def launch(args):
mkOutdir(args.output, args.force)
pangenome = Pangenome()
pangenome.addFile(args.pangenome)
if args.proteins is not None:
align(pangenome=pangenome,
proteinFile=args.proteins,
output=args.output,
tmpdir=args.tmpdir,
identity=args.identity,
coverage=args.coverage,
defrag=args.defrag,
cpu=args.cpu,
getinfo=args.getinfo,
draw_related=args.draw_related)
if args.annotation is not None:
projectRGP(pangenome,
args.annotation,
args.output,
args.tmpdir,
args.identity,
args.coverage,
args.defrag,
args.cpu,
args.translation_table,
pseudo=args.use_pseudo)
def launch(args):
"""
main code when launch partition from the command line.
"""
if args.draw_ICL or args.keep_tmp_files:
mkOutdir(args.output, args.force)
pangenome = Pangenome()
pangenome.addFile(args.pangenome)
partition(pangenome,
args.tmpdir,
args.output,
args.force,
args.beta,
args.max_degree_smoothing,
args.free_dispersion,
args.chunk_size,
args.nb_of_partitions,
args.krange,
args.ICL_margin,
args.draw_ICL,
args.cpu,
args.seed,
args.keep_tmp_files,
show_bar=args.show_prog_bars)
writePangenome(pangenome,
pangenome.file,
args.force,
show_bar=args.show_prog_bars)
def launch(args):
""" launch the clustering step"""
pangenome = Pangenome()
pangenome.addFile(args.pangenome)
if args.clusters is None:
clustering(pangenome,
args.tmpdir,
args.cpu,
defrag=not args.no_defrag,
code=args.translation_table,
coverage=args.coverage,
identity=args.identity,
mode=args.mode,
force=args.force,
disable_bar=args.disable_prog_bar)
logging.getLogger().info("Done with the clustering")
else:
readClustering(pangenome,
args.clusters,
args.infer_singletons,
args.force,
disable_bar=args.disable_prog_bar)
logging.getLogger().info("Done reading the cluster file")
writePangenome(pangenome,
pangenome.file,
args.force,
disable_bar=args.disable_prog_bar)
def launch(args):
mkOutdir(args.output, args.force)
pangenome = Pangenome()
pangenome.addFile(args.pangenome)
writeFlatFiles(pangenome,
args.output,
cpu=args.cpu,
soft_core=args.soft_core,
dup_margin=args.dup_margin,
csv=args.csv,
genePA=args.Rtab,
gexf=args.gexf,
light_gexf=args.light_gexf,
projection=args.projection,
stats=args.stats,
json=args.json,
partitions=args.partitions,
regions=args.regions,
families_tsv=args.families_tsv,
all_genes=args.all_genes,
all_prot_families=args.all_prot_families,
all_gene_families=args.all_gene_families,
spots=args.spots,
borders=args.borders,
compress=args.compress)
def launch(args):
pangenome = Pangenome()
pangenome.addFile(args.pangenome)
if args.spot_graph or args.draw_hotspots:
mkOutdir(args.output, args.force)
predictHotspots(pangenome, args.output, force=args.force, cpu = args.cpu, spot_graph=args.spot_graph, overlapping_match=args.overlapping_match, set_size=args.set_size, exact_match=args.exact_match_size, draw_hotspot=args.draw_hotspots, interest=args.interest)
writePangenome(pangenome, pangenome.file, args.force)
def launch(args):
mkOutdir(args.output, args.force)
pangenome = Pangenome()
pangenome.addFile(args.pangenome)
if args.tile_plot:
drawTilePlot(pangenome, args.output, args.nocloud)
if args.ucurve:
drawUCurve(pangenome, args.output, soft_core = args.soft_core)
def launchSequences(args):
checkOptions(args)
mkOutdir(args.output, args.force)
pangenome = Pangenome()
pangenome.addFile(args.pangenome)
writeSequenceFiles(pangenome, args.output, fasta=args.fasta, anno=args.anno, soft_core=args.soft_core,
regions=args.regions, genes=args.genes, gene_families=args.gene_families,
prot_families=args.prot_families, compress=args.compress, disable_bar=args.disable_prog_bar)
def launch(args):
mkOutdir(args.output, args.force)
pangenome = Pangenome()
pangenome.addFile(args.pangenome)
writeFlatFiles(pangenome, args.output, args.cpu, args.soft_core,
args.dup_margin, args.csv, args.Rtab, args.gexf,
args.light_gexf, args.projection, args.stats, args.json,
args.partitions, args.families_tsv, args.all_genes,
args.all_prot_families, args.all_gene_families,
args.compress)
def launch(args):
pangenome = Pangenome()
pangenome.addFile(args.pangenome)
predictRGP(pangenome,
force=args.force,
persistent_penalty=args.persistent_penalty,
variable_gain=args.variable_gain,
min_length=args.min_length,
min_score=args.min_score,
dup_margin=args.dup_margin,
cpu=args.cpu)
writePangenome(pangenome, pangenome.file, args.force)
def launchMSA(args):
mkOutdir(args.output, args.force)
pangenome = Pangenome()
pangenome.addFile(args.pangenome)
writeMSAFiles(pangenome,
args.output,
cpu=args.cpu,
partition=args.partition,
tmpdir=args.tmpdir,
source=args.source,
force=args.force,
show_bar=args.show_prog_bars)
def launch(args):
pangenome = Pangenome()
pangenome.addFile(args.pangenome)
if args.spot_graph:
mkOutdir(args.output, args.force)
if args.draw_hotspots or args.interest or args.fig_margin or args.priority:
logging.getLogger().warning(
"Options to draw the spots with the 'ppanggolin spot' subcommand have been deprecated, "
"and are now dealt with in a dedicated subcommand 'ppanggolin drawspot'.")
