BME100 s2015:Group3 12pmL6

BME 100 Spring 2015	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: Abraham Rosengard Name: Juan Patterson Name: Gabriella Leiva-Hidalgo Name: Jessica Resendiz Name: Raghad Tamim LAB 6 WRITE-UP Bayesian Statistics Overview of the Original Diagnosis System What Bayes Statistics Imply about This Diagnostic Approach The probability that the patient will have a positive result about half of 1.00 and the positive PCR reaction is about half of 1.00 as well. The probability of the patient having a positive PCR reaction given the probability that a patient will get a positive result is very high. The probability that the patient will get a positive result given a positive PCR reaction is also very high. That means that the patient does have the disease. The probability that the patient sample contains a negative result is relatively close to being half. The negative diagnostic signal is in the middle of the spectrum as well. The frequency of a positive PCR, which is very high. The probability that a patient will get a negative final test conclusion, given a negative diagnostic signal extremely high, as a matter of fact it's OFF THE CHARTS. The probability the patient will develop disease is relatively low. The chances that the DNA sequence matches that of CHD (Coronary Heart Disease) is a little less than half, still relatively low. The probability that a patient will develop the disease, given a positive final test is about a 50% chance. The probability that a sample with the coronary heart disease sequence present given the probability of the patient developing the disease is slightly more than half. The probability that the patient does not have CHD is slightly more than half. The given a non- CDH DNA sequence is also slightly more than half. The probability that the patient will not have the disease given the fact that the DNA sequence for CHD is not present is about half. The probability that a patient will not develop the disease, given a negative final test conclusion is also half. Pipetting can cause error because often enough the sample can burst when it is being released or extracted causing the sample to spread throughout the glass slide which could potentially cause cross contamination of samples. The apparatus itself could also cause errors due to the fact that the system is not one but a consisting of very movable parts that can easily shift and change final results that image j calculates e.g. the phone holder can be accidentally moved, when it should be static. Other errors could be attributed to attributed to the design of the system and how the 'trap door' must be fully closed before the picture is actually taken. The door does not always close all the way causing extra light to come into the box which can skew the results once analyzed on image j. The samples were also sitting out the whole time and they were left uncovered for a time, being light sensitive, the samples have the potential to be damaged. + Computer-Aided Design TinkerCAD Our Design This machine is almost completely self-automated. The cybergreen, DNA samples, controls, and pipette cleaning solution are inserted into the slots located on the left box. While user-friendly system controls are typed into the computer to start the process, the machine will take the samples and arrange them accordingly in the PCR machine (center box) using a single pipette, repeatedly cleaning/reusing the same plastic tip. The cybergreen/examination process will take place on the right box and the cybergreen will not be exposed to any light and none of the DNA samples will spill due to human error. The product wastes will appear on the right most side and can be disposed of easily. Feature 1: Consumables Kit Feature 2: Hardware - PCR Machine & Fluorimeter