SingleFlow

SingleFlow is a pipeline for analyzing scRNA-seq data built using the workflow management system Nextflow.

Installation

Dependencies

• Compiler Java 8
• Runtime Java 8 or later
• Nextflow

Install Nextflow

Nextflow can be downloaded through the following command

curl -fsSL get.nextflow.io | bash

and subsequently moved to a location in $PATH.

Nextflow can also be installed from Conda

conda install -c bioconda nextflow

Python and R packages

The Python and R packages required for the specific analysis being performed have to be installed. The environment used when developing SingleFlow can be found in the requirements file. To include glm-PCA in the anlaysis see https://github.com/willtownes/scrna2019.

Usage

$ nextflow run SingleFlow.nf --input <folder(s)>

Parameters

Mandatory arguments

• --input: Folder or comma-separated list of folders containing the scRNA-seq data for analysis

Optional arguments

• --outdir: Folder for the results of the anlalysis to be put in, default: 'results'.
• --colors: Comma-separated colors for use in plotting the results of the analysis.
• --custom_colors: Comma-separated colors for use when defining custom cell clusters.
• --ccc: Specify whether to perform cell cycle correction of the data set or not.
• --custom_clusters: Specify whether to define custom cell clusters or not
• --deg: Specify whether to perform differentially expressed gene analysis or not.
• --rna_velocity: Specify whether to embed RNA velocity or not, if yes input a .loom file similar to the output of velocyto.
• --phenograph_clusters: Specify whether to calculate and visualize Phenograph clusters or not.
• --gene_trends: Specify whether to calculate the gene trends.
• --gene_trends_late: If set, the gene trends will be calculated and clustered from the given pseudotime.
• --gene_expression: Specify a file with genes whose expression levels should be visualized.
• --glmpca: Use the glm-PCA method or the conventional normalization and subsequent PCA.
• --imputation: Specify which imputation method to use, default: 'MAGIC'.
• --exclude: Specify a file containing cells that should be excluded form the analysis.
• --degWin: Show the result of DEG analysis in the specified file.
• --factorAnalysis: File containing the factors used as input to the factor analysis.
• --help: Show helper menu.

Examples

If we have three samples we want to include in our analysis and they are placed in three separate folders 'Sample 14', 'Sample 15' and 'Sample 16', within a folder called 'Donor 2', we can include all these samples in our analysis by specifying the input as in the following example

$ nextflow run SingleFlow.nf --input "Donor 2/Sample 14,Donor 2/Sample 15,Donor 2/Sample 16"

SingleFlow will in the subsequent analysis recognize that these comma-separated folders contain data from different samples.

For a specific example of the application of SingleFlow to obtain new biological insight, see our preprint on NK cell differentiation. Some of the results of the analysis is available and can be explored at http://herknet.io/nk.

License

SingleFlow is released under the MIT license.