Three groups issue

on Monday, September 19th, 2022 1:03 | by

  desc_1 <- tolower(grouped.OMparams[[1]]$desc)
  desc_2 <- tolower(grouped.OMparams[[2]]$desc)
  desc_3 <- tolower(grouped.OMparams[[3]]$desc)
  if(desc_1[1] == desc_2[1]) {
    Control[[1]] = na.omit(grouped.OMparams[[1]])
    Control[[2]] = na.omit(grouped.OMparams[[2]])
    Exp = na.omit(grouped.OMparams[[3]])
    Count = 2
  } else if(desc_1[1] == desc_3[1]) {
    Control[[1]] = na.omit(grouped.OMparams[[1]])
    Control[[2]] = na.omit(grouped.OMparams[[3]])
    Exp = na.omit(grouped.OMparams[[2]])
    Count = 2
  } else {
    Control[[1]] = na.omit(grouped.OMparams[[2]])
    Control[[2]] = na.omit(grouped.OMparams[[3]])
    Exp = na.omit(grouped.OMparams[[1]])
    Count = 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 Exp list while the other two sets are emplaced in the Control list (the name of these two variables should be replaced).

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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)))

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

-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 | 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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Making sense of dwelling data

on Tuesday, March 24th, 2020 12:54 | by

Mean or median?


A highly hypothetical scenario of how the distribution of dwelling times could be. Even if unrealistic, it still illustrates the problem of using median instead of mean.

Plotting the dwelling times as means

An example fly of how the dwelling times are distributed over the different periods.

Grouped analysis of dwelling times

Cumming estimation plot

Used the R package Dabestr to plot the estimation statistics. The effect size and 95% CIs are plotted a separate axes
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Updates on optomotor response software

on Friday, March 20th, 2020 3:19 | by

  • Added a timer
  • Previous version generated faulty xml files. This bug has been squashed (see image below)
  • Display window of the software now also prints which direction the striped arena turns
The highlighted red areas are the ones that caused issues. Contingency has also been added to the xml file from the optomotor response (not shown). This did not cause any errors when running the DTS analysis Rscript but I thought it looked nicer having it there.
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Dwelling time

on Monday, February 3rd, 2020 1:41 | by

The schematic drawing is an example. The method that is currently used to calculate the dwelling time is excluding times that are 50 ms. Each dwelling time is getting an additional 50ms to compensate for the transitional time loss (dashed line in schematic drawing). The chart on the right side is the total time for each period when adding negative and positive dwelling times.

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