pygengraph

Install

Enter the directory of the library and enter:

pip install .

and for development use

pip install -e .[dev]

How to use

Use command line interface `pantograph`

After this package is installed, a command line tool pantograph becomes available.

It has several functions as following

Converting annotations to gene graph (see user manual on what is gene graph).

This is done by a command

$ pantograph annotation2graph [-h] [-g] setting_file.yaml

It requires a path to a yaml file with all settings for the process. If used with -g option, then a sample file will be generated for you to edit and then run it. Sample file has extensive comments explaining every parameter.

So, it is best to do the following:

$ pantograph annotation2graph -g setting.yaml

then, using your favourite text editor, edit the generated file and then run

$ pantograph annotation2graph setting.yaml

Converting a file(s) with paths into gene/block graph

This is done by a command

$ pantograph paths2graph [-h] [-g] setting_file.yaml

So, it is best to do the following:

$ pantograph paths2graph -g setting.yaml

then, using your favourite text editor, edit the generated file and then run

$ pantograph paths2graph setting.yaml

Sorting a graph

In order to sort a graph, it should be in GFA v1 format file. To run the sorting, you need to use the following command:

$ pantograph sort-graph [-h] [--quiet] [--isseq] [--output OUTPUT] input

with the following parameters

positional arguments:

input Relative (to current directory) or absolute path to the GFA file with the graph to be sorted.

optional arguments:

-h, --help show this help message and exit

--quiet, -q Suppress most of output. False (i.e. verbose) is not set.

--isseq, -s Does this graph contains nucleotide sequences. False is not set.

--output OUTPUT, -o OUTPUT File path where to save sorted graph. If not set, the input will be overwritten.

Exporting graph into visualisation data structure, which can be used by Pantograph visualisation tool.

This is done by a command

$ pantograph export-vis [-h] [-g] setting_file.yaml

So, it is best to do the following:

$ pantograph export-vis -g setting.yaml

then, using your favourite text editor, edit the generated file and then run

$ pantograph export-vis setting.yaml

Use python package

The rest of the file describes some of the uses of the pyGenGraph package. There are more ways to use it, but more detailed documentation is needed to describe all use cases. Also, more things required for this package to become really universal.

from nbdev import nbdev_export
nbdev_export()

import os
import glob
import re
import time

from pygengraph.graph import GenomeGraph
from pygengraph.utils import pathFileToPathDict
from pygengraph.export import exportProject

If redis database needs to be cleaned.

from redis import Redis

redisConn = Redis(host=‘redis’,port=6379)

redisConn.flushall()

redisConn.close()

del redisConn

import warnings
warnings.simplefilter('ignore')
warnings.filterwarnings('always',category=RuntimeWarning)

Generating graphs

Generating from annotation

Preparing list of files

refdir = '/path/to/reference/'
annotationdir = '/path/to/annotation'
gfadir = '/path/to/graphs'

annotationFiles = sorted(glob.glob(f'{annotationdir}{os.path.sep}*.gff'))
pangenomeFiles = sorted(glob.glob(f'{annotationdir}{os.path.sep}*pangen.gff'))
# If you want to include sequences instead of simple notion of genes.
# It should also be converted to sequenceFileDict, see details in documentation for GenomeGraph Class constructor.
# sequenceFiles = sorted(glob.glob(f'{annotationdir}{os.path.sep}sequences{os.path.sep}*.fasta'))
refAnnotationFile = f'{refdir}{os.path.sep}reference.gff'
# If you want to include sequences instead of simple notion of genes
# refSequenceFile = f'{refdir}{os.path.sep}reference.fasta'

refdir = '../../1001G/annotations/freeze2.1/outgroups'
annotationdir = '../../1001G/annotations/freeze2.1'
gfadir = '../../1001G/annotations/graphs'

annotationFiles = sorted(glob.glob(f'{annotationdir}{os.path.sep}*.gff'))
# pangenomeFiles = sorted(glob.glob(f'{annotationdir}{os.path.sep}*pangen.gff'))
# If you want to include sequences instead of simple notion of genes.
# It should also be converted to sequenceFileDict, see details in documentation for GenomeGraph Class constructor.
# sequenceFiles = sorted(glob.glob(f'{annotationdir}{os.path.sep}sequences{os.path.sep}*.fasta'))
refAnnotationFile = f'{refdir}{os.path.sep}araport.gff'
# If you want to include sequences instead of simple notion of genes
# refSequenceFile = f'{refdir}{os.path.sep}reference.fasta'

Generaton of gene graph

doUS = False
n = 1
for chrnum in range(1,n+1): # here n is number of chromosomes.
    chromosome = f'Chr{chrnum}'

    print(f'\nProcessing {chromosome}\n============')

    curtst = time.time()
    
    graph = GenomeGraph(annotationFiles = annotationFiles,
                        pangenomeFiles = None,
                        sequenceFilesDict = None,
                        doUS = doUS,
                        chromosome = chromosome,
                        refAnnotationFile=refAnnotationFile,
                        refAccession='TAIR10')
    
    print(f'Generating graph for {chromosome} took {time.time() - curtst} seconds')
    
    curtst = time.time()
    graph.treeSort()
    print(f'Sorting graph for {chromosome} took {time.time() - curtst} seconds')
    if len(graph.nodes)!=len(graph.order):
            print('Sorting failed and not all nodes were sorted. Saving unsorted graph')
            gfaFilename = f'Gene_{chromosome}_simOnly_unordered.gfa'
            graph.order = list(range(1,len(graph.nodes)+1))
    else:
        gfaFilename = f'Gene_{chromosome}_simOnly.gfa'
    
    graph.toGFA(f'{gfadir}{os.path.sep}{gfaFilename}',doSeq=False)

