Biology subjects

Murphy, C.

Publications and source records attributed to Murphy, C..

5 recordsLinked to original sources

bioRxiv2018

Phenogenon: Gene to Phenotype Associations for Rare Genetic Diseases

As genome sequencing is increasingly applied to molecular diagnosis of rare Mendelian disorders, large number of patients with diverse phenotypes have their genomic and phenotypic data pooled together to uncover new genotype - phenotype relations. We introduce Phenogenon, a method that combines: the power of Human Phenotype Ontology for describing patient phenotypes, gnomAD for estimating rare variant population frequency, and CADD for variant pathogenicity prediction. By using a divide and conquer approach, we demonstrate here that Phenogenon is able to uncover true gene to phenotype relations, such as \"ABCA4 - Macular dystrophy\" and \"SCN1A - Seizures\". Additionally, it accurately infers mode of inheritance, such as a recessive mode of inheritance in the case of the \"ABCA4 - Macular dystrophy\" relationship and a dominant mode of inheritance with the \"SCN1A - Seizures\" relationship. We also found that CADD has more power to detect early-onset rare genetic diseases than late-onset diseases. In this study, we ran Phenogenon against a diverse cohort of 3288 patients. Among the top 13 gene-phenotype relations, seven were previously known. We also highlight four potentially novel gene - phenotype relations such as \"SIPA1L3 - Abnormal electroretinogram\".

bioinformatics↗

bioRxiv2017

Scaffolding imagination: A role for medial frontal cortex in the expression of off-task thought

We often think about people, places and events that are outside of our immediate environment. Although prior studies have explored how we can reduce the occurrence of these experiences, the neurocognitive process through which they are produced are less understood. The current study builds on developmental and evolutionary evidence that language helps organise and express our thoughts. Behaviorally, we found the occurrence of task unrelated thought (TUT) in easy situations was associated with thinking in words. Using experience sampling data, in combination with online measures of neural function, we established that activity in a region of anterior cingulate cortex / medial-prefrontal cortex (mPFC) tracked with changes in the expression of TUT. This region is at the intersection of two mPFC clusters identified through their association with variation in aspects of spontaneous thought: thinking in words (dorsal) and mental time travel (ventral). Finally, using meta-analytic decoding we confirmed the dorsal/ventral distinction within mPFC corresponding to a functional difference between domains linked to language and meaning and those linked to memory and scene construction. This evidence suggests a role for mPFC in the expression of TUT that may emerge from interactions with distributed neural signals reflecting processes such as language and memory.

animal behavior and cognition↗

bioRxiv2017

Isolated from input: Transmodal cortex in the default mode network supports perceptually-decoupled and conceptually-guided cognition

The default mode network supports a variety of mental operations such as semantic processing, episodic memory retrieval, mental time travel and mind-wandering, yet the commonalities between these functions remains unclear. One possibility is that this system supports cognition that is independent of the immediate environment; alternatively or additionally, it might support higher-order conceptual representations that draw together multiple features. We tested these accounts using a novel paradigm that separately manipulated the availability of perceptual information to guide decision-making and the representational complexity of this information. Using task based imaging we established regions that respond when cognition combines both stimulus independence with multi-modal information. These included left and right angular gyri and the left middle temporal gyrus. Although these sites were within the default mode network, they showed a stronger response to demanding memory judgements than to an easier perceptual task, contrary to the view that they support automatic aspects of cognition. In a subsequent analysis, we showed that these regions were located at the extreme end of a macroscale gradient, which describes gradual transitions from sensorimotor to transmodal cortex. This shift in the focus of neural activity towards transmodal, default mode, regions might reflect a process of isolation from specific sensory inputs that enables conceptually rich cognitive states to be generated in the absence of input.\n\nHighlights O_LIBrain regions supporting meaning overlap with stimulus independence.\nC_LIO_LIBilateral angular gyri and left MTG respond strongly to both features of cognition.\nC_LIO_LIThese patterns reflect a shift in activity towards regions of transmodal cortex.\nC_LIO_LIComplex memory representations may emerge in cortical areas distant from input.\nC_LI

neuroscience↗

bioRxiv2016

Phenopolis: an open platform for harmonization and analysis of sequencing and phenotype data

SummaryPhenopolis is an open-source web server which provides an intuitive interface to genetic and phenotypic databases. It integrates analysis tools which include variant filtering and gene prioritisation based on phenotype. The Phenopolis platform will accelerate clinical diagnosis, gene discovery and encourage wider adoption of the Human Phenotype Ontology in the study of rare disease.\n\nAvailability and ImplementationA demo of the website is available at http://phenopolis.github.io (username: demo, password: demo123). If you wish to install a local copy, souce code and installation instruction are available at https://github.com/pontikos/phenopolis. The software is implemented using Python, MongoDB, HTML/Javascript and various bash shell scripts.\n\nContactn.pontikos@ucl.ac.uk\n\nSupplementary informationhttp://phenopolis.github.io

bioinformatics↗

bioRxiv2016

AGFusion: annotate and visualize gene fusions

SummaryThe discovery of novel gene fusions in tumor samples has rapidly accelerated with the rise of next-generation sequencing. A growing number of tools enable discovery of gene fusions from RNA-seq data. However it is likely that not all gene fusions are driving tumors. Assessing the potential functional consequences of a fusion is critical to understand their driver role. It is also challenging as gene fusions are described by chromosomal breakpoint coordinates that need to be translated into an actual amino acid fusion sequence and predicted domain architecture of the fusion proteins. Currently there are no easy-to-use tools that can automatically reconstruct and visualize fusion proteins from genomic breakpoints. To facilitate the functional interpretation of gene fusions, we developed AGFusion, available as an online web tool that can be readily used by non-computational researchers as well as a python package that can be built into computational pipelines. With minimal input from the user, AGFusion predicts the cDNA, CDS, and protein sequences of all gene fusion products based on all combinations of gene isoforms. For protein coding fusions, AGFusion can annotate and visualize the protein domain architecture. AGFusion currently supports Homo sapiens (genome builds GRCh37 and GRCh38) and Mus musculus (genome build GRCm38) and new genomes can easily be added.\n\nAvailabilityAGFusion python package is freely available at https://github.com/murphycj/AGFusion under the MIT license. The AGFusion web app is available at http://agfusion.info

bioinformatics↗