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Statistical Analysis of Mouse Gut Microbiota. Alex Tran TJHSST Computer Systems Lab 2009-2010. Abstract.
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Statistical Analysis of Mouse Gut Microbiota Alex Tran TJHSST Computer Systems Lab 2009-2010
Abstract The mouse gut microbiotal community is the population of bacteria, which inhabit the digestive track of a given population of mice. The ability to understand the microbiotal community has implications, which extend beyond mice and into factors of human obesity and the dietary needs of the human body. Computational genomics is an emerging field, which blends both biology and computer science, to analyze genes. This study seeks to utilize several methods emerging within computational genomics to analyze the gut microbiome of mice to observe the effects of varying diets on the gut microbiotal community, as well as create a universal and user friendly tool for researchers to utilize when studying any gut microbiome. The applications of this can extend past studying the gut microbiome, but can also be applied to any taxonomic group being counted for analysis, however several parts of the application are exclusively beneficial to the analysis of gut microbiota specifically those found in mice.
Introduction Genomics Gut Microbiota Mouse Digestive Tract http://esd.lbl.gov/img/HOME/a_gut_feeling.jpg
Background • OB/OB mice • Human Microbiome Project
Washington University Gordon Lab Working with Gut Microbiota in Obese Mice Specifically observing Fecal matter Larger Sample Size Mice last longer Currently pay $1,000 dollars for each batch of tests Comes back in an unreadable format Biologists can't program
Development • Python • Tkinter • I/O intensive
Objectives User Friendliness Efficiency Universal Compatibility Hugenholtz RDP
1st Quarter Progress Very Basic Gui shell in place Ability to read 2 taxonomic trees and strictly formatted files No exception catching ability No user selected taxonomies No clear data analysis possible
Current Status Driver and application style implementation Shell for multiple file loading and comparison User friendly error catch system Reads standard format files (with error detection) Any Taxonomic Tree Ability to specify taxonomy used Shell for detailed analysis implemented