BME100 f2014:Group22 L6: Difference between revisions

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In order to test various patients for the presence of the disease-associated SNP, 34 teams of roughly 6 members each ran tests using a PCR reaction. Each group tested two individual patients, and prepared three replicated solutions of DNA and primer mix for each to be compared to positive and negative controls. The three replicant solutions from each pair of patients were then run through 30 cycles in the Open PCR machines along with the positive and negative controls, giving a total of 8 PCR results per group. In order to compare each of the results to one another and determine their concentrations of DNA, a calibration curve was created using the fluorimeter and solutions of DNA of known concentrations. For calibration, 6 drops were prepared using 80 μL of DNA solution (0, 0.25, 0.5, 1, 2, and 5 μg/mL concentrations) and 80 μL of SYBR GREEN I dye were placed on a hydrophobic slide and placed in the fluorimeter. Using the same camera settings and distance from the camera to the fluorimeter (within each group; setups and cameras varied from group to group), three photos were taken of each droplet in the fluorimeter to prevent error and increase the reliability of the data. Each of the 8 test solutions from the PCR machine were put in the fluorimeter in a similar fashion. Then in ImageJ, the photos of the both calibration solutions and the solutions from the PCR machine were analyzed, comparing the intensity of green wavelengths of light between the droplet and the background interference. This resulted in a quantitative measure of the intensity of fluorescence from the SYBR GREEN I dye that could be compared to the calibration solutions to find the approximate concentration of DNA in the solution. As a result of the entire class's data (34 groups, 68 total patients), 30 patients' tests returned a positive conclusion, while 24 returned a negative conclusion. Out of the remaining 14 patients' samples, 8 were inconclusive and 6 were failed tests with no conclusion at all.
In order to test various patients for the presence of the disease-associated SNP, 34 teams of roughly 6 members each ran tests using a PCR reaction. Each group tested two individual patients, and prepared three replicated solutions of DNA and primer mix for each to be compared to positive and negative controls. The three replicant solutions from each pair of patients were then run through 30 cycles in the Open PCR machines along with the positive and negative controls, giving a total of 8 PCR results per group. In order to compare each of the results to one another and determine their concentrations of DNA, a calibration curve was created using the fluorimeter and solutions of DNA of known concentrations. For calibration, 6 drops were prepared using 80 μL of DNA solution (0, 0.25, 0.5, 1, 2, and 5 μg/mL concentrations) and 80 μL of SYBR GREEN I dye were placed on a hydrophobic slide and placed in the fluorimeter. Using the same camera settings and distance from the camera to the fluorimeter (within each group; setups and cameras varied from group to group), three photos were taken of each droplet in the fluorimeter to prevent error and increase the reliability of the data. Each of the 8 test solutions from the PCR machine were put in the fluorimeter in a similar fashion. Then in ImageJ, the photos of the both calibration solutions and the solutions from the PCR machine were analyzed, comparing the intensity of green wavelengths of light between the droplet and the background interference. This resulted in a quantitative measure of the intensity of fluorescence from the SYBR GREEN I dye that could be compared to the calibration solutions to find the approximate concentration of DNA in the solution. As a result of the entire class's data (34 groups, 68 total patients), 30 patients' tests returned a positive conclusion, while 24 returned a negative conclusion. Out of the remaining 14 patients' samples, 8 were inconclusive and 6 were failed tests with no conclusion at all. As far as diagnosing patients, the PCR tests across all 34 groups correctly diagnosed 10 patients out of 23 that had the disease, and 12 patients out of 45 that did not have the disease.  
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<!-- Instruction 1: In your own words, discuss what the results for calculations 1 and 2 imply about the reliability of the individual PCR replicates for concluding that a person has the disease SNP or not. Please do NOT type the actual numerical values here. Just refer to the Bayes values as being "close to 1.00 (100%)" or "very small." Discuss at least three possible sources of human or machine/device error that could have occurred during the PCR & detection steps that could have affected the Bayes values in a negative way. -->
<!-- Instruction 1: In your own words, discuss what the results for calculations 1 and 2 imply about the reliability of the individual PCR replicates for concluding that a person has the disease SNP or not. Please do NOT type the actual numerical values here. Just refer to the Bayes values as being "close to 1.00 (100%)" or "very small." Discuss at least three possible sources of human or machine/device error that could have occurred during the PCR & detection steps that could have affected the Bayes values in a negative way. -->


