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crick_project.yml
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#########################################
# TEST HiC project yaml
# SRA: SRR5339787
# Accession no: GSM2533822
#########################################
#######################################
# paths to raw input data (fastq-s):
#######################################
input:
raw_reads_paths:
SRR5339787:
lane1:
- /camp/home/westc/westc/data/neural_hic_data/sub_sample_test/fastq/sub1.fastq.gz
- /camp/home/westc/westc/data/neural_hic_data/sub_sample_test/fastq/sub2.fastq.gz
# Truncate input fastqs to a small number of reads (e.g. 10000) for
# semi-dry test runs.
truncate_fastq_reads: 0
# Specify a reference genome to align sequenced reads.
# Provide the genome assembly name, a wildcard path to the BWA index files
# of the reference genome, and a tab-separated table with contig sizes
# (known as "chrom.sizes"). The latter is used to specify the subset and the
# order of contigs in a resulting contact map.
genome:
assembly_name: 'mm10_chr6'
# bwa_index_wildcard_path: 'hic_data/genome/mm10.fa.*'
# chrom_sizes_path: 'hic_data/genome/mm10.chrom.sizes'
bwa_index_wildcard_path: '/camp/home/westc/westc/data/neural_hic_data/sub_sample_test/small_genome/mm10_chr6.fa.*'
chrom_sizes_path: '/camp/home/westc/westc/data/neural_hic_data/sub_sample_test/small_genome/mm10_chr6.chrom.sizes'
# Choose if you want to do FastQC of the input files:
do_fastqc: True
# Control how reads are mapped to the reference genomes.
map:
# If 'chunksize' is non-zero, each input file gets split into multiple chunks,
# each mapped separately. Useful for mapping on clusters with many
# relatively weak nodes.
# The optimal chunk size is defined by the balance between mapping and merging.
# Smaller chunks (~30M) are better for clusters with many weak nodes,
# however, having >~10 chunks per run slow down merging.
# chunksize: 0
# Specify extra BWA mapping options.
mapping_options: '-v 3'
# Specify fastp trim options.
#i.e. parameters
#--detect_adapter_for_pe -q 15
trim_options: '-q 20 --json /dev/null'
# A more technical option, use a custom script to split fastq files from SRA
# into two files, one per read side. By default it is true, which is
# faster (because we can use multi-threaded compression), but less
# stable. Set to false if you download files from SRA and bwa complains
# about unpaired reads.
use_custom_split: true
# Control how read alignments are converted ('parsed') into Hi-C pairs.
parse:
# If 'make_pairsam' is True, parsed Hi-C pairs will store complete
# alignment records in the SAM format (the resulting hybrid between the
# .pairs and .sam formats is called '.pairsam'). Such files can be useful for
# thorough investigation of Hi-C data. Downstream of parsing, pairsams
# are split into .pairs and .bam, and .bam alignments are tagged with
# Hi-C related information. 'make_pairsam' roughly doubles the storage
# and I/O requirements and should be used only when absolutely needed.
# NOTE: when 'make_pairsam' is False, the initial output of parsing is still
# called '.pairsam' despite missing SAM alignments, for technical reasons.
make_pairsam: True
# When 'make_pairsam' is True, enabling 'drop_seq' erases sequences and
# Phred scores from the SAM alignments in .pairsam and .bam output files.
# Enable to make lightweight .pairsam/.bam output.
# NOTE: when 'make_pairsam' is False, 'drop_seq' is ignored.
drop_seq: False
# Enable 'drop_readid' to drop readID from .pairs files to create
# lightweight .pairs files
# NOTE: does not affect alignment records in the .pairsam files and
# subsequently .bam files after .apirsam splitting.
drop_readid: False
# When 'keep_unparsed_bams' is True, distiller preserves the _immediate_
# output of bwa in a .bam format. Could be used as a faster alternative
# to 'make_pairsam' when alignments are needed, but tagging them with Hi-C
# related information is not necessary.
keep_unparsed_bams: True
# Pass extra options to pairtools parse, on top of the ones specified by
# flags 'make_pairsam', 'drop_readid', 'drop_seq'. The default value
# enables storing MAPQ scores in the .pairsam/.pairs output, which are
# used later for filtering/binning. The default walks-policy is 'mask'
# which masks complex walks in long reads.
parsing_options: '--add-columns mapq'
# Control how PCR/optical duplicates are detected in the data.
dedup:
# PCR/optical duplicates are detected as Hi-C pairs with matching locations
# on both sides. 'max_mismatch_bp' controls the maximal allowed mismatch in
# mapped locations on either side for two pairs to be still considered as
# duplicates.
max_mismatch_bp: 3
# Control how Hi-C pairs are binned into contact maps, stored in .cool files.
bin:
# Specify which resolutions should be included in the multi-resolution .cool file.
# The lowest (base) resolution _must_ be the common denominator of all other
# resolutions.
resolutions:
- 1000000
- 500000
- 250000
- 100000
- 50000
- 20000
- 10000
# Specify if the multi-resolution .cool output files should be balanced.
balance: true
# Pass additional parameters to cooler balance:
# balance_options: ''
# Specify additional filters applied to pairs during binning.
# Multiple filters are allowed; for each filter, all pairs satisfying the
# given filter expression will be binned into a separate cooler.
# Filters are specified using the following syntax:
# {filter_name}: '{a valid Python expression}'
filters:
no_filter: ''
mapq_30: '(mapq1>=30) and (mapq2>=30)'
########################################
# folder structure for storing results
########################################
output:
dirs:
processed_fastqs: 'results/processed_fastqs/'
mapped_parsed_sorted_chunks: 'results/mapped_parsed_sorted_chunks'
fastqc: 'results/fastqc/'
pairs_library: 'results/pairs_library'
coolers_library: 'results/coolers_library/'
coolers_library_group: 'results/coolers_library_group/'
stats_library_group: 'results/stats_library_group/'