User Guide#


What is fba?#

fba is a flexible and streamlined toolbox for quality control, quantification, demultiplexing of various single-cell 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.

Workflow#

FBA workflow

The workflow of FBA: a flexible and streamlined package for single-cell feature barcoding assays.#

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 typically contains cell partitioning and UMI information, while 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, while 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 of extract or qc). Additional fragment filter/selection can be applied through -cb_seq and/or -fb_seq.

  • count: count UMIs per feature per cell (UMI deduplication), powered by UMI-tools (Smith, T., et al. 2017). The output of extract or filter is taken as input.

  • demultiplex: demultiplex cells based on the abundance of features (matrix generated by count as input).

  • qc: generate diagnostic information. If -1 is 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).