Loading Pathfile to graph

# For path file v1
pathfileDir = 'examples/gene_graph'

pathsfile = 'paths_genegraph.txt'

paths = pathFileToPathDict(f'{pathfileDir}{os.path.sep}{pathsfile}', True, True, False)

graph = GenomeGraph(pathsDict=paths)

graph.treeSort()

if len(graph.nodes)!=len(graph.order):
    print('Sorting failed and not all nodes were sorted. Saving unsorted graph')
    output = 'paths_genegraph_unordered.gfa'
    graph.order = list(range(1,len(graph.nodes)+1))
    graph.toGFA(output,doSeq=False)
else:
    coreGFApath = f'{pathfileDir}{os.path.sep}paths_genegraph.gfa'
    graph.toGFA(coreGFApath,doSeq=False)

# For v2
# This is example, no v2 file currently available for demonstration.
pathfileDir = '/path/to/file'

pathsfile = f'paths.txt'

paths = pathFileToPathDict(f'{pathfileDir}{os.path.sep}{pathsfile}',True,'reference',True)

for seqNum in paths.keys():

    graph = GenomeGraph(pathsDict=paths[seqNum])

    # On undirected coregraph sorting is not optimal! Check sorting!!!

    graph.treeSort()

    if len(graph.nodes)!=len(graph.order):
        print('Sorting failed and not all nodes were sorted. Saving unsorted graph')
        output = f'{pathfileDir}{os.path.sep}graph_Chr{seqNum}_unordered.gfa'
        graph.order = list(range(1,len(graph.nodes)+1))
        graph.toGFA(output,doSeq=False)
    else:
        coreGFApath = f'{pathfileDir}{os.path.sep}graph_Chr{seqNum}.gfa'
        graph.toGFA(coreGFApath,doSeq=False)

Loading graph from GFA and sorting it

gfadir = 'examples/nucleotide_graph'

# It is nucleotide graph. If it is not nucleotide graph, then `isSeq` variable should be changed to False.
gfafilename = 'paths_presentation.gfa'
isSeq = True

graph = GenomeGraph(gfaPath=f'{gfadir}{os.path.sep}{gfafilename}',isGFASeq=isSeq)

graph.treeSort()

assert len(graph.nodes)==len(graph.order)

basename,ext = os.path.splitext(gfafilename)

graph.toGFA(f'{gfadir}{os.path.sep}{basename}_ordered{ext}',doSeq=isSeq)

Exporting to Pantograph visualisation

projectID = 'paths_genegraph'
projectName = 'Example gene graph'
pathToGraphs = 'examples/gene_graph'
caseDict = {'Main': 'paths_genegraph.gfa'}
pathToIndex = 'examples/Visdata'

# This is if you run it in Docker compose together with active Redis image, which is named "redis".
# If you have separate redis server, enter full address here.
# If you do not want to add any annotation, `redisHost` should be None.
redisHost = 'redis'
redisPort = 6379
redisDB = 0

suffix = ''

maxLengthComponent = 100
maxLengthChunk = 6
inversionThreshold = 0.5
isSeq = False
zoomLevels = [1,2,4]
fillZoomLevel = True

exportProject(projectID, projectName, caseDict, pathToIndex, pathToGraphs,
              redisHost = redisHost, redisPort = redisPort, redisDB = redisDB,
              suffix = suffix,
              maxLengthComponent = maxLengthComponent, maxLengthChunk = maxLengthChunk,
              inversionThreshold = inversionThreshold,
              isSeq = isSeq,
              zoomLevels = zoomLevels, fillZoomLevel = fillZoomLevel)

projectID = 'tutorial_graph'
projectName = 'Example nucleotide graph'
pathToGraphs = 'examples/nucleotide_graph'
caseDict = {'Main': 'paths_presentation_ordered.gfa'}
pathToIndex = 'examples/Visdata'

# This is if you run it in Docker compose together with active Redis image, which is named "redis".
# If you have separate redis server, enter full address here.
# If you do not want to add any annotation, `redisHost` should be None.
redisHost = 'redis'
redisPort = 6379
redisDB = 0

suffix = ''

maxLengthComponent = 100
maxLengthChunk = 6
inversionThreshold = 0.5
isSeq = True
zoomLevels = [1,2,4]
fillZoomLevel = True

exportProject(projectID, projectName, caseDict, pathToIndex, pathToGraphs,
              redisHost = redisHost, redisPort = redisPort, redisDB = redisDB,
              suffix = suffix,
              maxLengthComponent = maxLengthComponent, maxLengthChunk = maxLengthChunk,
              inversionThreshold = inversionThreshold,
              isSeq = isSeq,
              zoomLevels = zoomLevels, fillZoomLevel = fillZoomLevel)

Pigrenok/pygengraph

pygengraph

Install

How to use

Use command line interface pantograph

Converting annotations to gene graph (see user manual on what is gene graph).

Converting a file(s) with paths into gene/block graph

Sorting a graph

Exporting graph into visualisation data structure, which can be used by Pantograph visualisation tool.

Use python package

If redis database needs to be cleaned.

Generating graphs

Generating from annotation

Preparing list of files

Generaton of gene graph

Loading Pathfile to graph

Loading graph from GFA and sorting it

Exporting to Pantograph visualisation

Use command line interface `pantograph`