recipe fba

Tools for single-cell feature barcoding analysis. Citation: Duan, et al (2021) <doi:10.1093/bioinformatics/btab375>.

Homepage:

https://github.com/jlduan/fba

Documentation:

https://jlduan.github.io/fba

License:

MIT

Recipe:

/fba/meta.yaml

'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.'

package fba

Versions:

0.0.13-0,  0.0.12-0,  0.0.11-0,  0.0.10.post1-0

Depends:

• dnaio >=0.10.0

• hdbscan >=0.8.21

• matplotlib-base >=3.3

• numpy >=1.19.0

• pandas >=1.0.0

• polyleven >=0.5

• pyclustering >=0.10.1

• pysam >=0.14.0

• python >=3.6

• regex

• scikit-learn >=0.23.0

• scipy >=1.5.0

• seaborn >=0.10.0

• statsmodels >=0.11.1

• umap-learn

• umi_tools >=1.0.0

Required By:

Installation

With an activated Bioconda channel (see set-up-channels), install with:

conda install fba

and update with:

conda update fba

or use the docker container:

docker pull quay.io/biocontainers/fba:<tag>

(see fba/tags for valid values for <tag>)

Download stats

Link to this page

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