Afann
Afann (Alignment-Free methods Adjusted by Neural Network) is a software tool that improves the accuracy of alignment-free methods for comparing genome sequences or raw sequencing samples without assembly. Alignment-free methods are faster and more memory-efficient than alignment-based methods. Still, they can overestimate the dissimilarity between sequencing samples and the dissimilarity calculated based on their genomes. This bias can significantly decrease the performance of the alignment-free analysis. Afann addresses this issue by using a neural network to adjust the bias, improving performance on various independent datasets.
Topic
Machine learning;Sequencing;Sequence assembly
Detail
Operation: Standardisation and normalisation;k-mer counting;Regression analysis
Software interface: Command-line user interface
Language: C++,Python
License: Other
Cost: Free fo available for academic or non-commercial purposes only.
Version name: v1.0.0
Credit: US National Science Foundation, National Institutes of Health.
Input: -
Output: -
Contact: Fengzhu Sun fsun@usc.edu
Collection: -
Maturity: -
Publications
- Afann: bias adjustment for alignment-free sequence comparison based on sequencing data using neural network regression.
- Tang K, et al. Afann: bias adjustment for alignment-free sequence comparison based on sequencing data using neural network regression. Afann: bias adjustment for alignment-free sequence comparison based on sequencing data using neural network regression. 2019; 20:266. doi: 10.1186/s13059-019-1872-3
- https://doi.org/10.1186/S13059-019-1872-3
- PMID: 31801606
- PMC: PMC6891986
Download and documentation
Source: https://github.com/GeniusTang/Afann/releases/tag/v1.0.0
Documentation: https://github.com/GeniusTang/Afann/blob/master/README.md
Home page: https://github.com/GeniusTang/Afann
Links: https://github.com/GeniusTang/Afann/blob/master/LICENSE.md
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