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Exploring Microarray Data Patterns for Genetic Disorder Detection

Analyzing microarray data for chromosome 17 markers to identify statistically significant differences among young patients, aiding in genetic disorder diagnosis.

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Exploring Microarray Data Patterns for Genetic Disorder Detection

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  1. Microarray Graph Uh Oh! Nothing stands out! 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 23 18 20 17 21 19 22 Chromosome Number This is a little easier to look at! Tall spikes mean that there is a lot in common at that point…

  2. Hmm…. Our Data.. Let’s look closely… Can we see if there is a difference among our young patients that is statistically unlikely to happen in the normal population? We can! It’s a Chi-Square statistics test and it allows us to look at our data in a slightly different way…

  3. Chi-Squared Microarray Data What’s this? A big spike at chromosome 17 says something is wrong here! The patients are different from the rest of the population in a way that is statistically significant! 23 21 18 19 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 22 20 17 Chromosome Number

  4. Let’s go back to OMIM… http://www.ncbi.nlm.nih.gov/sites/entrez?db=omim Search terms… macrocephaly AND polyhydramnios AND seizures Looking at our 8 results… which ones have gene problems at chromosome 17…

  5. OMIM SAYS… • POLYHYDRAMNIOS, MEGALENCEPHALY, AND SYMPTOMATIC EPILEPSY; PMSEGene map locus 17q23.3 • It’s our only result on chromosome 17, the area the patients all have a common difference… • So, what IS this poly-whatever? • Let us read….

  6. OMIM Sound about right? Good. We have a diagnosis. Pretzel Syndrome. But that is only ONE GENE! How is this possible?

  7. Diagnosis … Is not easy! Take into account how ALL the systems react and interact. “One goes out, they ALL go out!”

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