BME100 s2016:Group3 W1030AM L6

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BME 100 Spring 2016 Home
Lab Write-Up 1 | Lab Write-Up 2 | Lab Write-Up 3
Lab Write-Up 4 | Lab Write-Up 5 | Lab Write-Up 6
Course Logistics For Instructors
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Name: Mark Weser
Name: Mark Weser
Name: Makarios Begay
Name: Makarios Begay
Name: Alexis Nelson
Name: Alexis Nelson
Name: Kori Staples
Name: Kori Staples
Name: Morgan Murray
Name: Morgan Murray
Name: Ryan Wood
Name: Ryan Wood


Bayesian Statistics

Overview of the Original Diagnosis System
In order to test the patients for the disease-associated SNP, we had 16 teams of 6 students test 32 patients' DNA using a PCR reaction to see if they had the SNP. Each team was assigned two patients, and each patient had three replicates to prevent error. Another preventative measure was taken and each team used two PCR controls, negative and positive. The tests were conducted using careful measurements with micro pipetting solutions made of buffer, PCR reaction, and SYBR Green I solution. The solutions were analyzed in the form of three separate drops per patient replicate. Those drops were analyzed in ImageJ. After all the results were recorded, the class's final data was compiled into one spreadsheet so that all of the results could be analyzed using Bayesian Statistics. The class recorded 12 positive PCR conclusions, 18 negative PCR conclusions, and 2 inconclusive PCR conclusions. Some challenges we encountered mostly involved gathering the images for ImageJ. Because of this, the images might not have been as clear as they could possibly be, and therefore there could have been some error in our ImageJ calculations.

What Bayes Statistics Imply about This Diagnostic Approach

Calculation 1

Calculation 2

Calculation 3

Calculation 4

Calculation 1 asked us to find the probability that the patient will have a positive final test conclusion given a positive PCR reaction. Our Bayes value for calculation 1 was quite high. Calculation 2 asked us to find the probability of a negative final test conclusion given a negative diagnosis. The Bayes value for that calculation was equally as high as the value for calculation 1. This indicates that the individual PCR replicates are reliable for concluding whether or not the person has the disease SNP.

Calculation 3 asked us to find the probability that the patient will develop the disease given a positive final test conclusion. Our Bayes value came out to be low. Calculation 4 asks us to find the probability that the patient will not develop the disease given a negative final test conclusion. Our Bayes value came out extremely high, more than 100%. These two calculations imply that a positive PCR result was not reliable, while a negative PCR result is quite reliable in predicting the development of the disease.

Error coming from the images that were taken could have a negative impact on the Bayes values. If the images weren't clear enough, the ImageJ calculations could have been slightly off. Human error can also come from error in micro pipetting measurements, air bubbles in the tip could throw the measurements off.

Intro to Computer-Aided Design

TinkerCAD is an online design software that is user friendly and simple to use. Two members of our group were able to completely understand the program in less than thirty minutes. TinkercAD is most definitely easier to use than Solidworks. The controls are smoother and it is easier to navigate through the program. While in Solidworks, there are many different options and toolbars making it time consuming to learn and understand. Our group was able to jump right in and start designing after watching a few short video tutorials.

Our Design

Our design differs from the original openPCR design in a few ways. One of the biggest differences between the designs is that on the inside, there is a built in mount for a camera. One of the biggest issues we faced was getting our camera to stand up straight and keep it at the same distance each time. So, we definitely wanted to implement this fix into our design. We also altered the design so that it contained less openings and let in less light. We believed it was important to eliminate as much light exposure as possible. Overall, much of the design is similar, but there are a few key differences that improve and set our design apart.

Feature 1: Consumables

Our Consumables kit will come with a pack of 15-20 tubes, and tips for the micropipettor. These will be packaged with plastic and will be shipped inside a box. The initial package will also come with a package of primer mix and a separate package of PCR mix. We will also include a pack of glass viewing slides if those who are buying are product want to do many trials in their usage. We will place a "Fragile: Handle With Care" label on the outside of the box, because we do not want the bag of mix to be punctured or the package of glass slides to be shattered. We will also sell additional packages tubes and tips that can be bought in bulk if our PCR set is going to be used over an extended amount of experiments. We can also offer large containers of PCR primer and mix in a separate package.

Feature 2: Hardware - PCR Machine & Fluorimeter

There aren't many changes that we needed to make from the original PCR machine design, it is a really refined machine and does its job very well. The only things that we could improve on the device is increase the amount of slides it could hold by in creasing the length and width of the inside of the device. Also, we would add a a viewing hood and a camera stand with the device as it was very difficult to keep the inside of the device dark enough to view the results of the PCR reaction, and it was difficult to focus and take picture with the camera without a solid stand to rest on.

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