Information about sex, age, treatment, and animal ID

This dataset provides an example of the type of cell characteristics that you should be recording for your data. The dataset contains columns for the animal number, age, sex, the synapses being recorded from, and treatments applied. There is also a column for access, which is stored as a list.

The most important column is letter. This is a unique identifier that you will assign to each recording. The letter column will enable you to link all information relevant to the recording (evoked current data, spontaneous current data, animal data like age, sex, etc.) from different files.

You should import this .csv file using the import_cell_characteristics_df() function, which will format it in a format that makes it easy to merge with raw recording data in functions like make_normalized_EPSC_data(). This will enable you to analyze relationships between properties like age and current amplitude.

Format

A dataframe with 19 rows and 11 columns

letter

A character value that is a unique identifier for a single recording. Used to link data sets for evoked or spontaneous currents and cell-characteristics. Example: "A"

cell

A character or numeric value representing the cell. For example, use 3.1.1 for animal #3, slice #1, cell #1.

sex

A character value such as "Male" or "Female".

X

A numeric value representing the x-value of the cell's location in µm.

Y

A numeric value representing the y-value of the cell's location in µm.

age

A numeric value representing the animal's age. Can be any value as long as the time units are consistent throughout (e.g. don't mix up days and months when reporting animal ages). Do not use characters (e.g. avoid "P31" and use 31 instead).

animal

A numeric value representing the animal's ID or number.

synapses

A character value such as "Glutamate" or "GABA".

treatment

A character value such as "Control" or "HNMPA".

category

A numeric value representing the experiment type. Used to assign top-level groups for further analyses, with treatment as subgroups.

R_a

A list of values for the access resistance, which would have been monitored at several timepoints throughout the recording. See the section R_a formatting below.

See also

import_cell_characteristics_df() to import data like this from a .csv file.

make_interactive_summary_table() for a function which merges cell characteristics information with pruned evoked and spontaneous current data to create an interactive overview table of all recordings.

Examples

utils::read.csv(import_ext_data("sample_cell_characteristics.csv"))
#>    letter    cell    sex      X      Y age animal  synapses     treatment
#> 1      BN  25.1.2   Male 152.92 337.19  29   25.0 Glutamate       Control
#> 2      AZ  21.1.1 Female 352.62 331.74  32   21.0 Glutamate       Control
#> 3      AO  17.1.1   Male     NA     NA  39   17.0 Glutamate       Control
#> 4      BO  27.2.1   Male     NA     NA  32   27.0 Glutamate         HNMPA
#> 5      BT  30.2.1   Male 387.19 586.98  37   30.0 Glutamate         HNMPA
#> 6      CG  35.1.3 Female 164.18 366.52  36   35.0 Glutamate         HNMPA
#> 7       L 8.5.2.1   Male     NA     NA  38    8.5 Glutamate       Control
#> 8      CZ  41.2.2   Male 296.51 492.90  28   41.0 Glutamate         HNMPA
#> 9      FT  72.2.1 Female 153.33 337.18  39   72.0 Glutamate         HNMPA
#> 10     FX  74.1.2 Female 234.69 495.50  28   74.0 Glutamate           PPP
#> 11     GF  77.3.1 Female 217.23 323.55  36   77.0 Glutamate           PPP
#> 12     GI  81.1.1 Female 235.96 284.23  28   81.0 Glutamate           PPP
#> 13     GK  84.1.1   Male 248.74 574.44  35   84.0 Glutamate           PPP
#> 14     GR  90.3.1   Male 313.50 415.97  34   90.0 Glutamate           PPP
#> 15     GX  97.2.3   Male     NA     NA  33   97.0 Glutamate PPP_and_HNMPA
#> 16     HB 100.1.1   Male 133.20 590.25  39  100.0 Glutamate PPP_and_HNMPA
#> 17     HC 100.2.2   Male 172.54 576.26  39  100.0 Glutamate PPP_and_HNMPA
#> 18     HG 103.2.1 Female     NA     NA  34  103.0 Glutamate PPP_and_HNMPA
#> 19     HN 109.1.1   Male 288.97 400.18  38  109.0 Glutamate PPP_and_HNMPA
#> 20     AV  20.3.1 Female  55.10 248.80  31   20.0 Glutamate       Control
#>    category                                              R_a
#> 1         2                     1.6, 1.7, 1.7, 1.8, 1.8, 2.0
#> 2         2           2.5, 2.6, 2.6, 2.9, 2.6, 2.6, 2.6, 2.7
#> 3         2                     1.9, 1.9, 1.8, 1.9, 2.0, 3.0
#> 4         2                     1.7, 1.7, 1.7, 1.8, 1.7, 1.8
#> 5         2 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.8, 1.5, 1.5, 1.5
#> 6         2                     2.0, 2.1, 2.1, 2.2, 2.2, 2.2
#> 7         2                     1.4, 1.5, 1.5, 1.6, 1.6, 1.5
#> 8         2                     2.0, 2.0, 2.1, 2.2, 2.1, 2.1
#> 9         2                     1.5, 1.5, 1.6, 1.7, 1.9, 2.0
#> 10        2                     1.9, 1.8, 1.9, 2.1, 2.0, 2.3
#> 11        2                     1.6, 1.6, 1.7, 1.7, 1.8, 1.7
#> 12        2                     1.3, 1.3, 1.3, 1.3, 1.4, 1.4
#> 13        2                          2.2, 2.2, 2.2, 2.3, 2.5
#> 14        2                     1.3, 1.4, 1.5, 1.5, 1.6, 1.8
#> 15        2                     1.6, 1.6, 1.7, 1.7, 1.8, 1.7
#> 16        2                     2.2, 2.5, 2.5, 2.6, 2.6, 2.6
#> 17        2                1.4, 1.5, 1.6, 1.9, 1.8, 2.3, 2.0
#> 18        2                                                 
#> 19        2                     1.7, 1.7, 1.7, 1.7, 1.7, 1.7
#> 20        2                     1.6, 1.8, 1.8, 2.0, 2.0, 2.0