Plot protein: visualization of mutations

Turner, Tychele N.

doi:10.1186/2043-9113-3-14

Cited by 20 publications

(17 citation statements)

References 8 publications

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“…Identifying those that are pathogenic or which contribute to disease remains very challenging. We have previously shown that visualizing the distribution of missense variants in a given protein sequence can be informative in relation to identifying potentially causal variants (24). However, such visualization does not provide quantitative assessment of clustering patterns and it cannot be applied in a high-throughput setting.…”

Section: Discussionmentioning

confidence: 99%

Proteins linked to autosomal dominant and autosomal recessive disorders harbor characteristic rare missense mutation distribution patterns

et al. 2015

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The role of rare missense variants in disease causation remains difficult to interpret. We explore whether the clustering pattern of rare missense variants (MAF < 0.01) in a protein is associated with mode of inheritance. Mutations in genes associated with autosomal dominant (AD) conditions are known to result in either loss or gain of function, whereas mutations in genes associated with autosomal recessive (AR) conditions invariably result in loss-of-function. Loss-of-function mutations tend to be distributed uniformly along protein sequence, whereas gain-of-function mutations tend to localize to key regions. It has not previously been ascertained whether these patterns hold in general for rare missense mutations. We consider the extent to which rare missense variants are located within annotated protein domains and whether they form clusters, using a new unbiased method called CLUstering by Mutation Position. These approaches quantified a significant difference in clustering between AD and AR diseases. Proteins linked to AD diseases exhibited more clustering of rare missense mutations than those linked to AR diseases (Wilcoxon P = 5.7 × 10 −4 , permutation P = 8.4 × 10 −4). Rare missense mutation in proteins linked to either AD or AR diseases was more clustered than controls (1000G) (Wilcoxon P = 2.8 × 10 −15 for AD and P = 4.5 × 10 −4 for AR, permutation P = 3.1 × 10 −12 for AD and P = 0.03 for AR). The differences in clustering patterns persisted even after removal of the most prominent genes. Testing for such non-random patterns may reveal novel aspects of disease etiology in large sample studies.

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Section: Discussionmentioning

confidence: 99%

Proteins linked to autosomal dominant and autosomal recessive disorders harbor characteristic rare missense mutation distribution patterns

et al. 2015

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“…Where applicable, hypothetical proteins were investigated using the conserved domain architecture tool 49 , which was used to meta-analyze the predicted protein domains. These domains, alongside any mutations that were seen to occur during longitudinal carriage, were used as input for plot protein 50 to generate a protein diagram. In silico translations to determine effects of mutation on protein size were examined using ExPASy translate 51 .…”

Section: Methodsmentioning

confidence: 99%

Microevolution of Neisseria lactamica during nasopharyngeal colonisation induced by controlled human infection

et al. 2018

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Neisseria lactamica is a harmless coloniser of the infant respiratory tract, and has a mutually-excluding relationship with the pathogen Neisseria meningitidis. Here we report controlled human infection with genomically-defined N. lactamica and subsequent bacterial microevolution during 26 weeks of colonisation. We find that most mutations that occur during nasopharyngeal carriage are transient indels within repetitive tracts of putative phase-variable loci associated with host-microbe interactions (pgl and lgt) and iron acquisition (fetA promotor and hpuA). Recurrent polymorphisms occurred in genes associated with energy metabolism (nuoN, rssA) and the CRISPR-associated cas1. A gene encoding a large hypothetical protein was often mutated in 27% of the subjects. In volunteers who were naturally co-colonised with meningococci, recombination altered allelic identity in N. lactamica to resemble meningococcal alleles, including loci associated with metabolism, outer membrane proteins and immune response activators. Our results suggest that phase variable genes are often mutated during carriage-associated microevolution.

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“…One example is Plot Protein, an R script for creating detailed protein conservation and mutation plots. Plot Protein can provide many levels of detail and supporting information but requires the user to manually fetch, format, and integrate data from multiple sources [ 7 ]. Tools such as Mutation Mapper at cBioPortal are oriented to presenting population-level statistics and not individual variants, leading to inappropriate diagram layouts.…”

Section: Introductionmentioning

confidence: 99%

Lollipops in the Clinic: Information Dense Mutation Plots for Precision Medicine

2016

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IntroductionConcise visualization is critical to present large amounts of information in a minimal space that can be interpreted quickly. Clinical applications in precision medicine present an important use case due to the time dependent nature of the interpretations, although visualization is increasingly necessary across the life sciences. In this paper we describe the Lollipops software for the presentation of panel or exome sequencing results. Source code and binaries are freely available at https://github.com/pbnjay/lollipops. Although other software and web resources exist to produce lollipop diagrams, these packages are less suited to clinical applications. The demands of precision medicine require the ability to easily fit into a workflow and incorporate external information without manual intervention.ResultsThe Lollipops software provides a simple command line interface that only requires an official gene symbol and mutation list making it easily scriptable. External information is integrated using the publicly available Uniprot and Pfam resources. Heuristics are used to select the most informative components and condense them for a concise plot. The output is a flexible Scalable Vector Graphic (SVG) diagram that can be displayed in a web page or graphic illustration tool.ConclusionThe Lollipops software creates information-dense, publication-quality mutation plots for automated pipelines and high-throughput workflows in precision medicine. The automatic data integration enables clinical data security, and visualization heuristics concisely present knowledge with minimal user configuration.

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Plot protein: visualization of mutations

Cited by 20 publications

References 8 publications

Proteins linked to autosomal dominant and autosomal recessive disorders harbor characteristic rare missense mutation distribution patterns

Proteins linked to autosomal dominant and autosomal recessive disorders harbor characteristic rare missense mutation distribution patterns

Microevolution of Neisseria lactamica during nasopharyngeal colonisation induced by controlled human infection

Lollipops in the Clinic: Information Dense Mutation Plots for Precision Medicine

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