Cash in on Expressed Barcode Tags (EBTs) from NGS Sequencing Data with Python

Cashier is a tool developed by Russell Durrett for the analysis and extraction of expressed barcode tags.

This python implementation offers the same flexibility and simple command line operation.

Like it's predecessor it is a wrapper for the tools cutadapt, fastx-toolkit, and starcode.

Dependencies

• cutadapt (sequence extraction)
• starcode (sequence clustering)
• fastx-toolkit (PHred score filtering)
• pear (paired end read merging)
• pysam (sam file convertion to fastq)

Recommended Installation Procedure

It's recommended to use conda to install and manage the dependencies for this package

conda env create -f https://raw.githubusercontent.com/brocklab/pycashier/main/environment.yml # or mamba env create -f ....
conda activate cashierenv
pycashier --help

Additionally you may install with pip. Though it will be up to you to ensure all the non-python dependencies are on the path and installed correctly.

pip install pycashier

Usage

Pycashier has one required argument which is the directory containing the fastq or sam files you wish to process.

conda activate cashierenv
pycashier ./fastqs

For additional parameters see pycashier -h.

As the files are processed two additional directories will be created pipeline and outs.

Currently all intermediary files generated as a result of the program will be found in pipeline.

While the final processed files will be found within the outs directory.

Merging Files

Pycashier can now take paired end reads and perform a merging of the reads to produce a fastq which can then be used with cashier's default feature.

pycashier ./fastqs -m

Processing Barcodes from 10X bam files

Pycashier can also extract gRNA barcodes along with 10X cell and umi barcodes.

Firstly we are only interested in the unmapped reads. From the cellranger bam output you would obtain these reads using samtools.

samtools view -f 4 possorted_genome_bam.bam > unmapped.sam

Then similar to normal barcode extraction you can pass a directory of these unmapped sam files to pycashier and extract barcodes. You can also still specify extraction parameters that will be passed to cutadapt as usual.

Note: The default parameters passed to cutadapt are unlinked adapters and minimum barcode length of 10 bp.

pycashier ./unmapped_sams -sc

When finished the outs directory will have a .tsv containing the following columns: Illumina Read Info, UMI Barcode, Cell Barcode, gRNA Barcode

Usage notes

Pycashier will NOT overwrite intermediary files. If there is an issue in the process, please delete either the pipeline directory or the requisite intermediary files for the sample you wish to reprocess. This will allow the user to place new fastqs within the source directory or a project folder without reprocessing all samples each time.

• Currently, pycashier expects to find .fastq.gz files when merging and .fastq files when extracting barcodes. This behavior may change in the future.
• If there are reads from multiple lanes they should first be concatenated with cat sample*R1*.fastq.gz > sample.R1.fastq.gz
• Naming conventions:
  • Sample names are extracted from files using the first string delimited with a period. Please take this into account when naming sam or fastq files.
  • Each processing step will append information to the input file name to indicate changes, again delimited with periods.