Difference between revisions of "DNA Melting Report Requirements"

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(→‎Report outline)
(→‎Report outline)
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#;Model Parameter Determination: For each sample type, show a comparison of your data to a modeled sigmoidal curve from the thermodynamic model, and compare each to a simulated result obtained from DINAmelt or another melting curve simulator.
 
#;Model Parameter Determination: For each sample type, show a comparison of your data to a modeled sigmoidal curve from the thermodynamic model, and compare each to a simulated result obtained from DINAmelt or another melting curve simulator.
 
##These plots should be in the "ideal" format. For each sample type:  
 
##These plots should be in the "ideal" format. For each sample type:  
−
###Fit a model to your melting curve data.  
+
###Fit a model to your as-observed melting curve data by applying corrections to the ideal curve output by DnaFraction.m. Use a predicted sample temperature based on the measured heating block temperature. Both the parameters used to correct DnaFraction.m as well as the sample temperature lag time and gain should be part of your fit.
−
###Scale the data to make it look like the 'ideal sigmoidal form,' from 1 to 0 like the output of DnaFraction.m, using the corrections you applied to that model and the parameters obtained from your fit.  
+
###Now use the parameters found in that fit and the inverse of your corrections to scale the data to make it look like the ideal model, plotted vs the predicted sample temperature.
−
###Average the corrected curves for all successful runs of that sample type.  
+
###Average the scaled curves for all successful runs of that sample type.
−
###Finally, compare each of those corrected, averaged curves to the ideal curve for that sample type. (Ideal curves are obtained using your fitted ΔS and ΔH in the basic thermodynamic model.)
+
###Compare each of those averaged, scaled curves to the ideal sigmoidal curve for that sample type obtained using the ΔS and ΔH you obtained by fitting your model.
−
##Also include an example or two of plots in the "as-observed" format, showing that your model fit well to the as-observed data. For these examples, also include a plot of a modeled response using your initial guesses.
+
###In the same figure, show the melting curve predicted by simulation with DINAMelt of equivalent.
 +
##Also, in a separate figure include an example or two of plots in the "as-observed" format, showing that your model fit well to the as-observed data, and showing your initial guess(es).
 
#;Unknown determination: Finally, include averaged, corrected data and a modeled response for your unknown sample either on the above dsDNA and ΔdsDNA plots, or in separate plots.
 
#;Unknown determination: Finally, include averaged, corrected data and a modeled response for your unknown sample either on the above dsDNA and ΔdsDNA plots, or in separate plots.
−
#;Table of estimated thermodynamic parameters for each sample. Include estimated &Delta;H, &Delta;S, and T<sub>m</sub> values (by multiple methods)
+
#;Include a table of estimated thermodynamic parameters for each sample. Include estimated &Delta;H, &Delta;S, and T<sub>m</sub> values (by multiple methods)
−
#;Comparative data analysis and plots:Plots of any data you analyzed that came from other groups
+
#;Show comparative data analysis and plots:Plots of any data you analyzed that came from other groups.
−
#;Data analysis overview:Informative '''Bullet point''' summary of your data analysis methodology. Teach us what you did.
+
#;Give a data analysis overview using an informative '''Bullet point''' summary of your data analysis methodology. Teach us what you did.
−
#;Discussion of results:'''Bullet point''' discussion of results. Compare your results to theoretical models and/or other group's datasets. Be concise, but express yourself clearly.
+
#;Discuss your results: Compare your results to theoretical models and/or other group's datasets. Be concise, but express yourself clearly.
−
#'''Sources of error:'''Detailed discussion of error sources. Indicate whether each source causes a systematic or random distortion in the data. (The uncertainty from a random error decreases with additional experimental runs; systematic error does not.) Consider all possible sources of error including all aspects of your instrument, the oligo design, the dye used, the experimental methodology, and the analysis methodology.
+
#'''Sources of error: '''Provide a detailed discussion of error sources. Indicate whether each source causes a systematic or random distortion in the data. (The uncertainty from a random error decreases with additional experimental runs; systematic error does not.) Consider all possible sources of error including all aspects of your instrument, the oligo design, the dye used, the experimental methodology, and the analysis methodology.
 
