## Bachelor Blog / #4 is there something?

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

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…

## Three Groups Example

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

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
}

Category: R code | No Comments

## Three groups issue

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

```
```**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.

Category: R code | No Comments

## Progress Week 29

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

-Introduced Sayani to the wonderful world of *Drosophila*

-Been doing some DTS coding

-Preparing flies to do optomotor response for Mathias Raß

Category: flight, genetics, Lab, Memory, Optomotor response, R code | No Comments

## Progress week 26-28

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

Category: Anatomy, genetics, Lab, neuronal activation, personal, R code, science, Uncategorized | No Comments

## Progress for week 25:

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

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.

Category: Lab, Optomotor response, R code, Uncategorized | No Comments

## Pooling data not possible: working on a fix

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

Category: R code | No Comments

## Dwelling time errors, prevents code from running

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

Category: R code | No Comments

## Statistical evaluation of OR

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

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?

Category: crosses, genetics, Lab, Optomotor response, R code | No Comments

## Making sense of dwelling data

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

#### Mean or median?

Unpunished | Punished | |

100 | 1 | |

1 | 3 | |

1,2 | 1 | |

0,5 | 2 | |

0,3 | 5 | |

5 | ||

Mean | 18 | 2,4 |

Median | 1,1 | 2 |

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

#### Grouped analysis of dwelling times

#### Cumming estimation plot

Category: flight, Memory, Operant learning, operant self-learning, R code | No Comments