Visualizing incompatibilities in phylogenetic trees using consensus outlines.

Phylogenetic analysis frequently leads to the creation of many phylogenetic trees, either from using multiple genes or methods, or through bootstrapping or Bayesian analysis. A consensus tree is often used to summarize what the trees have in common. Consensus networks were introduced to also allow the visualization of the main incompatibilities among the trees. However, in practice, such networks often contain a large number of nodes and edges, and can be non-planar, making them difficult to interpret. Here, we introduce the new concept of a phylogenetic consensus outline, which provides a planar visualization of incompatibilities in the input trees, without the complexities of a consensus network. Furthermore, we present an effective algorithm for its computation. We demonstrate its usage and explore how it compares to other methods on a Bayesian phylogenetic analysis of languages using data from a published database and on multiple gene trees from a published study on water lilies.

Microbial Phylogenetic Context Using Phylogenetic Outlines.

Microbial studies typically involve the sequencing and assembly of draft genomes for individual microbes or whole microbiomes. Given a draft genome, one first task is to determine its phylogenetic context, that is, to place it relative to the set of related reference genomes. We provide a new interactive graphical tool that addresses this task using Mash sketches to compare against all bacterial and archaeal representative genomes in the Genome Taxonomy Database taxonomy, all within the framework of SplitsTree5. The phylogenetic context of the query sequences is then displayed as a phylogenetic outline, a new type of phylogenetic network that is more general than a phylogenetic tree, but significantly less complex than other types of phylogenetic networks. We propose to use such networks, rather than trees, to represent phylogenetic context, because they can express uncertainty in the placement of taxa, whereas a tree must always commit to a specific branching pattern. We illustrate the new method using a number of draft genomes of different assembly quality.

Assessment of the quality of life of mothers of children with cerebral palsy (primary caregivers).

OBJECTIVES: To evaluate the quality of life and psychological status in mothers of children with cerebral palsy (MCCPs) and to assess their relation with regard to the degree of their child's disability. DESIGN: Face-to-face interviews with MCCPs have been performed. A prospective, case control study. SETTING: Physical therapy and rehabilitation training and research hospital. Subjects. 46 MCCPs and the mothers of 46 healthy children. MAIN OUTCOME MEASURE: Notthingam Health Profile-1, Beck Depression Inventory (BDI), and Beck Anxiety Inventory (BAI) scores in MCCPs and the mothers of healthy children. Gross Motor Function Classification System (GMFCS) was used for the children with cerebral palsy. RESULTS: A significantly worsened (P = 0.001) quality of life was observed in MCCPs compared to the mothers of healthy children. BDI scores of the MCCPs were significantly higher than the mothers in the control group (P = 0.000). There were no significant differences in BAI scores between MCCPs and control mothers (P > 0.05). A positive correlation between the quality of life and BDI scores was noted in MCCPs (P = 0.000, r = 0.57), and no correlation was detected between the quality of life in MCCPs and the GMFCS levels of children with cerebral palsy (r = 0.012, P = 0.95). CONCLUSION: The quality of life in MCCPs is significantly lower than that of control mothers. Also, although the BAI scores were not significantly different between the groups, the BDI scores were poorer in MCCPs compared to those the control group.

Quality of life for patients poststroke and the factors affecting it.

OBJECTIVE: We sought to assess quality of life (QOL) and the factors affecting QOL for patients with stroke. METHODS: This study was designed as a controlled prospective study. The study group consisted of 88 patients who had experienced a stroke and the control group consisted of 40 healthy participants. The two groups were equivalent in terms of age and sex. QOL was measured by the Nottingham Health Profile (NHP). Functional independence was used to measure the functional states; the Ashworth scale (5, stage range 0-4) was used to measure spasticity levels; and the Mini Mental State Evaluation test, combined with the results of the functional independence cognitive subscale, was used to measure the cognitive state of patients. RESULTS: QOL of the patient group, as measured with the NHP, was significantly lower than in the control group (P < .0001). Total scores of the NHP were negatively correlated with functional state scores (r = -.30, P = .02), cognitive state scores (r = -0.40, P = .01), and upper extremity motor state scores (r = -0.30, P = .02). CONCLUSIONS: Stroke was found to disrupt patients' QOL. Patients' QOL was significantly associated with functional state, upper extreme motor state, poststroke depressions, and educational levels.