PALADIN
PALADIN maps DNA sequencing reads directly in protein space to enable rapid and accurate functional profiling of metagenomic samples.
Key Features:
- Direct Protein Space Mapping: Maps DNA reads directly within protein space rather than performing nucleotide alignment followed by translation, allowing direct alignment to protein references.
- Efficiency and Speed: Outperformed nucleotide mappers BWA and NovoAlign on simulated reads by detecting more proteins, yielding higher percentages of mapped reads and maintaining ontological similarity, and in empirical comparisons achieved results seven times faster than DIAMOND and nearly 8,000 times faster than BLASTX.
- Accuracy: Maintains accuracy levels comparable to the tested nucleotide and protein alignment tools, supporting reliable functional profiling.
- Robust Reporting Capabilities: Produces reporting outputs to support comprehensive analysis and interpretation of metagenomic functional profiles.
Scientific Applications:
- Microbial ecology: Enables functional profiling to investigate metabolic pathways and ecological roles of microorganisms within communities.
- Environmental microbiology: Supports rapid alignment of DNA reads to protein references for profiling environmental microbial communities.
- Functional profiling of complex microbial communities: Facilitates detailed characterization of gene function and metabolic potential in large-scale metagenomic datasets.
Methodology:
Built upon a novel modification of the Burrows-Wheeler Aligner (BWA) tailored for direct mapping in protein space and implemented in C, enabling orders-of-magnitude improvements in efficiency.
Topics
Details
- Tool Type:
- command-line tool
- Operating Systems:
- Linux, Mac
- Programming Languages:
- Python
- Added:
- 6/5/2018
- Last Updated:
- 11/25/2024
Operations
Publications
Westbrook A, Ramsdell J, Schuelke T, Normington L, Bergeron RD, Thomas WK, MacManes MD. PALADIN: protein alignment for functional profiling whole metagenome shotgun data. Bioinformatics. 2017;33(10):1473-1478. doi:10.1093/bioinformatics/btx021. PMID:28158639. PMCID:PMC5423455.
PMID: 28158639
PMCID: PMC5423455
Funding: - National Science Foundation: 1455957, 1638296
- Gulf of Mexico Research Initiative: SA-1618