2 releases

0.1.3 Mar 14, 2023
0.1.2 Feb 13, 2023
0.1.0 Jan 30, 2023
0.0.11 Dec 9, 2022
0.0.4 Jul 31, 2022

#1410 in Command line utilities

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MIT license

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fibertools-rs

fibertools-rs dark logo fibertools-rs light logo

Actions Status Conda (channel only) Downloads crates.io version crates.io downloads DOI

fibertools-rs a CLI tool for creating and interacting with fiberseq bam files.

Install Conda (channel only)

fibertools-rs is avalible through bioconda and can be installed with the following command:

mamba install -c conda-forge -c bioconda fibertools-rs

Other installation methods are available in the INSTALL.md file.

Usage

ft --help

Help page for fibertools

Subcommands for fibertools-rs

ft predict-m6a

Help page for predict-m6a. Predict m6A positions using HiFi kinetics data and encode the results in the MM and ML bam tags.

Adding nucleosome calls to the BAM files

To add nucleosome calls to the BAM files you can use the python package fibertools. See that repository for installation and instructions.

ft extract

Help page for extract. Extracts fiberseq data from a bam file into plain text.

ft extract --all

The extract all option is a special option that tries to extract all the fiberseq data into a tabular format. The following is an image of the output. Note that the column names will be preserved across different software versions (unless otherwise noted); however, the order may change and new columns may be added. Therefore, when loading the data (with pandas e.g.) be sure to use the column names as opposed to indexes for manipulation. ft-extract all

ft center

Help page for center. Center fiberseq reads (bam) around reference position(s). Center

Read the fibertools docs

You can find the docs for the latest release here: https://docs.rs/fibertools-rs/latest/fibertools_rs/ or download from source and run:

cargo doc --open

and the docs will open in your browser.

TODO items

  • Use new iterator for ft extract and group writes to try and improve the speed
  • Set filters for ML depending on the model used
  • long format extract command
  • Add rustybam stats to ft all as an option
  • add option result to bamlift
  • Add more test cases, learn about test modules in folders
  • Test GPU support, see if I can simplify or statically link PyTorch.
  • Improve progress bar for predict-m6a.
    • Get size of bam, say how far we are through the bam in terms of MB/GB?
  • Add unaligned, secondary, supplemental reads to the test bam.
  • Detect GPU memory to set batch size dynamically.

Dependencies

~41MB
~879K SLoC