Optomotor graph coded

on Wednesday, February 21st, 2024 10:15 | by

There had been some concerns about the optomotor display in the group evaluation sheets showing right-turning torque on the left side of the graph and vice versa. Also, the use of standard deviations seemed to blur differences between the experimental groups:

Because of these concerns, I have swapped the traces and used standard error of the means instead of standard deviations:

What do you think? Better or worse? Feedback very welcome!

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Bachelor Blog / #4 is there something?

on Monday, August 7th, 2023 2:13 | by

The offspring of my first experimental fly cohort finally hatched! Below you find a few first pre-tests I ran last week :)

First, here are the results of a quick test to see if the offspring shows a preference for the parentally trained side after the first training period:

After that I played around with the laser a little bit to find the learning threshhold. I set the laser on 2,6V but the results I got look a bit weird:

-> untrained wtb flies

-> offspring of trained wtb flies

I´m optimistic however there is still a lot of work to do…

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Three Groups Example

on Monday, November 7th, 2022 12:06 | by

Pseudocode of the statical analysis with three groups according to the group descriptions.

# If n. of groups = 3 and n. of unique descriptions = 2, then perform
# the statistical analysis between singleton and each doubleton group.
# Else if n. of groups = 3 and descriptions are all identical/different,
# then perform the statistical analysis between each one of them.
if (NofGroups==3 & length(unique(groupdescriptions))==2) {
    statistical_analysis(singleton, doubleton_1)
    statistical_analysis(singleton, doubleton_2)
    plot_results
} else {
    statistical_analysis(group_1, group_2)
    statistical_analysis(group_1, group_3)
    statistical_analysis(group_2, group_3)
    plot_results
}
Example of a graph with two unique descriptions. Data: wtb (control), mut_1 (experimental), mut_2 (experimental).
Example of a graph with two unique descriptions. Data in a different order to show graph flexibility: mut_1 (experimental),
wtb (control), mut_2 (experimental)
Example of a graph with three different descriptions. Data: wtb (control), mut_1 (experimental_1), mut_2 (experimental_2).
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Three groups issue

on Monday, September 19th, 2022 1:00 | by


if(NofGroups == 3 & length(unique(groupdescriptions))==2){
  
  doubleton <- list()
  singleton <- list()
  
  if (groupdescriptions[1] == groupdescriptions[2]) {
     doubleton = c(unique(groupdescriptions[1], groupdescriptions[2]), 
                   groupnames[1], groupnames[2])
     singleton = c(groupdescriptions[3], groupnames[3])
  }  else if (groupdescriptions[2] == groupdescriptions[3]) {
     doubleton = c(unique(groupdescriptions[2], groupdescriptions[3]), 
                   groupnames[2], groupnames[3])
     singleton = c(groupdescriptions[1], groupnames[1])
  }  else {
     doubleton = c(unique(groupdescriptions[1], groupdescriptions[3]),  
                   groupnames[1], groupnames[3])
     singleton = c(groupdescriptions[2], groupnames[2])
  }
}

Given three descriptions, splits them into three variables. Two out of three of these are the same while the other is not: the single set to be compared to the two “identical” sets is emplaced in the singleton list while the other two sets are emplaced in the doubleton list.

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Progress Week 29

on Monday, July 20th, 2020 1:38 | by

-Introduced Sayani to the wonderful world of Drosophila

-Been doing some DTS coding

-Preparing flies to do optomotor response for Mathias Raß

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Progress week 26-28

on Monday, July 13th, 2020 1:39 | by

Updates in DTS code

Refreshing dissection skills

Tdc2-Gal4 expression in adult brain
Actin-GFP expression in adult brain

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Progress for week 25:

on Monday, June 22nd, 2020 1:58 | by

DTS coding
-Added progressbar for data validation
-Updated the progress bar (see figure 1)
-Fixed bug with wrong sample size (see figure 2)
-Fixed bug with unorganized barplots (see figure 2)

Figure 1. Updated progress bar
Figure 2. Correct sample size and restructured barplot


Exp always to the right:
plotOMparams <- plotOMparams[order(plotOMparams$desc),]
plotOMparams$group <- factor(plotOMparams$group, levels=paste(unique(plotOMparams$group)))


Samplesize fix:
samplesizes.annotate(boxes, as.numeric(table(plotOMparams$desc)))

Progressbar:
progress <- c(round(l(100/(length(xml_list)))),round(flycount(100/(totalflies))))

Rescreening:
-Finished rescreening last Thursday. Started to evaluate the new data

Optomotor platform: Ran a few more tests to confirm that the machine was still working, it is. I also adjusted the 0 line so that it is at 0, by readjusting the “zero line” screw. Looks much better now but it is still not perfectly at 0. A difference 0.1 on the computer screen translates to 100 in the evaluation chart.

Optomotor platform:
Ran a few more tests to confirm that the 0 line is always at 0. Readjusted the “zero line” screw. Looks much better now. It is still not perfectly at 0 but a difference of 0.1 in the chart translates to 100 in the evaluation graph.

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Pooling data not possible: working on a fix

on Tuesday, June 2nd, 2020 12:25 | by

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Dwelling time errors, prevents code from running

on Monday, May 25th, 2020 12:28 | by

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Statistical evaluation of OR

on Monday, May 25th, 2020 12:23 | by

Recently I measured the optomotor response in T4/T5 flies. As expected, they did not respond to the optomotor stimulus as seen in the left chart below. However, statistical evaluation struggles to quantify this difference. It might be that this is because of the low sample size, or that we are using the wrong statistical analysis?

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