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remove --classified parameter
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CSU-KangHu committed Jan 25, 2024
1 parent 3c84f00 commit e01f003
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Showing 2 changed files with 21 additions and 23 deletions.
2 changes: 0 additions & 2 deletions README.md
Original file line number Diff line number Diff line change
Expand Up @@ -270,8 +270,6 @@ optional arguments:
The chunk size of large genome, default = [ 400 MB ]
--miu miu The neutral mutation rate (per bp per ya), default = [ 1.3e-08 ]
--plant is_plant Is it a plant genome, 1: true, 0: false. default = [ 1 ]
--classified is_classified
Whether to classify TE models, HiTE uses RepeatClassifier from RepeatModeler to classify TEs, 1: true, 0: false. default = [ 1 ]
--remove_nested is_remove_nested
Whether to remove nested TE, 1: true, 0: false. default = [ 1 ]
--domain is_domain Whether to obtain TE domains, HiTE uses RepeatPeps.lib from RepeatMasker to obtain TE domains, 1: true, 0: false. default = [ 0 ]
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42 changes: 21 additions & 21 deletions main.py
Original file line number Diff line number Diff line change
Expand Up @@ -59,7 +59,7 @@
parser.add_argument('--chunk_size', metavar='chunk_size', help='The chunk size of large genome, default = [ ' + str(default_chunk_size) + ' MB ]')
parser.add_argument('--miu', metavar='miu', help='The neutral mutation rate (per bp per ya), default = [ ' + str(default_miu) + ' ]')
parser.add_argument('--plant', metavar='is_plant', help='Is it a plant genome, 1: true, 0: false. default = [ ' + str(default_plant) + ' ]')
parser.add_argument('--classified', metavar='is_classified', help='Whether to classify TE models, HiTE uses RepeatClassifier from RepeatModeler to classify TEs, 1: true, 0: false. default = [ ' + str(default_classified) + ' ]')
# parser.add_argument('--classified', metavar='is_classified', help='Whether to classify TE models, HiTE uses RepeatClassifier from RepeatModeler to classify TEs, 1: true, 0: false. default = [ ' + str(default_classified) + ' ]')
parser.add_argument('--remove_nested', metavar='is_remove_nested',help='Whether to remove nested TE, 1: true, 0: false. default = [ ' + str(default_remove_nested) + ' ]')
parser.add_argument('--domain', metavar='is_domain', help='Whether to obtain TE domains, HiTE uses RepeatPeps.lib from RepeatMasker to obtain TE domains, 1: true, 0: false. default = [ ' + str(default_domain) + ' ]')
parser.add_argument('--recover', metavar='is_recover', help='Whether to enable recovery mode to avoid starting from the beginning, 1: true, 0: false. default = [ ' + str(default_recover) + ' ]')
Expand Down Expand Up @@ -94,7 +94,7 @@
chrom_seg_length = args.chrom_seg_length
flanking_len = args.flanking_len
plant = args.plant
classified = args.classified
# classified = args.classified
remove_nested = args.remove_nested
domain = args.domain
miu = args.miu
Expand Down Expand Up @@ -168,10 +168,10 @@
else:
plant = int(plant)

if classified is None:
classified = default_classified
else:
classified = int(classified)
# if classified is None:
# classified = default_classified
# else:
# classified = int(classified)

if remove_nested is None:
remove_nested = default_remove_nested
Expand Down Expand Up @@ -298,7 +298,7 @@
log.logger.info('\nParameters configuration\n'
'====================================System settings========================================\n'
' [Setting] Reference sequences / assemblies path = [ ' + str(reference) + ' ]\n'
' [Setting] Is classified = [ ' + str(classified) + ' ] Default( ' + str(default_classified) + ' )\n'
# ' [Setting] Is classified = [ ' + str(classified) + ' ] Default( ' + str(default_classified) + ' )\n'
' [Setting] Is remove nested TE = [ ' + str(remove_nested) + ' ] Default( ' + str(default_remove_nested) + ' )\n'
' [Setting] Is getting domain = [ ' + str(domain) + ' ] Default( ' + str(default_domain) + ' )\n'
' [Setting] The neutral mutation rate (per bp per ya) = [ ' + str(miu) + ' ] Default( ' + str(default_miu) + ' )\n'
Expand Down Expand Up @@ -331,20 +331,20 @@

# The HiTE pipeline performs recognition of LTR, Non-LTR, TIR, and Helitron transposons.
# The organizational structure of HiTE is as follows:
# Pipeline:
# ├──LTR: judge_LTR_transposons.py
# ├──Homology-Non-LTR: judge_Other_transposons.py
# ├──split genome into chunks: split_genome_chunks.py
# ├──De novo TE searching: coarse_boundary.py
# ├──TIR: judge_TIR_transposons.py
# ├──Helitron: judge_Helitron_transposons.py
# └──De novo-Non-LTR: judge_Non_LTR_transposons.py
# ├──generate TE library: get_nonRedundant_lib.py
# └──unwrap nested TE: remove_nested_lib.py
# ├──classify TE library: get_classified_lib.py
# ├──genome annotation: annotate_genome.py
# ├──benchmarking reproduction: benchmarking.py
# └──clean temporary files: clean_lib.py
# Pipeline: main.py
# ├──LTR: judge_LTR_transposons.py
# ├──Homology-Non-LTR: judge_Other_transposons.py
# ├──split genome into chunks: split_genome_chunks.py
# ├──De novo TE searching: coarse_boundary.py
# ├──TIR: judge_TIR_transposons.py
# ├──Helitron: judge_Helitron_transposons.py
# └──De novo-Non-LTR: judge_Non_LTR_transposons.py
# ├──generate TE library: get_nonRedundant_lib.py
# └──unwrap nested TE: remove_nested_lib.py
# ├──genome annotation: annotate_genome.py
# ├──benchmarking reproduction: benchmarking.py
# └──clean temporary files: clean_lib.py

pipeline_starttime = time.time()
if skip_HiTE != 1:
log.logger.info('Start step0: Structural Based LTR Searching')
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