MACER
MACER assembles taxonomically and marker-focused molecular sequence datasets from online repositories (including NCBI GenBank) as an R package to support dataset curation for genomics, phylogenetics, and evolutionary biology.
Key Features:
- R package implementation: Implemented as an R package to script and reproduce dataset assembly workflows.
- Data Assembly: Automated acquisition, accumulation, and organization of sequence data from online molecular repositories.
- Dereplication: Identification and removal of redundant or duplicate sequence entries to maintain dataset integrity.
- Cleaning: Processing of datasets to remove inconsistencies and prepare sequences for downstream analysis.
- Customization for specific applications: Construction of taxonomically and marker-targeted datasets based on user-defined criteria.
Scientific Applications:
- Genomics: Curation of sequence datasets for comparative and marker-based genomic analyses.
- Phylogenetics: Assembly of marker-specific and taxonomically focused sequence sets for phylogenetic inference.
- Evolutionary biology: Preparation of cleaned, non-redundant sequence datasets to support evolutionary analyses.
- Comparative studies: Generation of consistent datasets across projects to enable comparative molecular studies.
Methodology:
Automated access to online molecular sequence repositories (e.g., NCBI GenBank); targeted searching and downloading of sequences based on user-defined criteria; dereplication to remove duplicate sequences; and dataset cleaning to remove inconsistencies and prepare sequences for analysis.
Topics
Details
- License:
- GPL-2.0
- Cost:
- Free of charge
- Tool Type:
- library
- Operating Systems:
- Linux, Mac, Windows
- Programming Languages:
- R
- Added:
- 4/25/2022
- Last Updated:
- 4/25/2022
Operations
Publications
Young R, Gill R, Gillis D, Hanner R. Molecular Acquisition, Cleaning and Evaluation in R (MACER) - A tool to assemble molecular marker datasets from BOLD and GenBank. Biodiversity Data Journal. 2021;9. doi:10.3897/bdj.9.e71378. PMID:34594153. PMCID:PMC8443542.