I tested more wtb, this time with the switch mode protocol. Here are the results:

With the modified laser settings I was able to test 3 more wtb. Here are the results:

–> yaw torque

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!

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…

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
}

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.

-Introduced Sayani to the wonderful world of Drosophila

-Been doing some DTS coding

-Preparing flies to do optomotor response for Mathias Raß

Updates in DTS code

Refreshing dissection skills

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)

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.