singlecell

Overview

This pipeline performs alignment free based quantification of drop-seq, 10X single-cell sequencing analysis using wither kallisto or salmon. Pseudoalignment is performed on the RNA reads, using kallisto or Alevin and the resulting data is quantitatively and qualitatively analysed.

The pipeline performs the following analyses: * Alignment using kallisto or alevin (part of salmon) * QC of reads using the scater package

Input files

The pipeline is ran using fastq files that follow the naming convention Read1: Name.fastq.1.gz and read2: Name.fastq.2.gz.

• a fastq file (paired end following the naming convention below)
• a GTF geneset

The default file format assumes the following convention: fastq.1.gz and fastq.2.gz for paired data, where fastq.1.gz contains UMI/cellular barcode data and fastq.2.gz contains sequencing reads. Chromium output is of the format: samplename_R1.fastq.gz and samplename_R2.fastq.gz so will require conversion to the default file format above.

Configuring the pipeline

[describe how to set config values]

Running the pipeline

To run the pipeline you will need to set up the cluster configuration according to the cluster documentation.

However the pipeline can also be run locally without the cluster using the commandline flag –no-cluster.

The following command will run the pipeline:

scflow singlecell make full -v5

Report generation

The pipeline also generates Rmarkdown reports by running the following command:

scflow singlecell make build_report -v5

output