Dataset Information

PSCAN: Spatial scan tests guided by protein structures improve complex disease gene discovery and signal variant detection.

ABSTRACT: Germline disease-causing variants are generally more spatially clustered in protein 3-dimensional structures than benign variants. Motivated by this tendency, we develop a fast and powerful protein-structure-based scan (PSCAN) approach for evaluating gene-level associations with complex disease and detecting signal variants. We validate PSCAN's performance on synthetic data and two real data sets for lipid traits and Alzheimer's disease. Our results demonstrate that PSCAN performs competitively with existing gene-level tests while increasing power and identifying more specific signal variant sets. Furthermore, PSCAN enables generation of hypotheses about the molecular basis for the associations in the context of protein structures and functional domains.

SUBMITTER: Tang ZZ

PROVIDER: S-EPMC7448521 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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PSCAN: Spatial scan tests guided by protein structures improve complex disease gene discovery and signal variant detection.

Tang Zheng-Zheng ZZ Sliwoski Gregory R GR Chen Guanhua G Jin Bowen B Bush William S WS Li Bingshan B Capra John A JA

Genome biology 20200826 1

Germline disease-causing variants are generally more spatially clustered in protein 3-dimensional structures than benign variants. Motivated by this tendency, we develop a fast and powerful protein-structure-based scan (PSCAN) approach for evaluating gene-level associations with complex disease and detecting signal variants. We validate PSCAN's performance on synthetic data and two real data sets for lipid traits and Alzheimer's disease. Our results demonstrate that PSCAN performs competitively ...[more]

PMID: 32847609

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Project description:In forest clearings of the Malaysian rainforest, chirping and trilling Mecopoda species often live in sympatry. We investigated whether a phenomenon known as stochastic resonance (SR) improved the ability of individuals to detect a low-frequent signal component typical of chirps when members of the heterospecific trilling species were simultaneously active. This phenomenon may explain the fact that the chirping species upholds entrainment to the conspecific song in the presence of the trill. Therefore, we evaluated the response probability of an ascending auditory neuron (TN-1) in individuals of the chirping Mecopoda species to triple-pulsed 2, 8 and 20 kHz signals that were broadcast 1 dB below the hearing threshold while increasing the intensity of either white noise or a typical triller song. Our results demonstrate the existence of SR over a rather broad range of signal-to-noise ratios (SNRs) of input signals when periodic 2 kHz and 20 kHz signals were presented at the same time as white noise. Using the chirp-specific 2 kHz signal as a stimulus, the maximum TN-1 response probability frequently exceeded the 50% threshold if the trill was broadcast simultaneously. Playback of an 8 kHz signal, a common frequency band component of the trill, yielded a similar result. Nevertheless, using the trill as a masker, the signal-related TN-1 spiking probability was rather variable. The variability on an individual level resulted from correlations between the phase relationship of the signal and syllables of the trill. For the first time, these results demonstrate the existence of SR in acoustically-communicating insects and suggest that the calling song of heterospecifics may facilitate the detection of a subthreshold signal component in certain situations. The results of the simulation of sound propagation in a computer model suggest a wide range of sender-receiver distances in which the triller can help to improve the detection of subthreshold signals in the chirping species.

Dataset Information

PSCAN: Spatial scan tests guided by protein structures improve complex disease gene discovery and signal variant detection.

Publications

PSCAN: Spatial scan tests guided by protein structures improve complex disease gene discovery and signal variant detection.

Similar Datasets

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