rglab/hipccyto repository overview

⁠HIPCCyto

The goal of HIPCCyto is to standardize and pre-process flow cytrometry data of HIPC⁠ studies from ImmPort⁠.

⁠Local installation

You can install the development version of HIPCCyto from GitHub⁠ with:

install.packages("remotes")
remotes::install_github("RGLab/HIPCCyto")

You also need to register at ImmPort and install the Aspera CLI. Please follow the instructions here⁠.

⁠Docker

There are many dependencies in HIPCCyto, so it takes a long time to install them all. Instead, you can use the Docker image of HIPCCyto.

docker pull rglab/hipccyto:latest
docker run \
    -it \
    --user rstudio \
    --volume <yourLocalDirectory>:/home/rstudio \
    --env ImmPortUsername=<yourImmPortUsername> \
    --env ImmPortPassword=<yourImmPortPassword> \
    rglab/hipccyto:latest \
    R

Replace <yourLocalDirectory> with the local directory path where you'd like to store the gating sets and <yourImmPortUsername> and <yourImmPortPassword> with your Immport credential. For more information on using docker containers, please read this documentation⁠ by Bioconductor.

⁠Usage

⁠Retrieve FCS files from ImmPort

library(HIPCCyto)
file_dir <- fetch_files(study = "SDY820", output_dir = "~/")

⁠Process study

gsl <- process_study(study = "SDY820", input_dir = file_dir)

process_study function standradizes and pre-processes FCS files into gating sets.

1. Standardize marker names using ImmPort's fcs_header_marker table.
2. Merge metadata and batch information if available.
3. Compensate using the embeded spillover matrix in FCS files.
4. Transform the fluorescence channels using the inverse hyperbolic sine transformation with cofactor = 150 (Weber & Robinson, 2016⁠).
5. Pre-gate up to "Lymphocytes" using various automatic gating methods.

⁠Save gating sets

save_gating_sets(gsl = gsl, output_dir = file_dir)