HAYSTAC documentation
- Introduction
- Installation
- Workflow
- Outputs
- Tutorial
- Configuring HAYSTAC
- Building the database
- Constructing the Query
- Representative RefSeq species
- Important note on RefSeq databases
- Providing custom accessions
- Providing custom sequences
- Combinations
- Index building
- Database building modes
- Building a mitochondrial DNA database
- Preparing a sample for analysis
- Sample analysis
- Filtering Alignment
- Database Alignments
- Likelihood calculation
- Important Note on the Dirichlet Assignment process during Likelihood calculation
- Single organism sample or metagenome ?
- Assignment Probability Calculation
- Mean Posterior Abundances
- Reads
- Mapdamage analysis
- Important note on sample analysis
- Command Line Interface
- Developer documentation
- FAQs
- Tracking issues and bugs
Citations
A preprint describing haystac
is available on bioRxiv:
Dimopoulos, E.A.*, Carmagnini, A.*, Velsko, I.M., Warinner, C., Larson, G., Frantz, L.A.F., Irving-Pease, E.K., 2020. HAYSTAC: A Bayesian framework for robust and rapid species identification in high-throughput sequencing data. bioRxiv 2020.12.16.419085. https://www.biorxiv.org/content/10.1101/2020.12.16.419085v1
Contributing
Evangelos Antonios Dimopoulos, Evan K. Irving-Pease, Alberto Carmagnini
License
MIT