# BME100 f2015:Group11 1030amL6 BME 100 Fall 2015 Home
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Lab Write-Up 1 | Lab Write-Up 2 | Lab Write-Up 3
Lab Write-Up 4 | Lab Write-Up 5 | Lab Write-Up 6
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## Bayesian Statistics

Overview of the Original Diagnosis System

BME 100 took two patients DNA samples and made three replicas of each DNA and then had a positive and negative control. Each sample was placed into a tube and primer gets added to each one. The samples are then placed into the OpenPCR machine which was pre-set to certain cycles. These cycles start with the heated lid which is 100*C, then the initial step of 95*C for 2 minutes, then 25 cycles of denature at 95*C for 30 seconds, anneal at 57*C for 30 seconds, and extend at 72*C for 30 seconds, then the final step at 72*C for 2 minutes, and final hold at 4*C. The samples were left in the OpenPCR machine and were removed once the cycles were completed. Next we took each of the samples and looked at them with the fluorimeter box which emitted a light through the sample droplet and revealed a green fluorescence which showed that the disease was present in our patients. Once all of the data was gathered there were a few groups that received inconclusive results, most groups received successful results, and only one group received blank data. There were many errors that could have occurred in this experiment that could have altered the final results of whether the patient intact does have the disease or not. Some of these could have been not putting the correct amounts of each sample in the tubes and also incorrectly placing the primer incorrectly. It was assumed that all of these things were done correctly but there could always be an error.

With calculations 1 and 2 they were both around the 50% probability for a positive test result and negative test result. But the probability of a positive final test conclusion given a positive PCR reaction and the probability of a positive PCR reaction given a positive final test conclusion was about an 80% probability. This also occurred with the probability of a negative final test conclusion given a negative diagnostic signal and the probability of a negative diagnostic signal given a negative final test conclusion, where the probability was about 80%.

in calculations 3 the probability that a patient will develop a disease given a positive final test conclusion and the probability of a positive final test conclusion given the patient will develop the disease were about 25% which is a relatively small chance. But then with calculation 4 the probability that a patient will not develop the disease given a negative final test conclusion and the probability of a negative final test conclusion given that a patient will not develop the disease were about 60% which is a much better chance of not getting the disease when a patient's test comes out negative.

Three possible errors of human error or machine error would be with the pipetting, the measuring of solutions, and the readings of the machine. With the pipetting it can be hard to get the exact amount to and from each tube so that could cause error. Also with the measuring, it is hard to get exact measurements of such small amounts of solutions without the correct measurements there could be errors, and the machine could measure incorrectly which would give false data and cause errors in diagnosis.

Calculation #1
 Variable Description Numerical Value A Positive final test conclusion 13/32 or 0.41 B A positive PCR reaction 43/96 or 0.45 P(A|B) Probability of a positive final test conclusion given a positive PCR reaction. 0.77 P(B|A) Probability of a positive PCR reaction given a positive final test conclusion. 33/39 or 0.85
Calculation #2
 Variable Description Numerical Value A A negative final test conclusion 17/32 or .53 B A negative diagnostic signal 47/96 or 0.49 P(A|B) The probability of a negative final test conclusion given a negative diagnostic signal. .84 P(B|A) The probability of a negative diagnostic signal given a negative final test conclusion. 42/54 or .78
Calculation #3
 Variable Description Numerical Value A Patient will develop the disease. 10/32 or .31 B A positive final test conclusion. 13/32 or .41 P(A|B) The probability that a patient will develop a disease given a positive final test conclusion. .23 P(B|A) The probability of a positive final test conclusion given the patient will develop the disease. 4/13 or .31
Calculation #4
 Variable Description Numerical Value A A patient will not develop the disease. 22/32 or .69 B A negative final test conclusion. 17/32 or .53 P(A|B) The probability that a patient will not develop the disease given a negative final test conclusion. .65 P(B|A) The probability of a negative final test conclusion given that a patient will not develop the disease. 12/24 or .5

## Intro to Computer-Aided Design

Our Design  We addressed two problems with the PCR machine in our new design. These problems were with the number of test tube holes and not being able to know what cycle the machine is on. Our design has more holes in the tube holding chamber so more reactions can occur at once, we also added a phase indicating light source which will tell you what stage the reaction is in, and lastly we changed the colors

## Feature 1: Consumables

Very important consumables are supplies specific to the PCR kit that must be included with the new design of the PCR machine. Our new design does not require any new consumables because the only changes to the design are a light to show the phase of the PCR reaction and an increased amount of tube holding holes. Therefore, we would include the same basic consumables in our kit.

List of Consumables
- Plastic Tubes
- PCR mix
- Primer Solution
- SYBR Green Solution
- Buffer
- Micro-Pipette Tips

## Feature 2: Hardware - PCR Machine & Fluorimeter

We addressed two weaknesses in the PCR machine to make it more effective. We added more holes for the tubes to be placed in so the machine can run more tests at once and more data can be gathered. We also added a light to the front that will change colors to indicate what stage of the cycle that the machine is on. These improvements will allow more tests to be done at once and will allow the tester to know what stage the cycles are on so they can know how much time is left and when the temperatures are changing.