ArticleGenome biology2019
Afann: bias adjustment for alignment-free sequence comparison based on sequencing data using neural network regression.
Article in Genome biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- DipSkmer: Reference-free population genomics with diploid genome skims.bioRxiv : the preprint server for biology · 2026Article
- ReSkmer: modeling repeats allows k-mer-based alignment-free methods to calculate population genomic distances.Genome biology · 2026Article
- Machine Learning Enables Alignment-Free Distance Calculation and Phylogenetic Placement Using k-Mer Frequencies.Molecular ecology resources · 2025Article
- Rapid species-level metagenome profiling and containment estimation with sylph.Nature biotechnology · 2025Article
- Fast and robust metagenomic sequence comparison through sparse chaining with skani.Nature methods · 2023Article
- Quantifying the uncertainty of assembly-free genome-wide distance estimates and phylogenetic relationships using subsampling.Cell systems · 2022Article
- Development of an Artificial Neural Network for the Detection of Supporting Hindlimb Lameness: A Pilot Study in Working Dogs.Animals : an open access journal from MDPI · 2022Article
- Phage-bacterial contig association prediction with a convolutional neural network.Bioinformatics (Oxford, England) · 2022Article
- Genome-wide alignment-free phylogenetic distance estimation under a no strand-bias model.Bioinformatics advances · 2022Article
- CONSULT: accurate contamination removal using locality-sensitive hashing.NAR genomics and bioinformatics · 2021Article
- Phylogenetic double placement of mixed samples.Bioinformatics (Oxford, England) · 2020Article
- Beyond DNA barcoding: The unrealized potential of genome skim data in sample identification.Molecular ecology · 2020Article
- KITSUNE: A Tool for Identifying Empirically Optimal K-mer Length for Alignment-Free Phylogenomic Analysis.Frontiers in bioengineering and biotechnology · 2020Article
- Afann: bias adjustment for alignment-free sequence comparison based on sequencing data using neural network regression.Genome biology · 2019Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Alignment-free methods, more time and memory efficient than alignment-based methods, have been widely used for comparing genome sequences or raw sequencing samples without assembly. However, in this study, we show that alignment-free dissimilarity calculated based on sequencing samples can be overestimated compared with the dissimilarity calculated based on their genomes, and this bias can significantly decrease the performance of the alignment-free analysis. Here, we introduce a new alignment-free tool, Alignment-Free methods Adjusted by Neural Network (Afann) that successfully adjusts this bias and achieves excellent performance on various independent datasets. Afann is freely available at https://github.com/GeniusTang/Afann.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.