Advisor Information
Kate Cooper
Location
MBSC 201
Presentation Type
Poster
Start Date
6-3-2020 2:00 PM
End Date
6-3-2020 3:15 PM
Abstract
In this project, I compared the tools used at each step of the high-throughput sequencing pipeline used to detect single-nucleotide polymorphisms (SNP’s). There are 11 sequences I utilized from my mentor, Dr. Kate Cooper, on this project (pertaining to Staphylococcus aureus) and I used those in the sequencing pipeline. I evaluated different tools by using different ones at different steps of the pipeline. By doing this, I was able to see how close or far the outputs are by only changing one factor. It is also important to note that, with each online tool comes its own sets of parameters. I kept track of the parameters I am using and did everything I could to keep them consistent between tools.
In the beginning of this project, I gathered data by running the same sequence through a different series of tools. Again, I ran the same data through several times while only changing one tool at one step. The next time through, I changed a tool at a different step while keeping the rest of the tools consistent. This provided plenty of data since there are many combinations of tools for how many steps there are. After gathering enough data, I analyzed the results and how significantly similar or different the results are. Finally, after analyzing the results, I looked into the specific algorithms of each tool to determine why the results are different and attempted to construct the best possible pipeline to obtain the best set of results.
High-Throughput Sequencing Pipeline Tool Analysis - Staphylococcus Aureus
MBSC 201
In this project, I compared the tools used at each step of the high-throughput sequencing pipeline used to detect single-nucleotide polymorphisms (SNP’s). There are 11 sequences I utilized from my mentor, Dr. Kate Cooper, on this project (pertaining to Staphylococcus aureus) and I used those in the sequencing pipeline. I evaluated different tools by using different ones at different steps of the pipeline. By doing this, I was able to see how close or far the outputs are by only changing one factor. It is also important to note that, with each online tool comes its own sets of parameters. I kept track of the parameters I am using and did everything I could to keep them consistent between tools.
In the beginning of this project, I gathered data by running the same sequence through a different series of tools. Again, I ran the same data through several times while only changing one tool at one step. The next time through, I changed a tool at a different step while keeping the rest of the tools consistent. This provided plenty of data since there are many combinations of tools for how many steps there are. After gathering enough data, I analyzed the results and how significantly similar or different the results are. Finally, after analyzing the results, I looked into the specific algorithms of each tool to determine why the results are different and attempted to construct the best possible pipeline to obtain the best set of results.