RS number filter

Users can now search by rsNumbers in our search fitlers

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Measuring Variant Conservation with GERP Score and Siphy

The more annotations, the better! We've recently added 2 new annotations to assist with variant prioritisation as a measure of variant conservation and these are GERP scores and Siphy. GERP stands for Genomic Evolutionary Rate Profiling. Conceptually, GERP is a method for the identification of slowly evolving regions in a multiple sequence alignment, defined as ‘constrained elements’. "Constrained elements are identified by comparing the observed to the expected rates of evolution for each window, and defining all those regions whose collective observed rates of evolution are significantly lower than would be expected under a null model." More simply, it is a score used to calculate the conservation of each nucleotide in multi-species alignment with ranges from -12.3 to 6.17, with 6.17 being the most conserved. Positive scores (observed fewer than expected) indicate that a site is under evolutionary constraint. Negative scores may be weak evidence of accelerated rates of...
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Exomiser analysis available

What is Exomiser? Taken from the website: "The Exomiser is a tool that finds potential disease-causing variants from whole-exome/genome data. Starting from a VCF file and a set of phenotypes encoded using the Human Phenotype Ontology (HPO) it will annotate, filter and prioritise likely causative variants. The program does this based on user-defined criteria such as a variant's predicted pathogenicity, frequency of occurrence in a population and also how closely the given phenotype matches the known phenotype of diseased genes from human and model organism data. " Our tests indicate that Exomiser is able to rank the correct gene, In the top spot #1, 52% of the time. In the top 5, 78% of the time. In the top 10, 91% of the time. How to use? Download the attachment, Unzip/decompress the attachment, Open the file ending with HTML or TSV, The genes are listed from highest ranking downwards. Currently we use some default settings in exomiser, but it can be re-analyz...
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Health reports: GWAS

In addition to Clinvar and Snpedia, we've recently added GWAS Catalog to the health reports based on the the rsNumbers for a patient. GWAS is particularly useful in a research context by comparing variant frequencies in the affected population against a control (healthy) population using statistical analysis to establish a hypothetical link between variants and disease traits. In the health report under GWAS, we've added the following columns: disease traits, studies, risk allele, initial sample size, replication sample size, p-value and risk allele frequency. In GWAS it has been shown that false positives are not uncommon (false association between variant and disease) due to uncontrolled biases and so it's important to take into consideration whether any replicate studies were done to give more confidence to the hypothesized association.
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