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Rauf Salamzade edited this page Aug 12, 2024
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lsaBGC-Pan puts together some programs from the original suite (e.g. lsaBGC-Cluster, lsaBGC-See, lsaBGC-ComprehenSeeIve, and GSeeF) and some new programs (e.g. zol, lsaBGC-Reconcile [an updated version of lsaBGC-Divergence], and lsaBGC-Sociate). lsaBGC-Pan works on both bacterial and fungal genomes and can jointly process both antiSMASH and GECCO BGC predictions. In summary, lsaBGC-Pan is a newer and recommended workflow to the previously available lsaBGC-Easy.py and lsaBGC-EukEasy.py workflows. We plan to continue development of this workflow but maintain support for lsaBGC-Easy.py and lsaBGC-EukEasy.py.
- overview of lsaBGC-Pan
- comparison of workflows: what's different about lsaBGC-Pan compared to lsaBGC-(Euk)Easy.py
- installation guide
- tutorial on GECCO based analysis of BGCs from Cutibacterium avidum and Cutibacterium acnes
- tutorial on joint AntiSMASH & GECCO analysis of BGCs from Streptomyces olivaceus
- tutorial on AntiSMASH analysis of BGCs from Aspergillus flavus
- guide to parameter selections during mid-way break
- explanation of final spreadsheet and visual reports
- details on new modules: lsaBGC-Reconcile and lsaBGC-Sociate
Perform analysis using a directory of AntiSMASH results as input:
lsaBGC-Pan -a AntiSMASH_Results/ -o Pan_Results/ -c 10Provide a directory of AntiSMASH results as input and incorporate GECCO BGC predictions as well:
lsaBGC-Pan -a AntiSMASH_Results/ -o Pan_Results/ -c 10 -rgProvide a directory of genomes in FASTA format for GECCO-based BGC predictions and analysis (only works for bacteria):
lsaBGC-Pan -g Directory_of_Genomes_in_FASTA/ -o Pan_Results/ -c 10usage: lsaBGC-Pan [-h] [-a ANTISMASH_RESULTS_DIRECTORY] [-g GENOMES [GENOMES ...]] -o OUTPUT_DIRECTORY [-f] [-k] [-rg] [-up] [-omc] [-ohq] [-hqp] [-cs CORE_PROPORTION] [-mcs MAX_CORE_GENES]
[-pic POPULATION_IDENTITY_CUTOFF] [-mpf MANUAL_POPULATIONS_FILE] [-ci CLUSTER_INFLATION] [-cj CLUSTER_JACCARD] [-cr CLUSTER_SYNTENIC_CORRELATION] [-cc CLUSTER_CONTAINMENT] [-nb]
[-zp ZOL_PARAMETERS] [-zhq] [-zl] [-ed EDGE_DISTANCE] [-hqr] [-rsh] [-at ALIGNMENT_TIMEOUT] [-py] [-c THREADS]
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Program: lsaBGC-Pan
Author: Rauf Salamzade
Affiliation: Kalan Lab, UW Madison, Department of Medical Microbiology and Immunology
QUICK DESCRIPTION:
Workflow to run a pan-genome analysis of biosynthetic gene clusters for a single genus or species.
https://github.com/Kalan-Lab/lsaBGC-Pan/
**********************************************************************************************************
NOTES & CONSIDERATIONS:
* Check out the documentation at: https://github.com/Kalan-Lab/lsaBGC-Pan/wiki
* Either provide an antiSMASH results directory or a directory with genomes (not both!).
* lsaBGC-Pan does not have all the functionalities of the original lsaBGC suite to make things simpler
and more straightforward. In particular, lsaBGC-(Auto)Expansion, which helped with scalability is
discluded because its usage generally requires more careful consideration and manual curation. Thus, to
make sure your analysis runs in a relatively timely manner, the program is restricted to handling data
from 4-200 genomes.
- Consider using tools for dereplication/strain-clustering (such as skDER/CiDDER, dRep, PopPunk,
or treemmer) to prune down your set of genomes if you have more than 200.
* Panaroo should only be used if working with genomes belonging to a single bacterial species. If working
with multiple bacterial species or fungal genomes, please use OrthoFinder instead.
* Specifying fungal mode makes sure OrthoFinder is being used and that antiSMASH results were provided.
GECCO is not designed for fungal genomes. In addition, customized processing designed for bacterial
genomics is not performed and a more direct extraction of hierarchical orthogroups is applied.
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OVERVIEW OF WORKFLOW STEPS:
PART 1
----------------------------------------------------------------------------------------------------------
- Step 1: Assess inputs provided
- Step 1a: If genomes are provided, perform gene-calling with p(y)rodigal and annotate BGCs with GECCO
- Step 1b: If antiSMASH results are provided, extracted genes from full genome GenBank files. If GECCO
is requested, then it will also be run and overlapping GECCO and antiSMASH BGC regions will
be consolidated by taking
the larger region.
- Step 2: Run OrthoFinder/Panaroo for orthology inference.
- Step 3: Create species tree/phyogeny from (near-) core ortholog groups.
- Step 4: Infer populations (will do so at multiple "core AAI" cutoffs) [no checkpoint, always rerun].
- Step 5: Run lsaBGC-Cluster.py to determine evolutionary GCFs (by default in testing mode unless
--auto-cluster specified) [no checkpoint, always rerun].
BREAK (optional - but recommended - can be skipped by issuing --no-break)
----------------------------------------------------------------------------------------------------------
- Step 6a: Manually examine which parameters make the most sense for evolutionary clustering of GCFs.
Restart the workflow after with parameters for gene cluster clustering adapted.
