BME100 f2014:Group34 L6

From OpenWetWare

Jump to: navigation, search
BME 100 Fall 2014 Home
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
Wiki Editing Help



Victor Huerta
Victor Huerta
Xavier Richmond
Xavier Richmond
Ferrin Thomas
Ferrin Thomas
Morgan Seburn
Morgan Seburn
Teja Vemulapalli
Teja Vemulapalli



Bayesian Statistics

Overview of the Original Diagnosis System

What Bayes Statistics Imply about This Diagnostic Approach

The reliability of indidivual PCR replicates for concluding that a person has the disease SNP are actually fairly reliable. The values for the probability a patient will get either a positive or a negative final test conclusion are much closer to 100% than 0% indicating that the chances someone may or may not get the disease given a positive or negative diagnostic signal, respectively, are high. Possible sources of error that could have had a negative impact on the Bayes values include: (1) Improper/Incorrect micropipette technique. Failing to transfer the exact amount of solution from tube to tube could significantly alter the concentration of DNA after the polymerase chain reaction. (2) Human error in imageJ software. Failing to select the entire drop in the image or selecting an area greater than that of the drop would lead to incorrect INTDEN values, the values that we then converted into concentrations. If the INTDEN values are wrong our concentrations will also be wrong. (3) The slide with the drop of PCR product and SYBR Green could have been misaligned with the blue LED leaving some of the drop not illuminated. As a result, it would not have been captured in the photo and left out of the analysis on imageJ, skewing INTDEN/concentration values and consequently, our Bayes calculations.

The results of calculation 3 describes the sensitivity of the system regarding the ability to predict the disease. The probability that a patient will develop the disease, given a positive final test conclusion was very high. Calculation 4 describes the specificity of the system regarding the ability to predict the disease. The probability that a patient will not develop the disease, given a negative final test conclusion was very low. This discovery implies that a PCR is in fact reliable for predicting the development disease.

Computer-Aided Design


TinkerCAD is an online 3D modeling software that we used to create our own rendition of the PCR machine. We used it to create a visual representation of what we had changed about the device. It helped to recreate what we retained from the original design while allowing us to add to the device.

Our Design


We chose the design above so that a addition part added to the side could incorporate a fluorimeter into the PCR machine. This addition would work mechanically connecting to the rest of the PCR. This automated fluorimeter would help to eliminate human error. Additionally it would make the whole process more efficient, eliminating the need for micropipetting.

Feature 1: Consumables Kit

Liquid reagents will be stored in small tanks and containters on the exterior of the device. Rubber hosing will transport the fluids from the storage units to the needed location. This entire system is electronic and controlled by a computer chip inside the device. Small plastics will be packaged alongside the device with a means of ordering replacements made available through the internet.

By having an automated system to control volumes of liquid reagents going into the PCR, we eliminate the source of error brought about by improper micropipette technique. By using a computer, we can guarantee that the exact volume of reagent is being added to the reaction and the fluorimeter.

Feature 2: Hardware - PCR Machine & Fluorimeter

Since both the Fluorimeter and the PCR machine are essential instruments to be used in labs for DNA related tests, any improvements to these instruments would provide for more accurate and reliable results. Regarding the Fluorimeter, the group decided to have an automated dispensing mechanism for the liquid reagents, allowing for less human errors to occur and for more accurate data. Also an improvement on the The group also considered combining these two instruments into one device to eliminate any outside contamination or other factors that could alter the results received from the lab.

Personal tools