Skip to main content

eliminates chimeric reads by comparing the UMI sequences and finding any matches in the 5 prime or 3 prime UMIs and keeping the sequence that has the highest prevalence

Project description

Chimera_Buster

Overview

This package takes concensus fasta files from the MrHamer2.0 pipeline and eliminates chimeric reads by comparing the UMI sequences and finding any matches in the 5' or 3' UMIs and keeping the sequence that has the highest prevalence.


Installation

Requires python<=3.10

Quick Install

pip install Chimera_Buster

Manual Install

git clone https://github.com/JessicaA2019/Chimera_Buster.git 
cd Chimera_Buster
python setup.py install

Dependencies

Some dependencies currently do not install with Chimera_Buster. Please pip install the following dependencies:

  • edlib
  • pandas
  • multiprocessing
  • argparse

Usage

Chimera_Buster [options] {input_file_name} {input_prelim_name} {output_file_prefix}

Inputs

To run the pipeline the following input files are required:

Input Description
input_file_name Designates clusters_concesus.fasta file from the clustering_consensus folder to be filtered. This is required.
input_prelim_name Designates clusters_concesus.fasta file from the clustering folder to be filtered. This is required.
output_file_prefix Designates output file prefix. This is required.
The following input files are optional:
Arguement Function
------ ------
-h, --help Prints help message to terminal.
-m int, --mismatch int Designates the maximum number of mismatched/indel bases allowed when comparing UMIs. Default is 1.
-c True/False, --check_clusters True/False When set to true, chimeric reads are rechecked to account for any clustering issues earlier in the pipeline. WARNING: this part of the code is slow and is only recommended for low input samples. Default is False.

Outputs

The main output files created by the pipeline are:

Output Description
{output_file_prefix}_chimera_list.txt A list of all chimeric sample IDs.
{output_file_prefix}_nonchimera_list.txt A list of all nonchimeric sample IDs.
{output_file_prefix}_chimeras.csv A csv of the sample ID, UMI sequences, and cluster counts for each chimeric read.
{output_file_prefix}_non_chimeras.csv A csv of the sample ID, UMI sequences, and cluster counts for each nonchimeric read.

Help

For issues or bugs, please report them on the issues page.

License

MIT - Copyright (c) 2024 Jessica Lauren Albert

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

chimera_buster-1.2.1.tar.gz (9.0 kB view details)

Uploaded Source

Built Distribution

Chimera_Buster-1.2.1-py3-none-any.whl (8.2 kB view details)

Uploaded Python 3

File details

Details for the file chimera_buster-1.2.1.tar.gz.

File metadata

  • Download URL: chimera_buster-1.2.1.tar.gz
  • Upload date:
  • Size: 9.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.0 CPython/3.12.3

File hashes

Hashes for chimera_buster-1.2.1.tar.gz
Algorithm Hash digest
SHA256 14bb666e33db4618e841e635bf8ecfd166af2be49e8e333cf7e9576e619ccedf
MD5 61fbcea02d1bb8c79ef57bfce9097be7
BLAKE2b-256 60ad06137155902868da9c36d495d60b61b0452031f602e42ee29395ba554cb6

See more details on using hashes here.

File details

Details for the file Chimera_Buster-1.2.1-py3-none-any.whl.

File metadata

File hashes

Hashes for Chimera_Buster-1.2.1-py3-none-any.whl
Algorithm Hash digest
SHA256 fce3976e290da77c31773b06428bc2b373853d82fad5c9aa48c501d1e052f2ee
MD5 5e372e96612be60b4d294e45ab983a39
BLAKE2b-256 a6597eb47f8de4a952c6e8978622e089d79ac17934135eaca9e6027ae2458132

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page