Week 4

Caitlin E -

Hi Everyone!

Although I have some updates on my project, my progress is a bit slower than I expected. My work remains online, and my main priority for this week has been trying to interpret the findings presented by Clinprior and MARRVEL. Similar to last week, I have had some difficulties interpreting results. 

Data Set and Analysis Tools 

One of the main data sets that the Schrauwen lab is analyzing at the moment contains information related to the genetic background of rare neurological diseases in a sample of Finnish families. The set includes information such as the phenotype descriptions of affected subjects, sex of affected subjects, phenotype of affected subjects’ parents and siblings, and genetic testing methods used on the samples; these methods included exome sequencing, karyotype tests, microarray analysis, and optical genome mapping. The shared symptom among all the affected individuals in the data set is severe seizures.

Out of the fifty-five samples in the data set, two failed to run through ClinPrior. AI MARRVEL has had less complications analyzing the data. Aside from these two programs, the lab has added Exomiser to its array of analysis tools. Exomiser is a powerful variant prioritization tool used in genomics research to identify disease-causing genetic variants. It analyzes exome or genome sequencing data by processing phenotype information, gene function, and conservation scores. Exomiser helps researchers pinpoint pathogenic mutations efficiently, aiding in the diagnosis of rare genetic diseases. 

Next Steps

My plan for now is to compare the results from ClinPrior, MARRVEL, and Exomiser in order to see which model is most effective. I anticipate seeing some differences between the results that each software yields. 

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Comments:

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    camille_bennett
    Hi Caitlin, it sounds like you are doing some great work, even in the online format. Is there a reason why you are using the specific data set that you are using?
    caitlin_e
    Hi Ms. Bennett. The reason why I am using this specific data set is because it is a recent data set that observes a niche population. Dr. Schrauwen has worked with this data set in the past while investigating autosomal recessive intellectual disabilities in the founder population of Finland. Reducing the sample size to a specific demographic can be beneficial in genetic research, as certain pathogenic variants can be easier to observe and identify in more genetically similar environments. In addition, the demographic similarities can make environmental factors more apparent as well.

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