BME100 f2015:Group7 1030amL6
BME 100 Fall 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
LAB 6 WRITE-UPBayesian StatisticsOverview of the Original Diagnosis System The division labor of how BME100 tested patients for the disease-associated SNP, there was 17 teams of 6 students each diagnosed 34 patients, each group had a total of two patients.The things that were done to prevent error were labeling each patients ID number in order to not get them confused. Each patient has a total of three DNA samples, there was also a positive and negative control to compare to each sample. For each sample we took three pictures, with a total of twenty four pictures. For each picture, we used the ImageJ program to split channels and each result was labeled and put onto a table.the overall results for the BME 100 PCR were successfully conclusive with positive and negative results,however there was a few inconclusive results. There was also one group that had blank data because of technical difficulties. Some of the difficulties may have effected our data was that for the flourimeter it wasn't completely dark and some light interfere and may have alter the results by the time the images were analyze by ImageJ program. What Bayes Statistics Imply about This Diagnostic Approach Calculation 1 was close to 75%, which means that there is a high probability that a positive test result will occur given that there is a positive PCR reaction. Calculation 2 was close to 100%, which means that there is a very high probability that a negative final test result will occur, given a negative diagnostic signal. Both calculations 1 and 2 seem to have a high reliability. Calculation 3 is close to 25%, which indicates that there is a low probability that the patient will develop the disease, given a positive final test result. Calculation 4 is close to 90%, which indicates that there is a high probability that a patient will not develop a disease given a negative final test result. There is a low reliability because the probabilities are very different. Three possible errors: Measuring could have been compromised, pipettes may have been in device for wrong period of time, lids may not have been closed tight enough. Consumables: plastics, pipettor, and reagents (PCR mix, primers) STRENGTH: Disposable, inexpensive, abundancy, easy to use. WEAKNESS: bad for the environment, because they are disposable there is the need to use many consumables. The OpenPCRmachine and software STRENGTH: the time was reasonable for the PCR to be copied. WEAKNESS: sample space is limited. The Fluorimeter system(including slides, stand, etc.) STRENGTH: the functionality of the overall fluorimeter WEAKNESS: the size, it was hard to adjust the height.
Intro to Computer-Aided DesignTinkerCAD Our Design
Feature 1: ConsumablesThe consumables used with the experiment are glass slides, tubing, PCR mix, primer solution, SYBR Green solution, buffer, pipettor, and a PCR machine. The kit that comes along with the Fluorimeter includes a PCR device, a pipetter, and glass slides. Feature 2: Hardware - PCR Machine & FluorimeterThe PCR and the fluorimeter will both be included in the package system. The Fluorimeter is the only device that will be improved. The PCR device will be left unchanged. The group decided to make the Fluorimeter have a machine operated height system. The original Fluorimeter was not tall enough to be viewed at a high enough level for viewers or a camera. The new design creates a better functioning viewing experience. The Fluorimeter will have a switch that can lower and higher the device using a scissor lift. Another change to the Fluorimeter will be a screen that tells the experimenter what the percentage of the green is in the liquid. The device will include a camera that will capture an image of the light and use an image j system to calculate the percentage of green in the liquid.
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