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.
- 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
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
As the files are processed two additional directories will be created
Currently all intermediary files generated as a result of the program will be found in
While the final processed files will be found within the
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
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.gzfiles when merging and
.fastqfiles 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.