sgosline/imm-classifier repository overview

⁠ImmClassifier

Update: March 10, 2020

Knowledge-based and lineage-driven immune cell classification in single-cell RNA-Seq data

Maintainer: Xuan Liu [email protected]⁠ Sara Gosline [email protected]⁠

⁠Description

ImmClassifier (Immune cell classifier), a knowledge-based and lineage-driven immune cell classification algorithm with fine annotation granularity yet high prediction accuracy. ImmClassifer seamlessly integrates the biology of immune cell differentiation, the strength of heterogeneous reference datasets and the state-of-art machine learning models. ImmClassifier cascades a machine learning module and a deep learning module.

⁠Install

We have provided a Docker container that includes ImmClassifier and all its dependencies. To get the container, you must have Docker installed and use this command:

docker pull sgosline/imm-classifier

Alternatively, you can also build locally and install from the GitHub source. To do this, you must have both git and Docker installed and then run the commands:

git clone https://github.com/sgosline/ImmClassifier.git

cd ImmClassifier

docker build . -t imm-classifier

⁠Prerequisites

All pre-requisites are in the Docker image. We recommend using this image instead of installing locally.

⁠Usage Examples

ImmClassifier runs a series of three individual commands using both R and Python. It requires two parameters:

• the input file
• the output prefix

⁠Input File

This file is a matrix of gene counts where the rows represent gene names with the HUGO identifiers and the columns represent individual cells.

An example file is at: https://github.com/sgosline/ImmClassifier/blob/master/test/bulk.logrma.txt⁠

⁠Output File

This file is a matrix of cell type predictions for each cell.

The output for the exmple above is at: https://github.com/sgosline/ImmClassifier/blob/master/output/bulk.output.txt⁠

⁠To run

To run the command you must provide the path to your input file, the output prefix and mount the /tmp directory to get the output files.

docker run --volume $PWD:/tmp -ti sgosline/imm-classifier --input `input_file` --output `output_prefix`

input_file is the name of input file. It needs to be in the local directory for docker to find it. If you are a docker expert, you may specify files in other directories, but you will need to bind the directory using the docker --volume command.

The output files will be written to your local directory with the prefix specified by the output_prefix argument. ImmClassifier will generate three files:

• output_prefix.dnn.input.txt
• output_prefix.deeplearning.ontotree.stats.txt
• output_prefix.output.txt

The output_prefix.output.txt file contains the final predictions. The other files contain intermediate results.