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Research

Childhood dementias are a group of rare and ultra-rare paediatric conditions clinically characterised by enduring global decline in central nervous system function, associated with a progressive loss of developmentally acquired skills, quality of life and shortened life expectancy. Traditional research, service development and advocacy efforts have been fragmented due to a focus on individual disorders, or groups classified by specific mechanisms or molecular pathogenesis.

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Clinical deep phenotyping and phenotype annotation play a critical role in both the diagnosis of patients with rare disorders as well as in building computationally-tractable knowledge in the rare disorders field.

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Here we focus on the problem of prioritising variants with respect to the observed disease phenotype

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People living with rare diseases (PLWRD) still face huge unmet needs, in part due to the fact that care systems are not sufficiently aligned with their needs and healthcare workforce (HWF) along their care pathways lacks competencies to efficiently tackle rare disease-specific challenges. Level of rare disease knowledge and awareness among the current and future HWF is insufficient.

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We hypothesised that the performance of variant prioriisation tools may vary by disease phenotype.

People

Feilman Fellow; Head, Precision Health Research and Head, Computational Biology

Research

An estimated 3.5%-5.9% of the global population live with rare diseases, and approximately 80% of these diseases have a genetic cause. Rare genetic diseases are difficult to diagnose, with some affected individuals experiencing diagnostic delays of 5-30 years. Next-generation sequencing has improved clinical diagnostic rates to 33%-48%. In a majority of cases, novel variants potentially causing the disease are discovered. 

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SAMStat is an efficient program to extract quality control metrics from fastq and SAM/BAM files. A distinguishing feature is that it displays sequence composition, base quality composition and mapping error profiles split by mapping quality. This allows users to rapidly identify reasons for poor mapping including the presence of untrimmed adapters or poor sequencing quality at individual read positions.

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Bubble CPAP may be used in infants with suspected or confirmed COVID-19. Electrostatic filters may reduce cross infection. This study aims to determine if including a filter in the bubble CPAP circuit impacts stability of pressure delivery. A new electrostatic filter was placed before (pre) or after (post) the bubble CPAP generator, or with no filter (control) in an in vitro study. Pressure was recorded at the nasal interface for 18 h (6 L/min; 7 cm H2O) on 3 occasions for each configuration. Filter failure was defined as pressure >9 cm H2O for 60 continuous minutes. The filter was weighed before and after each experiment.

Research

This protocol describes bilateral murine tumor models that display a symmetrical yet dichotomous response to immune checkpoint blockade