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Imaris-3D-LN-stats

DOI

Description

To streamline the image analysis of cleared lymph nodes, we provide an R workflow that rapidly consolidates all Imaris statistics from a single segmented surface (eg Germinal centers, Follicular T cells, Plasma cells) from the same image. We also provide the code to combine the statistics from the same surface across different images into a unified data frame, including a unique identifier column for each image.

Dependencies

Requires manual installation of R >= 3.6.0 from source.

Installation of the required R packages are automated within the script, including dplyr and stringr.

Configurations

Inputs

Please see an example of input.csv below. The configuration will be loaded as a dataframe with 2 columns, where the first column contains the Sample_ID and the second corresponds to the Directory (folder) path for all IMARIS statistics in .csv format.

Example input.csv :

Sample_ID Directory
Lymph_node_1 ./test/Lymph_node_1/GCs_Statistics/
Lymph_node_2 ./test/Lymph_node_2/GCs_Statistics/
Lymph_node_3 ./test/Lymph_node_3/GCs_Statistics/

Running the compiler

Clone this repository and cd into it :

git clone https://github.com/FrancisCrickInstitute/Imaris-3D-LN-stats
cd ./Imaris-3D-LN-stats

To compile the csv files, specify the following arguments and execute our compiler script:

/path/to/Rscript compiler.R <input_csv_path> <output_csv_path> <column_to_merge1 (optional)> <column_to_merge2 (optional)> ...

<input_csv_path> = Required; full or relative path of the input csv file
<output_csv_path> = Required; full or relative path of the output csv file
<column_to_merge> = Optional; additional columns in IMARIS csv outputs to merge. The columns must be present in all samples.

Example

Here we will run the compiler using our example data, merging on the Classification column across all csv files (example) for each sample.

git clone https://github.com/FrancisCrickInstitute/Imaris-3D-LN-stats
cd ./Imaris-3D-LN-stats

Rscript ./compiler.R ./input.csv ./3D_LN_stats_v0.0.0.csv "Classification" 

License

This project is licensed under the MIT License - see the LICENSE file for details.

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