hatchet.bin package

Submodules

hatchet.bin.HATCHet module

class hatchet.bin.HATCHet.ProgressBar(total, length, counter=0, verbose=False, decimals=1, fill='█', prefix='Progress:', suffix='Complete')

Bases: object

Methods

progress

progress(advance=True, msg='')

hatchet.bin.HATCHet.argmax(d)

hatchet.bin.HATCHet.argmin(d)

hatchet.bin.HATCHet.backward(f, i, g, limit)

hatchet.bin.HATCHet.central(f, i, g, limit)

hatchet.bin.HATCHet.computeSizes(seg, bbc, samples)

hatchet.bin.HATCHet.debug(msg)

hatchet.bin.HATCHet.estimate_forward(f, i, g, knw, limit)

hatchet.bin.HATCHet.execute(args, basecmd, n, outprefix)

hatchet.bin.HATCHet.execute_python(solver, args, n, outprefix)

hatchet.bin.HATCHet.filtering(bbc, seg, size, ts, tc, mB, mR, samples, v)

hatchet.bin.HATCHet.findClonalClusters(fseg, neutral, size, tB, tR, samples, v)

hatchet.bin.HATCHet.findNeutralCluster(seg, size, td, samples, v)

hatchet.bin.HATCHet.forward(f, i, g, limit)

hatchet.bin.HATCHet.info(msg)

hatchet.bin.HATCHet.isfloat(value)

hatchet.bin.HATCHet.logArgs(args, width)

hatchet.bin.HATCHet.main(args=None)

hatchet.bin.HATCHet.makeBaseCMD(args, e)

hatchet.bin.HATCHet.parseClonalClusters(clonal, fseg, size, samples, v)

hatchet.bin.HATCHet.parse_clonal_diploid(clonal)

Given a list of clonal cluster copy numbers, this function tries to order them to be compatible with the HATCHet C++ factorization module. For diploid scaling, this module requires: -the first cluster is indicated with copy-number 1,1 -the second cluster has a total copy number different from 2

hatchet.bin.HATCHet.parse_clonal_tetraploid(clonal)

Given a list of clonal cluster copy numbers, this function tries to order them to be compatible with the HATCHet C++ factorization module. For tetraploid scaling, this module requires: -the first cluster is indicated with copy-number 2,2 -the second cluster has a total copy number different from 4

hatchet.bin.HATCHet.parsing_arguments(args=None)

Parse command line arguments Returns:

hatchet.bin.HATCHet.readBBC(filename)

hatchet.bin.HATCHet.readSEG(filename)

hatchet.bin.HATCHet.runningDiploid(neutral, args, clonal=None)

hatchet.bin.HATCHet.runningTetraploid(clonal, scale, size, args)

hatchet.bin.HATCHet.safediv(v)

hatchet.bin.HATCHet.select(diploid, tetraploid, v, rundir, g, limit)

hatchet.bin.HATCHet.selectDiploid(diploid, v, rundir, g, limit)

hatchet.bin.HATCHet.selectTetraploid(tetraploid, v, rundir, g, limit)

hatchet.bin.HATCHet.t2s(x)

hatchet.bin.HATCHet.warning(msg)

hatchet.bin.HATCHet-preprocess module

hatchet.bin.model_select module

hatchet.bin.model_select.info(msg)

hatchet.bin.model_select.model_selection(diploid_objs: list, tetraploid_objs: list, wd: str, v=1)

1. per solution instance, compute likelihoods of observed RDR and BAF given CNP.

2. select best solution based on elbow detection on likelihood curves.

3. WGD ver no WGD by principle of parsimony.

Module contents