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
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