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An expanded phenotype centric benchmark of variant prioritisation tools

Identifying the causal variant for diagnosis of genetic diseases is challenging when using next-generation sequencing approaches and variant prioritization tools can assist in this task. These tools provide in silico predictions of variant pathogenicity, however they are agnostic to the disease under study. We previously performed a disease-specific benchmark of 24 such tools to assess how they perform in different disease contexts.

SAMStat 2: quality control for next generation sequencing data

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.

What’s in a name?

In WA, 60,000 kids live with a rare disease, and of those about half do not have a diagnosis. At The Kids, researchers are leading the charge in developing a method to identify genetic variations, so that kids like Charlotte can get answers.

Temporally restricted activation of IFNβ signaling determines response to immune checkpoint therapy

The biological determinants of the response to immune checkpoint blockade (ICB) in cancer remain incompletely understood. Little is known about dynamic biological events that underpin therapeutic efficacy due to the inability to frequently sample tumours in patients.

Innovation in Informatics to Improve Clinical Care and Drug Accessibility for Rare Diseases in China

In China, there are severe unmet medical needs of people living with rare diseases. Relatedly, there is a dearth of data to inform rare diseases policy. This is historically partially due to the lack of informatics infrastructure, including standards and terminology, data sharing mechanisms and network; and concerns over patient privacy protection.

Translational Intelligence

The aim of the Translational Intelligence team is to understand how individual bases in our genome predispose, alter and interact in normal and disease contexts.