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Your Poster Title Here Your name here, and names of others Place the name of your institution here

Your Poster Title Here Your name here, and names of others Place the name of your institution here. Analysis of Protein from the Thousand Genome Project. Kaitlin Lisle, Kymberleigh Pagel, Alex Wu. Abstract. Methods. Methods. Results. Sample Data.

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  1. Your Poster Title Here Your name here, and names of others Place the name of your institution here Analysis of Protein from the Thousand Genome Project Kaitlin Lisle, Kymberleigh Pagel, Alex Wu Abstract Methods Methods Results Sample Data Our goal was to identify differences in genomes at the protein level between human populations. We obtained data from the Thousand Genomes Project and used multiple instances of a virtual machine to spread our work around and reduce runtime. Our main findings indicated that there is a significant difference in the percentage of functional mutations in exon variances between the Japanese and European samples. • Process • Identify dataset to use • Find program that will output the consequences of genetic variations • Take raw data from 1000 Genomes Project and convert to usable format • Set up virtual machine on Futuregrid project • Run data through numerous instances of our virtual machine • Analyze output from the program to make it meaningful • Draw conclusions from analysis • Computing • Provided by Futuregrid project • Ran virtual machine instances • Set up in parameters ideal for our program • Distributed workload through numerous nodes Student’s T-Test, p = 3.08848x10^-9 The small p value indicates that there is a significant statistical difference in protein functional mutation rates between Europeans and Japanese. Exon data chosen, which represents the coding region of proteins. Sample Input:Chromosome Start location End Location Change Strand Sample Output: Conclusions There is a significant difference in the percentage of functional mutations in exon variances between the Japanese and European samples .Proposed reasons: 1. Less migration 2. Stronger selection 3. Mutations not fixed yet in the population Objectives References References Evaluate genomic data, using tools from both bioinformatics and cyberinfrastructure, to determine if populations have different levels of functional protein mutations. http://www.1000genomes.org http://www.futuregrid.org

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