<p>
For calculations 1 and 2, the bayesian statistics had to do with the relationship between the likelihood of a PRC test (including replicates of the same patient) being positive and the likelihood of the overall conclusion (taking into account all three replicates of each patient) being positive. Overall, the likelihood of a positive PCR test resulting in a positive conclusion (sensitivity) and the likelihood of a negative PCR test resulting in a negative conclusion (specificity) were both fairly close to 1.0, although the system had a slightly lower specificity than its sensitivity. This means that the actual PCR test was fairly effective at producing positive conclusions, but it was slightly less conclusive when it came to negative ones. This discrepancy may be due to the fact that the conclusion was fairly arbitrary, requiring intuitive human judgement (across 34 different groups) to judge whether the concentration of DNA was more similar to the positive control than the negative one. Another source of error comes from the disparity between camera setups between groups, as neither the brand of phone nor the specific camera settings nor the distance between the camera and the fluorimeter were held constant between groups.
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'''Calculations 1 & 2: Conclusiveness and Errors of PCR Tests'''
'''Calculations 1 & 2: Conclusiveness and Errors of PCR Tests'''



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Bayesian Statistics

Overview of the Original Diagnosis System

In order to test various patients for the presence of the disease-associated SNP, 34 teams of roughly 6 members each ran tests using a PCR reaction. Each group tested two individual patients, and prepared three replicated solutions of DNA and primer mix for each to be compared to positive and negative controls. The three replicant solutions from each pair of patients were then run through 30 cycles in the Open PCR machines along with the positive and negative controls, giving a total of 8 PCR results per group. In order to compare each of the results to one another and determine their concentrations of DNA, a calibration curve was created using the fluorimeter and solutions of DNA of known concentrations. For calibration, 6 drops were prepared using 80 μL of DNA solution (0, 0.25, 0.5, 1, 2, and 5 μg/mL concentrations) and 80 μL of SYBR GREEN I dye were placed on a hydrophobic slide and placed in the fluorimeter. Using the same camera settings and distance from the camera to the fluorimeter (within each group; setups and cameras varied from group to group), three photos were taken of each droplet in the fluorimeter to prevent error and increase the reliability of the data. Each of the 8 test solutions from the PCR machine were put in the fluorimeter in a similar fashion. Then in ImageJ, the photos of the both calibration solutions and the solutions from the PCR machine were analyzed, comparing the intensity of green wavelengths of light between the droplet and the background interference. This resulted in a quantitative measure of the intensity of fluorescence from the SYBR GREEN I dye that could be compared to the calibration solutions to find the approximate concentration of DNA in the solution. As a result of the entire class's data (34 groups, 68 total patients), 30 patients' tests returned a positive conclusion, while 24 returned a negative conclusion. Out of the remaining 14 patients' samples, 8 were inconclusive and 6 were failed tests with no conclusion at all. As far as diagnosing patients, the PCR tests across all 34 groups correctly diagnosed 10 patients out of 23 that had the disease, and 12 patients out of 45 that did not have the disease.

What Bayes Statistics Imply about This Diagnostic Approach


For calculations 1 and 2, the bayesian statistics had to do with the relationship between the likelihood of a PRC test (including replicates of the same patient) being positive and the likelihood of the overall conclusion (taking into account all three replicates of each patient) being positive. Overall, the likelihood of a positive PCR test resulting in a positive conclusion (sensitivity) and the likelihood of a negative PCR test resulting in a negative conclusion (specificity) were both fairly close to 1.0, although the system had a slightly lower specificity than its sensitivity. This means that the actual PCR test was fairly effective at producing positive conclusions, but it was slightly less conclusive when it came to negative ones. This discrepancy may be due to the fact that the conclusion was fairly arbitrary, requiring intuitive human judgement (across 34 different groups) to judge whether the concentration of DNA was more similar to the positive control than the negative one. Another source of error comes from the disparity between camera setups between groups, as neither the brand of phone nor the specific camera settings nor the distance between the camera and the fluorimeter were held constant between groups.

Calculations 1 & 2: Conclusiveness and Errors of PCR Tests


Calculations 3 & 4: Accuracy and Errors of RNP Results in Detecting Disease

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