# Instrument documentation
 
# Instrument documentation
 
#;Block diagram and schematics:Include component values, relevant distances, and possibly a photograph or two. It is not necessary to document construction details, but do show your work in determining your component values, distances, etc.
 
#;Block diagram and schematics:Include component values, relevant distances, and possibly a photograph or two. It is not necessary to document construction details, but do show your work in determining your component values, distances, etc.
 
#;Signal to noise results
 
#;Signal to noise results
−
#;Design evolution:'''Bullet point''' summary of changes you made to your instrument design to address problems in the lab.
+
#;Design evolution:Give a '''bullet point''' summary of changes you made to your instrument design to address problems in the lab.
  
 
==Lab manual sections==
 
==Lab manual sections==

Revision as of 05:05, 9 November 2012

20.309: Biological Instrumentation and Measurement

ImageBar 774.jpg


Report outline

Use the following format for your report:

  1. Report submittal format
    Size of your lab manual file submitted MUST be less than 20 MB
    Post only pdf, with code included in the pdf at the end, not separately
    Include last name of each group member in the filename of the pdf you post. I would rather spend time carefully grading your report than renaming your files because every other group named theirs "DNA Report Part 2" or the like.
  2. Results
    Samples run
    List all of the samples you characterized (length/match/ionic strength)
    Data plots
    All plots should be complete with title, axis labels, and legend. Plot both your experimental data and the best fit curves from the DNA melting mode. Plots in this section should include only data that was created by your group's own hands in the lab. Analysis of other people's datasets belongs in a different section (see below).
    1. Single set of axes with plots of dsDNA concentration versus temperature for ALL raw data from all "known" samples that you ran.
    2. Single set of axes with plots of ΔdsDNA concentration/Δtemperature vs temperature for same.
    3. Similar figure, single axes, showing results for unknown sample, possibly including other samples run for comparison.
    Model Parameter Determination
    For each sample type, show a comparison of your data to a modeled sigmoidal curve from the thermodynamic model, and compare each to a simulated result obtained from DINAmelt or another melting curve simulator.
    1. These plots should be in the "ideal" format. For each sample type:
      1. Fit a model to your as-observed melting curve data by applying corrections to the ideal curve output by DnaFraction.m. Use a predicted sample temperature based on the measured heating block temperature. Both the parameters used to correct DnaFraction.m as well as the sample temperature lag time and gain should be part of your fit.
      2. Now use the parameters found in that fit and the inverse of your corrections to scale the data to make it look like the ideal model, plotted vs the predicted sample temperature.
      3. Average the scaled curves for all successful runs of that sample type.
      4. Compare each of those averaged, scaled curves to the ideal sigmoidal curve for that sample type obtained using the ΔS and ΔH you obtained by fitting your model.
      5. In the same figure, show the melting curve predicted by simulation with DINAMelt of equivalent.
    2. Also, in a separate figure include an example or two of plots in the "as-observed" format, showing that your model fit well to the as-observed data, and showing your initial guess(es).
    Unknown determination
    Finally, include averaged, corrected data and a modeled response for your unknown sample either on the above dsDNA and ΔdsDNA plots, or in separate plots.
    Include a table of estimated thermodynamic parameters for each sample. Include estimated ΔH, ΔS, and Tm values (by multiple methods)
    Show comparative data analysis and plots
    Plots of any data you analyzed that came from other groups.
    Give a data analysis overview using an informative Bullet point summary of your data analysis methodology. Teach us what you did.
    Discuss your results
    Compare your results to theoretical models and/or other group's datasets. Be concise, but express yourself clearly.
  3. Sources of error: Provide a detailed discussion of error sources. Indicate whether each source causes a systematic or random distortion in the data. (The uncertainty from a random error decreases with additional experimental runs; systematic error does not.) Consider all possible sources of error including all aspects of your instrument, the oligo design, the dye used, the experimental methodology, and the analysis methodology.
  4. Instrument documentation
    Block diagram and schematics
    Include component values, relevant distances, and possibly a photograph or two. It is not necessary to document construction details, but do show your work in determining your component values, distances, etc.
    Signal to noise results
    Design evolution
    Give a bullet point summary of changes you made to your instrument design to address problems in the lab.

Lab manual sections

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