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CleanBSequences: an efficient curator of biological sequences in R
Florencia I Pozzi1,2, Gisela Y Green3, Ivana G Barbona4
1Instituto de Tecnología Agropecuaria, EEA Marcos Juárez, Ruta 12 km. 3, 2580, Marcos Juárez, Córdoba, Argentina. pozzi@iicar-conicet.gob.ar.
Molecular Genetics and Genomics : MGG
|April 18, 2020
Summary
Researchers can now automate sequence curation for molecular markers like AFLP, cDNA-AFLP, and MSAP. The CleanBSequences R package efficiently removes unwanted adaptor sequences, saving time and reducing errors in omics studies.
Area of Science:
- Molecular Biology
- Genetics
- Bioinformatics
Background:
- Omics studies frequently utilize molecular markers such as Amplified Fragment Length Polymorphism (AFLP), complementary DNA-AFLP (cDNA-AFLP), and Methylation Sensitive Amplification Polymorphism (MSAP).
- These markers generate data at the genomics, transcriptomics, and epigenomics levels, respectively.
- A critical step in analyzing data from these markers involves removing adaptor sequences used in Polymerase Chain Reaction (PCR) amplification.
Purpose of the Study:
- To develop an automated method for curating molecular marker sequences.
- To address the time-consuming and error-prone manual process of removing adaptor sequences.
- To introduce a user-friendly, offline R package for efficient sequence data cleaning.
Main Methods:
- Development of an R package named CleanBSequences.
- Implementation of sequence curation through alignment of primers or cloning vector ends.
- Generation of new subsequences by removing unwanted biological fragments, including adaptors.
Main Results:
- CleanBSequences automates the massive, rapid, and error-free curation of molecular marker sequences.
- The tool effectively removes adaptor sequences and other unwanted fragments.
- The R package functions offline, enhancing accessibility for researchers.
Conclusions:
- The CleanBSequences tool significantly reduces the time and effort required for sequence curation in molecular biology and genetics research.
- This open-source package offers a flexible solution to common problems in omics data processing.
- CleanBSequences has the potential for future enhancements to address evolving research needs.
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