the step "phase_snps" error about hatchet HOT 3 OPEN

________________________________ From: Brian J Arnold ***@***.***> Sent: Monday, October 31, 2022 6:12 AM To: raphael-group/hatchet ***@***.***> Cc: Wu, Wei ***@***.***>; Author ***@***.***> Subject: Re: [raphael-group/hatchet] the step "phase_snps" error (Issue #170) Hi Wei, Could you provide a copy of your hatchet. ini file here? At first glance it looks like the first step to download the reference panel may not have been done, or the path of the panel (located in the download_panel. refpaneldir variable) ZjQcmQRYFpfptBannerStart This Message Is From an External Sender This message came from outside your organization. ZjQcmQRYFpfptBannerEnd Hi Wei, Could you provide a copy of your hatchet.ini file here? At first glance it looks like the first step to download the reference panel may not have been done, or the path of the panel (located in the download_panel.refpaneldir variable) was not specified. Sincerely, Brian — Reply to this email directly, view it on GitHub<https://urldefense.com/v3/__https://github.com/raphael-group/hatchet/issues/170*issuecomment-1297068925__;Iw!!LQC6Cpwp!oWqEGhHNVnFEqpQBEDssJjoU3lcxN8zQKMALMxi45Jza1kURDwMygP_a5kf3I4rGV03S5DUHE7_It9fgW0LdQqXk$>, or unsubscribe<https://urldefense.com/v3/__https://github.com/notifications/unsubscribe-auth/ADZWCCDLLUCEDLCAMXMH4JDWF7AUJANCNFSM6AAAAAARORL4J4__;!!LQC6Cpwp!oWqEGhHNVnFEqpQBEDssJjoU3lcxN8zQKMALMxi45Jza1kURDwMygP_a5kf3I4rGV03S5DUHE7_It9fgW5bceooB$>. You are receiving this because you authored the thread.Message ID: ***@***.***> [run] # What individual steps of HATCHet should we run in the pipeline? # Valid values are True or False download_panel = False count_reads = True genotype_snps = True phase_snps = False fixed_width = False # True uses older fixed-width versions of some commands count_alleles = True combine_counts = True cluster_bins = True loc_clust = True # True uses new locality-aware clustering plot_bins = True compute_cn = True plot_cn = True # What chromosome(s) do we wish to process in the pipeline? Leave unspecified to process # all chromosomes found in the normal/tumor bam files chromosomes = # