may be prone to data "swamping," where the phylogenetic signal of the larger molecular data sets overwhelm the signal present in the much smaller phenotypic data set. Nodes that relate hagfish and lampreys were recovered at a low frequency in parametric bootstrapping analyses, indicating that the timing of diversification among hagfishes, lampreys, and gnathostomes has created a difficult phylogenetic problem for molecular data. The fact that addition of relatively few phenotypic characters can alter phylogenetic inferences of cyclostome monophyly obtained from molecular data sets, and the inability of simulated data sets to recover key nodes in the craniate phylogeny provide reasons to view the strong support for cyclostome monophyly inferred from molecular data sets with a measured degree of skepticism.

Weighting against homoplasy improves phylogenetic analysis of morphological data sets

AbstractThe problem of character weighting in cladistic analysis is revisited. The finding that, in large molecular data sets, removal of third positions (with more homoplasy) decreases the number of well supported groups has been interpreted by some authors as indicating that weighting methods are unjustified. Two arguments against that interpretation are advanced. Characters that collectively determine few well‐supported groups may be highly reliable when taken individually (as shown by specific examples), so that inferring greater reliability for sets of characters that lead to an increase in jackknife frequencies may not always be warranted. But even if changes in jackknife frequencies can be used to infer reliability, we demonstrate that jackknife frequencies in large molecular data sets are actually improved when downweighting characters according to their homoplasy but using properly rescaled functions (instead of the very strong standard functions, or the extreme of inclusion/exclusion); this further weakens the argument that downweighting homoplastic characters is undesirable. Last, we show that downweighting characters according to their homoplasy (using standard homoplasy‐weighting methods) on 70 morphological data sets (with 50–170 taxa), produces clear increases in jackknife frequencies. The results obtained under homoplasy weighting also appear more stable than results under equal weights: adding either taxa or characters, when weighting against homoplasy, produced results more similar to original analyses (i.e., with larger numbers of groups that continue being supported after addition of taxa or characters), with similar or lower error rates (i.e., proportion of groups recovered that subsequently turn out to be incorrect). Therefore, the same argument that had been advanced against homoplasy weighting in the case of large molecular data sets is an argument in favor of such weighting in the case of morphological data sets.© The Willi Hennig Society 2008.

A Signal Analysis Approach Applied to the Study of Sequence, Structure and Function of the Proteins

Computational chemistry is largely based on the use of quantitative descriptors of organic molecules, allowing for the analysis of large molecular data sets and for building models that link the chemico-physical and structural descriptions of molecules to their biological activity or chemical reactivity. In the case of the proteins, this approach is severely hampered by the need to take into consideration in a meaningful way the actual sequence of the aminoacid residues. From a purely mathematical perspective, the protein sequences can be viewed as a time series, where the role of time is played by the order of the aminoacid residues along the sequences. In turn, each individual residue can be considered as a single organic molecule that can be represented by the classical molecular descriptors. Thus, in principle the generation of order- dependent synthetic descriptors through the application of time series analysis can be used for building QSAR-like models of proteins. As a matter of fact, Recurrence Quantification Analysis (RQA) of hydrophobicity-coded sequences of proteins has already been demonstrated to be useful in protein science. In this paper, we show merits and pitfalls of RQA in different case studies, ranging from the global description of a large set of diverse proteins, to the study of the effect of mutations in the human cytochrome P450 system.

Endopterygote systematics – where do we stand and what is the goal (Hexapoda, Arthropoda)?

Abstract. Impressive progress has been made recently in the systematics of holometabolous insects. Nevertheless, important questions remain controversial, and uncertainties concerning the relationships of major lineages may even have increased. New analytical techniques have been developed and an immense wealth of molecular data has accumulated. Although no decisive breakthrough has yet been achieved, recent analyses of large molecular datasets have contributed greatly to the reconstruction of the phylogeny of several holometabolous lineages. Extensive combined analyses with substantial morphological datasets and molecular data comprising several genes (‘total evidence’) are still required for a well‐founded phylogenetic hypothesis for the entire group. Endopterygota monophyly is supported mainly by the specific and derived mode of development, which may be considered as a new evolutionary level within Hexapoda. The basal branching pattern remains controversial. A division into two large clades comprising Coleoptera (+ Strepsiptera?) + Neuropterida, on the one hand, and Hymenoptera + [Amphiesmenoptera + Antliophora (including Strepsiptera?)], on the other, appears plausible. Alternative hypotheses have been proposed based on wing characters and molecular data. The position of Strepsiptera remains unsolved. Mecoptera almost certainly is not monophyletic, as Siphonaptera are probably sister to Boreidae. Immense progress has been made in the reconstruction of the intraordinal relationships of all orders, thanks to increasing studies based on combined datasets. Common efforts of morphologists and molecular systematists probably will lead to further rapid progress. Several discoveries of new higher ranking taxa during recent years have revealed that large‐scale habitat destruction will not only have disastrous effects on global biodiversity, but also on the study of insect phylogeny and evolution.

