ArticleHuman mutation2019
Assessment of methods for predicting the effects of PTEN and TPMT protein variants.
Article in Human mutation, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed.
- Classification models distinguish functional and trafficking effects of KCNQ1 variants to enhance variant interpretation.bioRxiv : the preprint server for biology · 2025Article
- Gene-based calibration of high-throughput functional assays for clinical variant classification.bioRxiv : the preprint server for biology · 2025Article
- Variant effect predictor correlation with functional assays is reflective of clinical classification performance.Genome biology · 2025Article
- Variant Effect Prediction in the Age of Machine Learning.Cold Spring Harbor perspectives in biology · 2024Review
- CAGI, the Critical Assessment of Genome Interpretation, establishes progress and prospects for computational genetic variant interpretation methods.Genome biology · 2024Article
- Comprehensive characterization of PTEN mutational profile in a series of 34,129 colorectal cancers.Nature communications · 2022Article
- Decoding the effects of synonymous variants.Nucleic acids research · 2021Article
- Classification of MSH6 Variants of Uncertain Significance Using Functional Assays.International journal of molecular sciences · 2021Review
- Rhapsody: predicting the pathogenicity of human missense variants.Bioinformatics (Oxford, England) · 2020Article
- Variant effect predictions capture some aspects of deep mutational scanning experiments.BMC bioinformatics · 2020Article
- funtrp: identifying protein positions for variation driven functional tuning.Nucleic acids research · 2019Article
- Reports from the fifth edition of CAGI: The Critical Assessment of Genome Interpretation.Human mutation · 2019Article
- CAGI5: Objective performance assessments of predictions based on the Evolutionary Action equation.Human mutation · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors.
Funding
Abstract
Thermodynamic stability is a fundamental property shared by all proteins. Changes in stability due to mutation are a widespread molecular mechanism in genetic diseases. Methods for the prediction of mutation-induced stability change have typically been developed and evaluated on incomplete and/or biased data sets. As part of the Critical Assessment of Genome Interpretation, we explored the utility of high-throughput variant stability profiling (VSP) assay data as an alternative for the assessment of computational methods and evaluated state-of-the-art predictors against over 7,000 nonsynonymous variants from two proteins. We found that predictions were modestly correlated with actual experimental values. Predictors fared better when evaluated as classifiers of extreme stability effects. While different methods emerging as top performers depending on the metric, it is nontrivial to draw conclusions on their adoption or improvement. Our analyses revealed that only 16% of all variants in VSP assays could be confidently defined as stability-affecting. Furthermore, it is unclear as to what extent VSP abundance scores were reasonable proxies for the stability-related quantities that participating methods were designed to predict. Overall, our observations underscore the need for clearly defined objectives when developing and using both computational and experimental methods in the context of measuring variant impact.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.