Eimeria_Lab repository

This repository is for the storage of data from experiments conducted in the research group of Emanuel Heitlinger.

data_products

This older contains cleaned data sets (more or less, discuss, e.g. in issues!) ready for use data sets for analyses.

data_products/Challenge_infections.csv

Contains data for challenge (repeated) infections performed between 2017 and 2019. It is generated by the script Challenge.R. The data product is structure in the following columns:

• EH_ID: the unique identifier of the mouse
• experiment: the experiment as numbered in the overview table
• mouse_strain: the strain (inbred or outbred) of the mouse
• primary_infection: The Eimeria strain used for the primary infection
• challenge_infection: The Eimeria strain used for the challenge infection
• infection_history: The resulting infection history
• labels: the unique label of the fecal sample at a particular dpi
• weight: the weight of the mouse at this dpi
• weight_dpi0: the weight at the day of infection
• relative_weight: the weight of the mouse at this dpi relative to the weight at dpi0
• feces_weight: the weight of the feces collected at this dpi
• dpi: days post infection at which samples and data in this row were taken
• infection: the infection (primary or challenge) this row/dpi corresponds to
• oocyst_sq1, oocyst_sq2, oocyst_sq3, oocyst_sq4: the raw values for squared during oocyst counting
• dilution: the amount of PBS the feces (with it's relative weight) was dissolved in
• OO4sq: the sum of oocysts in the four counting squares
• OOC: the overall number of oocysts in in the feces (of a particular weight) at this dpi
• OPG_O: Old way of counting opg (Emanuel ask me)
• infection_type: what kind of infection are we looking at (challenge or primary, homologous or heterologous immunization). This is differently coded to infection, as here UNI:E88 (first uninfected, then infected with E88) would count as a "primaryE88" infection

The next values max_dpi until maximum_weight are calculated for the infection type in which the mice died

• max_dpi = maximum dpi that the mouse that the mouse reached for each infection challenge or primary (group_by EH_ID and infection (primary/challenge) to get the value

• maximum oocysts for each infection type (group_by EH_ID and infection (primary/challenge) to get the value)

• maximum weight loss for each infection type (group_by EH_ID and infection (primary/challenge) to get the value)

• death = challenge/primary (in which infection did the mouse die

• Eim_MC = Melting curve for eimeria

• delta = delta ct value

• Gene expression columns:

  • CXCR3
  • IRG6
  • IL.12

• Sex: sex of the mouse

Mouse_strains: (hybrid status)

• BUSNA_STRA: inter subsp. hybrids
• STRA_BUSNA: inter subsp. hybrids
• SCHUNT_SCHUNT: parental strains
• PWD_SCHUNT: inter subsp. hybrids
• STRA_STRA: parental strains
• STRA_SCHUNT: outbred hybrids
• PWD_BUSNA: outbred hybrids
• BUSNA_PWD: outbred hybrids
• PWD_PWD: parental strains
• SCHUNT_PWD: inter subsp. hybrids
• SCHUNT_STRA: outbred hybrids
• STRA_SCHUNT: outbred hybrids

In order to summarize data by mouse and infection you will use code similar to the below in your analysis.

as_tibble(CI) %>%
    group_by(EH_ID, infection) %>%
    summarize(max_OOC = max(OOC, na.rm=TRUE),
              max_WL = min(relative_weight, na.rm=TRUE),
              experiment = unique(experiment),
              mouse_strain= unique(mouse_strain),
              primary_infection=unique(primary_infection),
              challenge_infection=unique(challenge_infection),
              infection_history=unique(infection_history),
              infection_type=unique(infection_type),
              experiment=unique(experiment)) ->
    CIMouse

Accessing raw data (and compiling it into data_products)

Pointers to clean and standardized raw data are given in the overview table. This can be used to compile the latest raw data into data_products. An example of how this can be done is available in Challenge.R

data

Contains somewhat cleaned (but still "raw") data generated during our experiments. The most relevant of these raw data sets are indicated in the overview tables as explained above for further compilation into data products.

Experimental_design

Mouse information sheets containing attributes such as: sex, strain, date of birth, EH_ID (unique identifier) and infection strain.

Experiment_results

Clean tables of results obtained from a given experiment and assay/observation