BME100 s2017:Group5 W1030AM L6

BME 100 Spring 2017	Home People 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 Photos Wiki Editing Help
OUR COMPANY Name: Esther Sim Name: Marci Bandala Name: Emina Causevic Name: Neil Collins Name: Chase Frailey Name: Cooper Bertke FlexiPCR LAB 6 WRITE-UP Bayesian Statistics Overview of the Original Diagnosis System In BME 100, 17 teams of 6 students diagnosed 34 patients total for the disease-associate SNP (rs121908757), with our group diagnosing the patients with the ID numbers 45783 and 21721. The SNP in particular that we analyzed is linked with cystic fibrosis. For the division of labor within our individual group, two members were in charge of working with the drop fluorimeter, three members were in charge of working with Image J, and one member was in charge of working on the gel electrophoresis. With each patient, multiple trials were conducted to ensure a reduction in error. Because more trials yield more reliable results, three replicates for each sample were tested, labeled as G5 1-1, 1-2, and 1-3 for the first patient and G5 2-1, 2-2, and 2-3 for the second patient. This allows for any anomalies in one of the results to be backed up by additional trials to prevent any false positives or negatives. In addition to this, a positive and negative PCR control were also tested to compare the results of our samples and to ensure a more accurate analysis of the sample results. Our group also made sure that multiple team members were assigned to each task to make sure that there were multiple people looking over the protocol and experimentation for the PCR portion of the lab. For Image J calibration, multiple team members made sure to evaluate images to make sure that there were consistently clear results. In addition, the images of the samples were compared to the positive and negative controls and calibration curves were used to evaluate the results and to ensure a reduction in error. There were also three images of the drops that were taken so that there were several possibilities for analysis. This ensured that if one image was blurry or insufficient, two other images were available for analysis for each sample. Overall, the class yielded relatively successful results, as there was only one inconclusive result out of fourteen. This data can be seen below. Ultimately, there were only some minor challenges that we faced that could have possibly affected our data. The main issue we had was with the fluorimeter, as we had some difficulty in adjusting it to the phone height. However, this was only a minor issue, and most likely did not affect the results too significantly. What Bayes Statistics Imply about This Diagnostic Approach While calculation 1 shows a moderate reliability of individual replicates concluding whether or not the patient has the disease SNP, calculation 2 demonstrates a very high accuracy in individual PCR tubes concluding that an SNP is non-diseased. Calculation one shows a 50-70% accuracy in properly concluding diseased SNPs. On the other hand, the second calculations show a 90-100% accuracy rate when concluding a negative result, meaning that false positives will be much more likely than false negatives in this case, based on single PCR tubes. Calculation 1 demonstrates the sensitivity of the system regarding its ability to detect the disease SNP, while calculation 2 demonstrates the system's specificity. Calculation 3 demonstrates a probability of about 2/3 in predicting that someone will develop the disease over time. Alternatively, calculation 4 shows that an individual PCR tube has a 90-100% chance of correctly predicting that the patient will not develop the disease. Calculation 3 demonstrates the sensitivity of the system regarding its ability to conclude the diseases development P, while calculation 4 demonstrates the system's specificity in concluding the disease's development. There are several potential sources of error associated with this system. For one, if the data was not properly processed using the imaging software, such as an inconsistent area being selected for light analysis, the data can be skewed. Furthermore, the data was collected using a variety of different cameras of different makes and qualities, which will impact the quality of the data. Finally, the data was not collected in a completely dark or light controlled room, so the lighting can vary in different portions of the room, possibly skewing data as the huds were not completely light-insulated. Any of these inconsistencies and variabilities in the data could have made the statistics less specific or less sensitive, or vice versa. Intro to Computer-Aided Design 3D Modeling The team used SolidWorks CAD software when designing the parts. This is not because it was the easiest program to use, but rather, a few team members had taken BME182 the semester prior so this was the software that the team had experience in. The team was efficient when using the program. Different parts were delegated to different team members. The pieces delegated were the fluorimeter frame, the phone holder, and the pegs used to hold the tray at different levels in the fluorimeter. The program was easy for the team members to pick up and there were little to no issues with the program during the Computer-Aided Design lab and any issues were minor. For example, one issue was with the design of the peg and when assembling the pieces of the peg, the mating of the parts would not come easy so a small extrude cut had to be used to create edges to mate the two cylindrical components of the peg. Our Design Phone Holder for Fluorimeter Part Description: Our updated phone stand has a taller back in order to better support your phone and ensure that your pictures are taken at the same angle for each sample. There is a screw with a rubber backing attached to hold your phone in place. Simply place the phone in the stand then twist the screw until the phone fits snug against the back of the stand. This ensures the phone does not fall over between samples. The rubber protects the phone screen. This mechanism still allows for access to the phone screen to take pictures. Updated Fluorimeter With Pegs Fluorimeter Part Description: The standard fluorimeter which is placed on top of the redesigned structure for the system or at any other level of the structure. Fluorimeter Structure Part Description: The structure is 80 mm in length, 120 mm in height, and 57 mm in width. There are 2 inches at the bottom to keep the structure stable, and the rest of the structure is hollowed out with 12 mm thick rims. The rims have 3 levels of 0.4-inch diameter peg holes where pegs can be inserted to hold the fluorimeter. The fluorimeter can also be placed on the top of the structure making four levels on which to put the fluorimeter in total. Peg for Fluorimeter Structure Part Description: The peg is used in conjunction with the frame of the fluorimeter.They are used to support the tray with the drops being looked at. There is a total of twelve pegs which make up three different levels for the samples to rest at. The pegs screw into the holes in the frame and lock the tray into place keeping it from moving. Feature 1: Consumables All prior reagents that would normally be used in a PCR reaction are still needed, including the PCR mix, the primer solution, SYBR Green solution, a buffer, and a multitude of other chemicals. Plastic tubes and glass slides are also needed. Among these, the PCR mix and the SYBR Green solution would likely be listed as "very important". The other solutions/consumables can be bought in bulk, but PCR mix and SYBR Green would be essential to the PCR testing kit. Without these "very important" consumables, the kit would be made of basic lab supplies, and would not be a PCR-specific kit, as things such as buffers and plastic tubes can be found almost anywhere. Feature 2: Hardware - PCR Machine & Fluorimeter For our system, the Open PCR machine and the fluorimeter are included. This allows for the user to conduct PCR and then use the fluorimeter to analyze the results. Neither of these pieces is to be excluded as they are important to our system. The only redesign is of the fluorimeter. When we used the original fluorimeter, it was obvious that the images were not consistent which led to inconsistent data. With our redesign of this, we opted to make the smartphone feature more flexible and reliable. We created a phone holder which clamps the smartphone in place which makes images more precise. The phone will not slide around changing the view of the PCR samples. Another redesign that we did was to add multiple elevations for the PCR samples depending on the height of the chosen smartphone. This allows for the height of the phone to not hinder the system.