- Step 6b: Manually assess how population designations structure along the species tree with different
core AAI cutoffs and, if desired, adjust population designations.
PART 2
----------------------------------------------------------------------------------------------------------
- Step 7: Parallel running of zol and cgc per GCF.
- Step 8: Parallel running of GSeeF, lsaBGC-See, and lsaBGC-ComprehenSeeIve per GCF.
- Step 9: Parallel running of lsaBGC-MIBiGMapper.
- Step 10: Run lsaBGC-Reconcile.
- Step 11: Run lsaBGC-Sociate.
- Step 12: Create consolidated report of zol, lsaBGC-MIBiGMapper, lsaBGC-Reconcile, and lsaBGC-Sociate
results [no checkpoint, always rerun].
**********************************************************************************************************
options:
-h, --help show this help message and exit
-a ANTISMASH_RESULTS_DIRECTORY, --antismash-results-directory ANTISMASH_RESULTS_DIRECTORY
A directory with subdirectories corresponding to antiSMASH results
per sample/genome [Optional].
-g GENOMES [GENOMES ...], --genomes GENOMES [GENOMES ...]
Paths to genomes or directories with genomes in FASTA format.
Will run GECCO for BGC-predictions [Optional].
-o OUTPUT_DIRECTORY, --output-directory OUTPUT_DIRECTORY
Parent output/workspace directory.
-f, --fungal Specify if input are from fungal genomes. Only possible
if antiSMASH results are provided.
-k, --keep-locus-tags
Keep original locus tags in antiSMASH GenBank files.
-rg, --run-gecco If antiSMASH results are provided also run GECCO for
annotation of BGCs.
-up, --use-panaroo Use Panaroo instead of OrthoFinder for orthology inference.
Recommended if investigating a single bacterial species.
-omc, --run-coarse-orthofinder
Use coarse clustering for orthogroups in OrthoFinder instead
of the more resolute hierarchical determined homolog groups.
There are some advantages to coarse OGs, including their
construction being deterministic.
-ohq, --run-msa-orthofinder
Run OrthoFinder using multiple sequence alignments instead of
DendroBlast to determine hierarchical ortholog groups.
-hqp, --high-quality-phylogeny
Prioritize quality over speed for phylogeny construction.
-cs CORE_PROPORTION, --core-proportion CORE_PROPORTION
What proportion of genomes single-copy orthogroups need to be
found in to be used for species tree construction [Default is 0.9].
-mcs MAX_CORE_GENES, --max-core-genes MAX_CORE_GENES
The maximum number of single copy (near-)core orthogroups to
use [Default is 500].
-pic POPULATION_IDENTITY_CUTOFF, --population-identity-cutoff POPULATION_IDENTITY_CUTOFF
The core-genome identity cutoff used to define pairs of genomes as
belonging to the same group/population [Default is 99.0].
-mpf MANUAL_POPULATIONS_FILE, --manual-populations-file MANUAL_POPULATIONS_FILE
Tab delimited file for manual mapping of samples to different
populations/clades.
-ci CLUSTER_INFLATION, --cluster-inflation CLUSTER_INFLATION
The MCL inflation parameter for clustering BGCs into GCFs [Default
is 0.8].
-cj CLUSTER_JACCARD, --cluster-jaccard CLUSTER_JACCARD
Cutoff for Jaccard similarity of homolog groups shared between two
BGCs [Default is 50.0].
-cr CLUSTER_SYNTENIC_CORRELATION, --cluster-syntenic-correlation CLUSTER_SYNTENIC_CORRELATION
The minimal correlation coefficient needed between for considering them
as a pair prior to MCL [Default is 0.4].
-cc CLUSTER_CONTAINMENT, --cluster-containment CLUSTER_CONTAINMENT
Cutoff for percentage of OGs for a gene cluster near a contig edge
to be found within the comparing gene cluster for the pair to be
considered in MCL (a minimum of 3 OGs shared are still required) [Default
is 70.0]
-nb, --no-break No break after step 5 to assess GCF clustering and population
stratification and adapt parameters.
-zp ZOL_PARAMETERS, --zol-parameters ZOL_PARAMETERS
The parameters to run zol analyses with - please surround by quotes
[Defaut is ""].
-zhq, --zol-high-quality-preset
Use preset of options for performing high-quality and comprehensive zol
analyses instead of prioritizing speed.
-zl, --zol-keep-multi-copy
Include all GCF instances in zol analysis, not just the most
representative instance from each sample/genome.
-ed EDGE_DISTANCE, --edge-distance EDGE_DISTANCE
Distance in bp to scaffold/contig edge to be considered potentially
fragmented. Used in GCF clustering (related to --cluster-containment
parameter) and zol conservation computations [Default is 5000].
-hqr, --high-quality-reconcile
Perform high-quality alignment for reconcile analysis.
-rsh, --report-sociate-hits
Report signficant pyseer hits with 'notes' - usually
indicate some general issue - should be examined with caution:
https://pyseer.readthedocs.io/en/master/usage.html#notes-field.
-at ALIGNMENT_TIMEOUT, --alignment-timeout ALIGNMENT_TIMEOUT
The timeout in seconds for constructing proteins alignments using
MUSCLE during lsaBGC-Reconcile and lsaBGC-Sociate - to prevent long
runs due to stragglers/abnormally large orthogroups [Default is
1800 (30 minutes)].
-py, --use-prodigal Use prodigal instead of pyrodigal (only if genomes are provided - not
relevant if antiSMASH results provided).
-c THREADS, --threads THREADS
Total number of threads/processes to use. Recommend inreasing as much
as possible. [Default is 4].