工欲善其事,必先利其器。—— 论语·卫灵公
fba
Tools for single-cell feature barcoding analysis
Jialei Duan, Gary C Hon, FBA: feature barcoding analysis for single cell RNA-Seq, Bioinformatics, Volume 37, Issue 22, 15 November 2021, Pages 4266–4268. DOI: https://doi.org/10.1093/bioinformatics/btab375. PMID: 33999185.
What is fba?
fba is a flexible and streamlined toolbox for quality control, quantification, demultiplexing of various feature barcoding assays. It can be applied to customized feature barcoding specifications, including different CRISPR constructs or targeted enriched transcripts. fba allows users to customize a wide range of parameters for the quantification and demultiplexing process. fba also has a user-friendly quality control module, which is helpful in troubleshooting feature barcoding experiments.
Installation
fba can be installed with pip:
pip install fba
Alternatively, you can install this package with conda:
conda install -c bioconda fba
Workflow Example
- CRISPR screening
- Cell surface protein labeling
- ECCITE-seq
- PHAGE-ATAC
- CellPlex
- Cell hashing
- MULTI-seq
- Targeted transcript enrichment
- Pseudo-bulk
Usage
$ fba
usage: fba [-h] ...
Tools for single-cell feature barcoding analysis
optional arguments:
-h, --help show this help message and exit
functions:
extract extract cell and feature barcodes
map map enriched transcripts
filter filter extracted barcodes
count count feature barcodes per cell
demultiplex demultiplex cells based on feature abundance
qc quality control of feature barcoding assay
kallisto_wrapper
deploy kallisto/bustools for feature barcoding
quantification
extract: extract cell and feature barcodes from paired fastq files. For single cell assays, read 1 usually contains cell partitioning and UMI information, and read 2 contains feature information.map: quantify enriched transcripts (through hybridization or PCR amplification) from parent single cell libraries. Read 1 contains cell partitioning and UMI information, and read 2 contains transcribed regions of enriched/targeted transcripts of interest. BWA (Li, H. 2013) or Bowtie2 (Langmead, B., et al. 2012) is used for read 2 alignment. The quantification (UMI deduplication) of enriched/targeted transcripts is powered by UMI-tools (Smith, T., et al. 2017).filter: filter extracted cell and feature barcodes (output ofextractorqc). Additional fragment filter/selection can be applied through-cb_seqand/or-fb_seq.count: count UMIs per feature per cell (UMI deduplication), powered by UMI-tools (Smith, T., et al. 2017). Take the output ofextractorfilteras input.demultiplex: demultiplex cells based on the abundance of features (matrix generated bycountas input).qc: generate diagnostic information. If-1is omitted, bulk mode is enabled and only read 2 will be analyzed.kallisto_wrapper: deploy kallisto/bustools for feature barcoding quantification (just a wrapper) (Bray, N.L., et al. 2016).
Metadata
Release files for fba 0.0.13
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| fba-0.0.13.tar.gz | 44.8 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| fba-0.0.13-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 88.0 kB
Release files / fba-0.0.13.tar.gz
| Download URL | fba-0.0.13.tar.gz |
|---|---|
| Size | 44.8 kB |
| Tags | Source |
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Release files / fba-0.0.13-py3-none-any.whl
| Download URL | fba-0.0.13-py3-none-any.whl |
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| Size | 43.2 kB |
| Tags | Python 3 |
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