Social informatics: Beyond emergence

Social informatics: Beyond emergence

Evolution and phylogeny of old world deer

The phylogenetic pattern and timing of the radiation of Old World deer was determined based on the complete mitochondrial cytochrome b gene from 33 Cervinae taxa. Using rooted and unrooted phylogenies derived from distinct theoretical approaches, strong support was achieved for monophyly of the Old World deer with muntjacs as sister group as well as for the divergence of at least three distinct genera: Rucervus, Dama, and Cervus. The latter clade comprises what have previously been regarded as the genera or subgenera Panolia, Rusa, Cervus, Sika, and probably Przewalskium. Our data also consistently confirmed paraphyly of nominate C. elaphus and did not support the monophyly of Axis. We used these molecular phylogenies to assess the homoplastic evolution of morphological, geographical, ecological, and selected behavioural character state differences within the Cervinae. Reliable fossil calibrations, large molecular data sets, and improved dating methods are shaping a molecular time scale for the evolutionary radiation of Old World deer that occurred at the Miocene/Pliocene transition and is largely compatible with existing palaeontological evidence. Using node ages estimated from sequence data, we estimated an average per-lineage diversification rate of 0.51 ± 0.1 species per million years (my) over roughly the last 6 mya.

Interactive exploration of fuzzy clusters using Neighborgrams

We describe an interactive method to generate a set of fuzzy clusters for classes of interest of a given, labeled data set. The presented method is therefore best suited for applications where the focus of analysis lies on a model for the minority class or for small to medium-sized data sets. The clustering algorithm creates one–dimensional models of the neighborhood for a set of patterns by constructing cluster candidates for each pattern of interest and then chooses the best subset of clusters that form a global model of the data. The accompanying visualization of these neighborhoods allows the user to interact with the clustering process by selecting, discarding, or fine–tuning potential cluster candidates. Clusters can be crisp or fuzzy and the latter leads to a substantial improvement of the classification accuracy. We demonstrate the performance of the underlying algorithm on several data sets from the StatLog project and show its usefulness for visual cluster exploration on the Iris data and a large molecular dataset from the National Cancer Institute.

A phylogeny of the extant Phocidae inferred from complete mitochondrial DNA coding regions

Despite extensive interest in the systematics of Pinnipedia, questions remain concerning phylogenetic relationships within the Phocidae or “true” seals. Relationships within the phocids and their placement relative to the remaining pinnipeds and major lineages of arctoid carnivores were examined using a large molecular data set consisting of 12 mitochondrial protein coding genes. Phylogenetic analysis including 15 extant species of the Phocidae, and representatives of the Otariidae, Odobenidae, Ursidae, Mustelidae, Canidae, and Felidae confirmed the monophyletic origins of the Pinnipedia within the Arctoidea. Slightly more support was found for an ursid affinity of the pinnipeds, however, this relationship remains contentious. The Phocidae were placed as the sister group to a common odobenid–otariid clade. Within the family Phocidae, strong support for the traditionally accepted subfamilies Phocinae (northern seals), and Monachinae (southern seals plus monk seals) was found. In contrast to recent suggestions, a monophyletic Monachus was strongly supported and was placed in a deep branching position within the Monachinae. Evidence from sequence divergence under a maximum likelihood model illustrated that the rarely used tribal distinction within the Monachinae are comparable, in terms of evolutionary distance, to accepted tribal distinctions within the Phocinae. In addition, results suggest that Pagophilus should be accepted as a genus within the Phocini. Sequence divergence between Phoca, Pusa, and Halichoerus is minimal, supporting a taxonomic reclassification of the three genera into an emended genus Phoca, without subgeneric distinctions.

Evolution of symbiosis in the Vibrionaceae: a combined approach using molecules and physiology.

