FHiTINGS
FHiTINGS processes fungal internal transcribed spacer (ITS) next-generation sequencing (NGS) data to assign taxonomic identifications and summarize biodiversity metrics.
Key Features:
- Integration with BLASTn: Consumes BLASTn output to identify and parse ITS sequences using sequence alignment results.
- Lowest Common Ancestor (LCA) Approach: Implements the LCA algorithm to assign a single taxonomic identification per sequence based on BLASTn hits.
- Taxonomic Classification: Assigns taxonomic ranks from species to kingdom using Index Fungorum as the reference database.
- Data Summarization and Sorting: Generates tabular summaries of sequence data enabling calculation of sample diversity metrics such as α-diversity and richness.
- Efficiency and Consistency: In silico testing reported reduction of analysis time for 1,000 sequences from over two hours (manual sorting) to under one minute computationally while maintaining consistency with manual classifications.
Scientific Applications:
- Fungal ecology and biodiversity: Enables analysis of species diversity and community composition from ITS NGS datasets to support biodiversity and ecosystem dynamics studies.
- Sequencing platform compatibility: Applicable to ITS datasets generated by sequencing platforms including 454 pyrosequencing for taxonomic profiling and diversity assessment.
Methodology:
Processes BLASTn output, applies the Lowest Common Ancestor (LCA) method to BLAST results, assigns taxonomic ranks using Index Fungorum, and summarizes results into tabular format to enable calculation of α-diversity and richness.
Topics
Details
- Maturity:
- Mature
- Tool Type:
- command-line tool
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- Python
- Added:
- 1/13/2017
- Last Updated:
- 11/25/2024
Operations
Publications
Dannemiller KC, Reeves D, Bibby K, Yamamoto N, Peccia J. Fungal High‐throughput Taxonomic Identification tool for use with Next‐Generation Sequencing (FHiTINGS). Journal of Basic Microbiology. 2013;54(4):315-321. doi:10.1002/jobm.201200507. PMID:23765392.
PMID: 23765392