ArticlePLoS computational biology2024
FindAdapt: A python package for fast and accurate adapter detection in small RNA sequencing.
Article in PLoS computational biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 6 citations in OpenAlex.
- PCsRNAdb: a comprehensive resource of small noncoding RNAs across cancers.Nucleic acids research · 2026Article
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- Evolutionarily New Solanaceous DCL2 Family Members Acquire Functions in Tomato.Molecular plant pathology · 2025Article
- Organism-Specific Sequence Motifs Link Ribosomal RNAs to Brain Disorders.Molecular biology and evolution · 2025Article
- IsomiRome analysis reveals dysregulation of 5' isomiRs during SARS-CoV-2 infection.Computational and structural biotechnology journal · 2025Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Adapter trimming is an essential step for analyzing small RNA sequencing data, where reads are generally longer than target RNAs ranging from 18 to 30 bp. Most adapter trimming tools require adapter information as input. However, adapter information is hard to access, specified incorrectly, or not provided with publicly available datasets, hampering their reproducibility and reusability. Manual identification of adapter patterns from raw reads is labor-intensive and error-prone. Moreover, the use of randomized adapters to reduce ligation biases during library preparation makes adapter detection even more challenging. Here, we present FindAdapt, a Python package for fast and accurate detection of adapter patterns without relying on prior information. We demonstrated that FindAdapt was far superior to existing approaches. It identified adapters successfully in 180 simulation datasets with diverse read structures and 3,184 real datasets covering a variety of commercial and customized small RNA library preparation kits. FindAdapt is stand-alone software that can be easily integrated into small RNA sequencing analysis pipelines.
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Registered trials
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