predictHotspots(pangenome, args.output, force=args.force, cpu=args.cpu, spot_graph=args.spot_graph,
overlapping_match=args.overlapping_match, set_size=args.set_size, exact_match=args.exact_match_size,
disable_bar=args.disable_prog_bar)
writePangenome(pangenome, pangenome.file, args.force, disable_bar=args.disable_prog_bar)
def launch(args):
""" launch the clustering step"""
pangenome = Pangenome()
pangenome.addFile(args.pangenome)
if args.clusters is None:
clustering(pangenome, args.tmpdir, args.cpu, args.defrag,
args.translation_table, args.coverage, args.identity,
args.force)
logging.getLogger().info("Done with the clustering")
else:
readClustering(pangenome, args.clusters, args.infer_singletons,
args.force)
logging.getLogger().info("Done reading the cluster file")
writePangenome(pangenome, pangenome.file, args.force)
def launchSequences(args):
mkOutdir(args.output, args.force)
pangenome = Pangenome()
pangenome.addFile(args.pangenome)
checkOptions(args)
writeSequenceFiles(pangenome,
args.output,
fasta=args.fasta,
anno=args.anno,
cpu=args.cpu,
regions=args.regions,
genes=args.genes,
prot_families=args.prot_families,
gene_families=args.gene_families,
compress=args.compress,
show_bar=args.show_prog_bars)
def launch(args):
if not any(x for x in [args.genome_fluidity, args.family_fluidity, args.info_modules, args.all]):
raise Exception("You did not indicate which metric you want to compute.")
pangenome = Pangenome()
pangenome.addFile(args.pangenome)
logging.getLogger().debug("Check if one of the metrics was already compute")
check_metric(pangenome, all=args.all, genome_fluidity=args.genome_fluidity, family_fluidity=args.family_fluidity,
info_modules=args.info_modules, force=args.force)
logging.getLogger().info("Metrics computation begin")
metrics_dictionary = compute_metrics(pangenome, all=args.all, genome_fluidity=args.genome_fluidity,
family_fluidity=args.family_fluidity, info_modules=args.info_modules,
disable_bar=args.disable_prog_bar)
logging.getLogger().info("Metrics computation done")
write_metrics(pangenome, metrics_dictionary, no_print_info=args.no_print_info)
def launch(args):
mkOutdir(args.output, args.force)
pangenome = Pangenome()
pangenome.addFile(args.pangenome)
if args.tile_plot:
drawTilePlot(pangenome,
args.output,
args.nocloud,
disable_bar=args.disable_prog_bar)
if args.ucurve:
drawUCurve(pangenome,
args.output,
soft_core=args.soft_core,
disable_bar=args.disable_prog_bar)
if args.spots != '':
drawSpots(pangenome=pangenome,
output=args.output,
spot_list=args.spots,
disable_bar=args.disable_prog_bar)
def launch(args):
mkOutdir(args.output, args.force)
pangenome = Pangenome()
pangenome.addFile(args.pangenome)
if args.interest or args.fig_margin or args.label_priority:
logging.getLogger().warning(
"Options --interest, --fig_margin and --label_priority are deprecated, "
"and the actions they defined are now doable directly in the interactive figures "
"that are drawn")
align(pangenome=pangenome,
sequenceFile=args.sequences,
output=args.output,
tmpdir=args.tmpdir,
cpu=args.cpu,
identity=args.identity,
coverage=args.coverage,
no_defrag=args.no_defrag,
getinfo=args.getinfo,
draw_related=args.draw_related,
disable_bar=args.disable_prog_bar)
def launch(args):
"""
main code when launch partition from the command line.
"""
mkOutdir(args.output, args.force)
pangenome = Pangenome()
pangenome.addFile(args.pangenome)
makeRarefactionCurve( pangenome = pangenome,
output = args.output,
tmpdir = args.tmpdir,
beta =args.beta,
depth = args.depth,
minSampling=args.min,
maxSampling=args.max,
sm_degree=args.max_degree_smoothing,
free_dispersion=args.free_dispersion,
chunk_size=args.chunk_size,
K=args.nb_of_partitions,
cpu = args.cpu,
seed = args.seed,
kestimate=args.reestimate_K,
krange = args.krange,
soft_core = args.soft_core)
def launch(args):
logging.getLogger().debug(f"Ram used at the start : {getCurrentRAM()}")
pangenome = Pangenome()
pangenome.addFile(args.pangenome)
computeNeighborsGraph(pangenome, args.remove_high_copy_number, args.force)
writePangenome(pangenome, pangenome.file, args.force)
def launch(args):
mkOutdir(args.output, args.force)
pangenome = Pangenome()
pangenome.addFile(args.pangenome)
align(pangenome, args.proteins, args.output, args.tmpdir, args.identity,
args.coverage, args.defrag, args.cpu)
def launch(args):
pangenome = Pangenome()
pangenome.addFile(args.pangenome)
computeNeighborsGraph(pangenome, args.remove_high_copy_number, args.force, show_bar=args.show_prog_bars)
writePangenome(pangenome, pangenome.file, args.force, show_bar=args.show_prog_bars)