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Personalised analytics for rare disease diagnosticsHere we focus on the problem of prioritising variants with respect to the observed disease phenotype
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CAGE-defined promoter regions of the genes implicated in Rett SyndromeA comprehensive picture of the regulatory regions of the three genes involved in Rett Syndrome
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Promoter-level expression clustering identifies time development of transcriptional regulatory cascades initiated by ERBB receptors in breast cancer cellsThe analysis of CAGE (Cap Analysis of Gene Expression) time-courses has been applied to examine the dynamics of enhancer and promoter by sequentially...
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Study Protocol for a Stepped-Wedge Cluster (Nested) Randomized Controlled Trial of Antenatal Colostrum Expression (ACE) Instruction in First-Time Mothers: The ACE StudyAlthough many mothers initiate breastfeeding, supplementation with human-milk substitutes (formula) during the birth hospitalization is common and has been associated with early breastfeeding cessation. Colostrum hand expressed in the last few weeks before birth, known as antenatal colostrum expression (ACE), can be used instead of human-milk substitutes. However, evidence is lacking on the efficacy of ACE on breastfeeding outcomes and in non-diabetic mothers.
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An evaluation of GPT models for phenotype concept recognitionClinical 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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Pushing the boundaries of rare disease diagnostics with the help of the first Undiagnosed HackathonTimo Lassmann BSc (Hons) MSc PhD Feilman Fellow; Head, Precision Health Research and Head, Computational Biology timo.lassmann@thekids.org.au
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Timo LassmannFeilman Fellow; Head, Precision Health Research and Head, Computational Biology
Research
CRISPR-Cas9-generated PTCHD1 2489T>G stem cells recapitulate patient phenotype when undergoing neural inductionAn 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 2: quality control for next generation sequencing dataSAMStat 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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TagDust2: A generic method to extract reads from sequencing data.Arguably the most basic step in the analysis of next generation sequencing data (NGS) involves the extraction of mappable reads from the raw reads...