DOKK / manpages / debian 12 / scoary / scoary.1.en
SCOARY(1) User Commands SCOARY(1)

scoary - pangenome-wide association studies

scoary [-h] [-t TRAITS] [-g GENES] [-n NEWICKTREE] [-s START_COL] [--delimiter DELIMITER] [-r RESTRICT_TO] [-o OUTDIR] [-u] [-p P_VALUE_CUTOFF [P_VALUE_CUTOFF ...]] [-c [{I,B,BH,PW,EPW,P} [{I,B,BH,PW,EPW,P} ...]]] [-m MAX_HITS] [--include_input_columns GRABCOLS] [-w] [--no-time] [-e PERMUTE] [--no_pairwise] [--collapse] [--threads THREADS] [--test] [--citation] [--version]

show this help message and exit

Input trait table (comma-separated-values). Trait presence is indicated by 1, trait absence by 0. Assumes strain names in the first column and trait names in the first row
Input gene presence/absence table (comma-separatedvalues) from ROARY. Strain names must be equal to those in the trait table
Supply a custom tree (Newick format) for phylogenetic analyses instead instead of calculating it internally.
On which column in the gene presence/absence file do individual strain info start. Default=15. (1-based indexing)
The delimiter between cells in the gene presence/absence and trait files, as well as the output file.
Use if you only want to analyze a subset of your strains. Scoary will read the provided comma-separated table of strains and restrict analyzes to these.

Directory to place output files. Default = .
This flag will cause Scoary to write the calculated UPGMA tree to a newick file
P-value cut-off / alpha level. For Fishers, Bonferronis, and Benjamini-Hochbergs tests, SCOARY will not report genes with higher p-values than this. For empirical p-values, this is treated as an alpha level instead. I.e. 0.02 will filter all genes except the lower and upper percentile from this test. Run with "-p 1.0" to report all genes. Accepts standard form (e.g. 1E-8). Provide a single value (applied to all) or exactly as many values as correction criteria and in corresponding order. (See example under correction). Default = 0.05
Apply the indicated filtration measure. Allowed values are I, B, BH, PW, EPW, P. I=Individual (naive) p-value. B=Bonferroni adjusted p-value. BH=BenjaminiHochberg adjusted p. PW=Best (lowest) pairwise comparison. EPW=Entire range of pairwise comparison p-values. P=Empirical p-value from permutations. You can enter as many correction criteria as you would like. These will be associated with the p_value_cutoffs you enter. For example "-c I EPW -p 0.1 0.05" will apply the following cutoffs: Naive p-value must be lower than 0.1 AND the entire range of pairwise comparison values are below 0.05 for this gene. Note that the empirical p-values should be interpreted at both tails. Therefore, running "-c P -p 0.05" will apply an alpha of 0.05 to the empirical (permuted) p-values, i.e. it will filter everything except the upper and lower 2.5 percent of the distribution. Default = Individual p-value. (I)
Maximum number of hits to report. SCOARY will only report the top max_hits results per trait
Grab columns from the input Roary file. and puts them in the output. Handles comma and ranges, e.g. --include_input_columns 4,6,8,16-23. The special keyword ALL will include all relevant input columns in the output
Use with -r if you want Scoary to create a new gene presence absence file from your reduced set of isolates. Note: Columns 1-14 (No. sequences, Avg group size nuc etc) in this file do not reflect the reduced dataset. These are taken from the full dataset.
Output file in the form TRAIT.results.csv, instead of TRAIT_TIMESTAMP.csv. When used with the -w argument will output a reduced gene matrix in the form gene_presence_absence_reduced.csv rather than gene_presence_absence_reduced_TIMESTAMP.csv

Perform N number of permutations of the significant results post-analysis. Each permutation will do a label switching of the phenotype and a new p-value is calculated according to this new dataset. After all N permutations are completed, the results are ordered in ascending order, and the percentile of the original result in the permuted p-value distribution is reported.
Do not perform pairwise comparisons. Inthis mode, Scoary will perform population structure-naive calculations only. (Fishers test, ORs etc). Useful for summary operations and exploring sets. (Genes unique in groups, intersections etc) but not causal analyses.
Add this to collapse correlated genes (genes that have identical distribution patterns in the sample) into merged units.

Number of threads to use. Default = 1
Run Scoary on the test set in exampledata, overriding all other parameters.
Show citation information, and exit.
Display Scoary version, and exit.

by Ola Brynildsrud (olbb@fhi.no)

This manpage was written by Andreas Tille for the Debian distribution and can be used for any other usage of the program.

January 2019 scoary 1.6.16