The family Vibrionaceae is considered to be one of the most diverse and well-studied groups of bacteria. Here, evolution is assessed within the Vibrionaceae to determine whether multiple origins of eukaryotic associations have occurred within this diverse group of bacteria. Analyses were based on a large molecular dataset, along with a matrix that consisted of 100 biochemical and restriction digest characters. By using direct optimization methods to analyse both datasets individually and in combination, a total-evidence cladogram has been produced, which supports the hypothesis that several important symbionts (both mutualistic and pathogenic) within the Vibrionaceae are not monophyletic. This leads us to consider that symbiosis (and subsequently, associations with Eukarya) has evolved multiple times within the Vibrionaceae lineage.

“Lipotyphlan” phylogeny based on the growth hormone receptor gene: a reanalysis

From an evolutionary perspective, “insectivores” have been one of the most important mammalian groups for over a century. Morphologists have successively pruned flying lemurs, elephant shrews, and tree shrews from Insectivora, but have retained chrysochlorids, tenrecs, erinaceids, soricids, talpids, and solenodontids in crown-group Lipotyphla. With the appearance of large molecular data sets, the monophyly of Lipotyphla has proved untenable. Rather, an emerging consensus is that Lipotyphla is a diphyletic taxon comprised of two monophyletic groups, Afrosoricida and Eulipotyphla. A recent paper by Malia et al. [Mol. Phylogenet. Evol. 24 (2002) 91–101] challenged this view and argued that “While the data [Growth Hormone Receptor] were unable to support the orders Lipotyphla, Eulipotyphla, and Tenrecoidea [= Afrosoricida] this was most likely due to the polyphyly of these groups and not to problems associated with the gene itself such as saturation or highly divergent sequences…” (p. 100). We analyzed Malia et al.’s original GHR data set (at both nuclear and protein level), an expanded GHR data set that included 49 additional sequences, and a concatenated data set that included GHR, BRCA1, vWF, and A2AB for a diverse selection of lipotyphlan taxa. Although protein analyses proved inconclusive, all analyses at the DNA level clearly show that the statement of Malia et al. is erroneous. Indeed, likelihood analyses with GHR and with the concatenated data set provide more support for Eulipotyphla and Afrosoricida than for competing hypotheses. These results also highlight the potential pitfalls of single-gene and parsimony-only analyses.

Indels in protein-coding sequences of Euarchontoglires constrain the rooting of the eutherian tree

Despite the availability of large molecular data sets, the position of the root of the eutherian tree remains a controversial issue. Depending on source data, taxon sampling and analytical approach, the root can be placed at either Afrotheria, Xenarthra, Afrotheria + Xenarthra, or murid rodents. We explored the phylogenetic potential of indels in four nuclear protein-coding genes (SCA1, PRNP, TNFα, and HspB3) with regard to a possible rooting at the murid branch. According to parsimony principles, five indels were interpreted to contradict such a rooting, and one indel to support it. The results illustrate that indels, despite the occurrence of homoplasy, can be convincing sources of independent molecular evidence to distinguish between alternative phylogenetic hypotheses.

Gunnerales are sister to other core eudicots: implications for the evolution of pentamery

Phylogenetic relationships among many lineages of angiosperms have been clarified via the analysis of large molecular data sets. However, with a data set of three genes (18S rDNA, rbcL, and atpB), relationships among lineages of core eudicots (Berberidopsidales, Caryophyllales, Gunnerales, Santalales, Saxifragales, asterids, rosids) remain essentially unresolved. We added 26S rDNA sequences to a three-gene matrix for 201 eudicots (8430 base pair aligned nucleotides per taxon). Parsimony analyses provided moderate (84%) jackknife support for Gunnerales, which comprise the two enigmatic families Gunneraceae and Myrothamnaceae, as sister to all other core eudicots. This position of Gunnerales has important implications for floral evolution. A dimerous or trimerous perianth is frequently encountered in early-diverging eudicots (e.g., Buxaceae, Proteales, Ranunculales, Trochodendraceae), whereas in core eudicots, pentamery predominates. Significantly, dimery is found in Gunneraceae and perhaps Myrothamnaceae (the merosity of the latter has also been interpreted as labile). Parsimony reconstructions of perianth merosity demonstrate lability among early-diverging eudicots and further indicate that a dimerous perianth could be the immediate precursor to the pentamerous condition characteristic of core eudicots. Thus, the developmental canalization that yielded the pentamerous condition of core eudicots occurred after the node leading to Gunnerales.

Phylogenetic relationships of agaric fungi based on nuclear large subunit ribosomal DNA sequences.

