Name: Alexander Oropel Research and Development Scientist
Name: Matt McClintock Protocol
Name: Student Role(s)
Name: Student Role(s)
LAB 3 WRITE-UP
Original System: PCR Results
PCR Test Results
Sample Name
Ave. INTDEN*
Calculated μg/mL
Conclusion (pos/neg)
Positive Control
5725984.00
11.66 μg/mL
N/A
Negative Control
2820659.67
4.50 μg/mL
N/A
Tube Label: 1 Patient ID: 92336 rep 1
4902761.33
9.63 μg/mL
pos
Tube Label: 2 Patient ID: 92336 rep 2
4957051.00
9.77 μg/mL
pos
Tube Label: 3 Patient ID: 92336 rep 3
5446934.67
10.93 μg/mL
pos
Tube Label: 4 Patient ID: 44606 rep 1
2497338.33
3.70 μg/mL
neg
Tube Label: 5 Patient ID: 44606 rep 2
2202675.67
2.97 μg/mL
neg
Tube Label: 6 Patient ID: 44606 rep 3
1789569.00
1.95 μg/mL
neg
* Ave. INTDEN = Average of ImageJ integrated density values from three Fluorimeter images
Bayesian Statistics
These following conditional statistics are based upon all of the DNA detection system results that were obtained in the PCR lab for 20 hypothetical patients who were diagnosed as either having cancer or not having cancer.
Bayes Theorem is an equation in probability theory and statistics that relates inverse representations of probabilities concerning two events, or rather, it expresses a degree of change when accounting for evidence. Bayes Theorem is represented as follows:
P(A|B) = P(B|A) * P(A) / P(B)
Which can be read as
the probability of A given B = (the probability of B given A * the probability of A) / the probability of B
This information will be utilized to determine various probabilities listed below when accounting for the positive/negative values determined by the entire class as well as an outside document listing the actual yes/no cancer diagnosis
Calculation 1: The probability that the sample actually has the cancer DNA sequence, given a positive diagnostic signal.
A = Cancer-Positive Conclustion = 9/20 = .45
B = Positive PCR Reactions = 26/60 = .433
P (B|A) = Positive PCR given cancer Positive conclustion = 11/13 = .846
P(A|B) = .879=88%
Calculation 2: The probability that the sample actually has a non-cancer DNA sequence, given a negative diagnostic signal.
A = Cancer negative conclustion = 11/20 = .55
B = Negative PCR reactions = 17/30 = .567
P (B|A) = Negative PCR given cancer-negative conclustion = 16/17 = .94
P(A|B) = .911 = 91%
Calculation 3: The probability that the patient will develop cancer, given a cancer DNA sequence.
A = "yes" cancer diagnosis = 7/20 = .35
B = "positive" test conclusion = 9/20 = .45
P (B|A) = Positive given yes = 6/20 = .3
P(A|B) = .233 = 23%
Calculation 4: The probability that the patient will not develop cancer, given a non-cancer DNA sequence.
A = "no" cancer diagnosis = 13/20 = .65
B = "negative" test conclusion = 11/20 = .55
P (B|A) = Negative given no = 1/2 = .5
P(A|B) = .591 = 59%
New System: Design Strategy
"We concluded that a good system to "Must Have:'
Results that are easy to determine. This means a clear indication of positive or negative results when compared to the controls. This is integral to the design success because the results must be easy differentiable as to not require re-testing.
Software that is simple to use. The software for open PCR is incredibly easy to use and a program similar would be ideal. Anything that requires computer coding or computational design is too complicated, so the software must already be made to use. A user should be able to plug in the information he or she wants and get the desired response from the software, no computing needed.
We concluded that we would Want a good system to have:
Samples that are easily identifiable throughout the experiment. This means that there is no changing of labels or titles for the samples. This is important because it is crucial to keep the samples consistent and not mixed up. When transferring the samples there should be prepared labels to keep them straight.
Accessibility. This means that anyone can access the materials needed and replicate the findings. For the purpose of DNA amplification no advanced technology is required, the PCR machine is easy for anyone to access.
We concluded that a good system Must Not Have:
High cost. This means that the system must not be too expensive. This is important because the system should be replicable and useful to everyone.
We concluded that a good system Should Avoid:
[Should Avoid #1 - why? short, ~4 or 5 sentences]
[Should Avoid #2 - why? short, ~4 or 5 sentences]
New System: Machine/ Device Engineering
SYSTEM DESIGN
KEY FEATURES
We chose to include these new features
Feature 1 - explanation of how this addresses any of the specifications in the "New System: Design Strategy" section
Feature 2 - explanation of how this addresses any of the specifications in the "New System: Design Strategy" section
Etc.
[OR]
We chose keep the devices the same as the original system
Feature 1 - explanation of how a pre-existing feature addresses any of the specifications in the "New System: Design Strategy" section
Feature 2 - explanation of how a pre-existing feature addresses any of the specifications in the "New System: Design Strategy" section
Etc.
INSTRUCTIONS
New System: Protocols
DESIGN
We chose to include these new approaches/ features
Feature 1 - explanation of how this addresses any of the specifications in the "New System: Design Strategy" section
Feature 2 - explanation of how this addresses any of the specifications in the "New System: Design Strategy" section
Etc.
[OR]
We chose keep the protocols the same as the original system
Feature 1 - explanation of how a pre-existing feature addresses any of the specifications in the "New System: Design Strategy" section
Feature 2 - explanation of how a pre-existing feature addresses any of the specifications in the "New System: Design Strategy" section
Etc.
MATERIALS
PROTOCOLS
PCR Protocol
Step 1
Step 2
Etc.
DNA Measurement and Analysis Protocol
Step 1
Step 2
Etc.
New System: Research and Development
BACKGROUND
Polymerase chain reaction is the process of amplifying a strand of DNA from a DNA template strand. From here the scientist is capable of amplifying any specific gene they choose. In this research we are targeting the single nucleotide polymorphism that is rs1787996, which contains a single nucleotide variation or SNV. The CHEK2 gene is essentially a gene that is capable of coding for susceptibility to breast cancer. The relation to SNP is that it is essentially a variation of the CHEK 2 gene that is present within humans, or Homo sapiens. The cancer-related function of the gene is that it essentially changes the base Thymine to Cytosine, changing the normal allele ATT to ACT, which is the cancer related allele.
DESIGN
Primers for PCR
Amplification of cancer-associated DNA
Cancer allele forward primer: 5' TATGTATGCACTGTAAGAGTT
Cancer allele reverse prime: 5' CTAGGAGAGCTGGTAATTTGG
A disease allele will give a PCR product because the primer associated with the process will identify the sequences that will code for cancer. From there the primer will allow for nucleotide bases to be placed in a reverse sequence from the template DNA. Essentially this will continuously amplify the cancerous DNA gene while the PCR process is in effect.
Our primers address the following design needs
Design specification 1 - explanation of how an aspect of the primers addresses any of the specifications in the "New System: Design Strategy" section
Design specification 2 - explanation of how an aspect of the primers addresses any of the specifications in the "New System: Design Strategy" section
Etc.
New System: Software
[THIS SECTION IS OPTIONAL. If your team has creative ideas for new software, and new software is a key component included in your new protocols, R&D, or machine design, you may describe it here. You will not receive bonus points, but a solid effort may raise your overall page layout points. If you decide not to propose new software, please delete this entire section, including the ==New System: Software== header.]
BME 103 Spring 2013
