4.1.3. bootstrap.py¶
Randomly sample the pairs of orthologs and compute the scaled distance using that sample. The sample as the same size as the original set of orthologs (the sampling is done with replacement). This is the first step of a bootstrap.
The mode argument define what kind of value we want to keep while computing the distance:
- intersection: only the values present in all species are kept.
- atLeastTwo: keep the values present in at least two species.
- union: keep all values.
Note
It is intended to be used instead of dist_all_pairs.py and dist_pairs_indep.py.
created: | May 2018 |
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last modified: | August 2019 |
4.1.3.1. Usage¶
Perform the first step of a bootstrap by sampling at random the orthologs and computing a distances matrix with that sample.
usage: bootstrap.py [-h] [-o] [-m {intersection,atLeastTwo,union}] [-p] [-v]
orthos outdir n values [values ...]
4.1.3.1.1. Positional Arguments¶
orthos | all the orthos, in TSV |
outdir | the dir for the resulting samples |
n | the number of replicates |
values | the values files, in (Gzipped) TSV |
4.1.3.1.2. Named Arguments¶
-o, --one-file | put all matrices in one file called all_replicates.phylip Default: False |
-m, --mode | Possible choices: intersection, atLeastTwo, union the mode, that is, the kind of values we want to keep while computing the distance Default: “intersection” |
-p, --progress | print a progress bar; need tqdm to be installed Default: False |
-v, --verbose | be verbose Default: False |