Phylogenetic relationships of mushrooms and their relatives within the order Agaricales were addressed by using nuclear large subunit ribosomal DNA sequences. Approximately 900 bases of the 5' end of the nucleus-encoded large subunit RNA gene were sequenced for 154 selected taxa representing most families within the Agaricales. Several phylogenetic methods were used, including weighted and equally weighted parsimony (MP), maximum likelihood (ML), and distance methods (NJ). The starting tree for branch swapping in the ML analyses was the tree with the highest ML score among previously produced MP and NJ trees. A high degree of consensus was observed between phylogenetic estimates obtained through MP and ML. NJ trees differed according to the distance model that was used; however, all NJ trees still supported most of the same terminal groupings as the MP and ML trees did. NJ trees were always significantly suboptimal when evaluated against the best MP and ML trees, by both parsimony and likelihood tests. Our analyses suggest that weighted MP and ML provide the best estimates of Agaricales phylogeny. Similar support was observed between bootstrapping and jackknifing methods for evaluation of tree robustness. Phylogenetic analyses revealed many groups of agaricoid fungi that are supported by moderate to high bootstrap or jackknife values or are consistent with morphology-based classification schemes. Analyses also support separate placement of the boletes and russules, which are basal to the main core group of gilled mushrooms (the Agaricineae of Singer). Examples of monophyletic groups include the families Amanitaceae, Coprinaceae (excluding Coprinus comatus and subfamily Panaeolideae), Agaricaceae (excluding the Cystodermateae), and Strophariaceae pro parte (Stropharia, Pholiota, and Hypholoma); the mycorrhizal species of Tricholoma (including Leucopaxillus, also mycorrhizal); Mycena and Resinomycena; Termitomyces, Podabrella, and Lyophyllum; and Pleurotus with Hohenbuehelia. Several groups revealed by these data to be nonmonophyletic include the families Tricholomataceae, Cortinariaceae, and Hygrophoraceae and the genera Clitocybe, Omphalina, and Marasmius. This study provides a framework for future systematics studies in the Agaricales and suggestions for analyzing large molecular data sets.

Phylogenetic analysis of large molecular data sets

Los adelantos tecnológicos en biología molecular han aumentado en gran medida la velocidad y eficiencia de la secuenciación de ADN, haciendo posible construir relativamente rápido grandes juegos de datos moleculares para la reconstrucción filogenética. A pesar de su potencial para mejorar nuestro entendimiento de la filogenia, estos grandes juegos de datos también proveen muchos retos. En este artículo discutimos varios de estos desafíos, incluyendo 1) el fracaso en la búsqueda del árbol más parsimonioso (el óptimo local) en un lapso de tiempo razonable, 2) la diferencia entre un óptimo local y el óptimo global, y 3) la existencia de clases múltiples (islas) de árboles más parsimoniosos. También discutimos posibles estrategias para aumentar la posibilidad de encontrar el o los árboles más parsimoniosos y presentamos dos ejemplos de nuestro trabajo en la filogenia de las angiospermas. Concluimos con una discusión de dos alternativas para el análisis de los juegos enteros de datos: el "enfoque de representantes" y la "compartamentalización". Sugerimos que debe darse consideración adicional al asunto del análisis de juegos grandes de datos, sean morfológicos o moleculares.

Gene Trees and Species Trees: Molecular Systematics as One-Character Taxonomy

Reconstruction of phylogenies from molecular data has become an important and increasingly common approach in systematics. The product of such studies is a gene tree, hypoth- esizing relationships among genes or genomes. This gene tree may be fundamentally incongruent with the true species phylogeny, due to various biological phenomena such as introgression, lineage sorting, or mistaken orthology. In such circumstances all of the gene tree characters defining the relationships of molecular taxa (haplotypes) may be necessarily correlated, and the gene or genome may behave as a single species tree character. In these circumstances robustness of the gene hypoth- esis is meaningless as a measure of confidence in the species phylogenetic hypothesis. Incongruence between a phylogenetic hypothesis based on numerous, presumably independent, non-molecular characters and a single gene tree should not be assumed to be due to noise in non-molecular data. As with other characters, a character phylogeny, in this case a gene tree, can be tested best by a parsimony analysis in which other characters are included. If independence of molecular characters is assumed, then each is an equivalent phylogenetic hypothesis, as is each non-molecular character, leading to the suggestion that direct combination is appropriate. Swamping becomes an issue when a large molecular data set may be behaving as a single character. To alleviate this problem, a gene tree may be treated as a single multistate character, either ordered or unordered, and included with non-molecular data to obtain a globally parsimonious result. An example is given using published molecular and non-molecular data from the Asteraceae.