HAYSTAC documentation

Contents:

• Introduction
• Installation
  • Install mamba
  • Install haystac
  • Git
• Workflow
• Outputs
  • Expected outputs for haystac database
  • Expected outputs for haystac sample
  • Expected outputs for haystac analyse
• 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
  • haystac config
  • haystac database
  • haystac sample
  • haystac analyse
• 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