BME100 f2014:Group26 L6: Difference between revisions
No edit summary |
No edit summary |
||
Line 37: | Line 37: | ||
<!-- Instruction 1: In your own words, discuss what the results for calculations 1 and 2 imply about the reliability of the individual PCR replicates for concluding that a person has the disease SNP or not. Please do NOT type the actual numerical values here. Just refer to the Bayes values as being "close to 1.00 (100%)" or "very small." Discuss at least three possible sources of human or machine/device error that could have occurred during the PCR & detection steps that could have affected the Bayes values in a negative way. --> | <!-- Instruction 1: In your own words, discuss what the results for calculations 1 and 2 imply about the reliability of the individual PCR replicates for concluding that a person has the disease SNP or not. Please do NOT type the actual numerical values here. Just refer to the Bayes values as being "close to 1.00 (100%)" or "very small." Discuss at least three possible sources of human or machine/device error that could have occurred during the PCR & detection steps that could have affected the Bayes values in a negative way. --> | ||
For Calculation 1, the probability result reflected that the Bayes value is close to 1.00. For the second Calculation, the probability also reflective of the Bayes value being close to 1.00. Based on these values, it can be concluded that the person has the disease SNP. Since these results Error that may have resulted during the PCR & detection steps could be that the samples were exposed to too much light. Another could be incorrect analysis of the samples using ImageJ. Another possible source of error could be an inadequate photo quality. | For Calculation 1, the probability result reflected that the Bayes value is close to 1.00. For the second Calculation, the probability also reflective of the Bayes value being close to 1.00. Based on these values, it can be concluded that the person has the disease SNP. Since these results | ||
Error that may have resulted during the PCR & detection steps could be that the samples were exposed to too much light. Another could be incorrect analysis of the samples using ImageJ. Another possible source of error could be an inadequate photo quality. | |||
<!-- Instruction 1: In your own words, discuss what the results for calculations 3 and 4 imply about the reliability of PCR for *predicting the development disease* (referred to as "diagnosis"). Please do NOT type the actual numerical values here. Just refer to the Bayes values as being "close to 1.00 (100%)" or "very small." --> | <!-- Instruction 1: In your own words, discuss what the results for calculations 3 and 4 imply about the reliability of PCR for *predicting the development disease* (referred to as "diagnosis"). Please do NOT type the actual numerical values here. Just refer to the Bayes values as being "close to 1.00 (100%)" or "very small." --> | ||
Line 70: | Line 72: | ||
<!-- Instruction 2: IF your group has decided to redesign the PCR machine and/or Fluorimeter to address any major weakness(es), explain how in an additional paragraph. --> | <!-- Instruction 2: IF your group has decided to redesign the PCR machine and/or Fluorimeter to address any major weakness(es), explain how in an additional paragraph. --> | ||
<!-- Do not edit below this line --> | <!-- Do not edit below this line --> | ||
|} | |} |
Revision as of 20:45, 24 November 2014
BME 100 Fall 2014 | 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 In this experiment, 68 patients were tested for a disease marker to predict their likelihood of developing the disease. These patient samples were divided among 34 teams in the BME 100 class. Each team, which consists of 6 members, received three replicates of each of the patient's data and two controls. Within the lab groups, the students worked together to perform image analysis. Errors were attempted to be prevented through multiple avenues, including: quantitative results and controls. The replicates of each patient's DNA prevented error, because it allowed for more quantitative data. In addition, there were PCR controls (+/- control samples) that were used in ImageJ to calibrate. The ImageJ calibration was based on the controls. The controls allowed for a baseline to refer to when analyzing patient data. To ensure accuracy, three drop images were analyzed through ImageJ calculations for each patient, and for each control. For the final data, of the 68 tests run, 8 of the results were inconclusive, 6 of the results were blank data and the remaining 54 results led to successful conclusions. What Bayes Statistics Imply About This Diagnostic Approach
Error that may have resulted during the PCR & detection steps could be that the samples were exposed to too much light. Another could be incorrect analysis of the samples using ImageJ. Another possible source of error could be an inadequate photo quality.
Computer-Aided DesignTinkerCAD
Our Design
Feature 2: Consumables KitFeature 3: Hardware - PCR Machine & Fluorimeter |