Provided by: seer_1.1.4-2build1_amd64
seer - sequence element enrichment analysis
Sequence Element Enrichment Analysis The .pheno file format is tab separated, two columns with sample name, one with phenotype. Phenotypes of only 0 or 1 will be treated as binary, any other value and the phenotype will be treated as quantitative. Therefore for missing phenotype values the sample should simply be excluded from this file.
Required options: -k [ --kmers ] arg dsm kmer output file -p [ --pheno ] arg .pheno metadata Covariate options: --struct arg mds values from kmds --covar_file arg file containing covariates --covar_list arg list of columns covariates to use. Format is 1,2q,3 (use q for quantitative) Performance options: --threads arg (=1) number of threads. Suggested: 4 Filtering options: --no_filtering turn off all filtering and peform tests on all kmers input --max_length arg (=100) maximum kmer length --maf arg (=0.01) minimum kmer frequency --min_words arg minimum kmer occurrences. Overrides --maf --chisq arg (=10e-5) p-value threshold for initial chi squared test. Set to 1 to show all --pval arg (=10e-8) p-value threshold for final logistic test. Set to 1 to show all Other options: --print_samples print lists of samples significant kmers were found in --version prints version and exits -h [ --help ] full help message
Basic usage: seer -k dsm_input.txt.gz --pheno metadata.pheno > significant_kmers.txt To use the kmds output, increase execution speed and give the most complete output seer -k filtered.gz --pheno metadata.pheno --struct filtered.dsm --threads 4 --print_samples
This manpage was written by Andreas Tille for the Debian distribution and can be used for any other usage of the program.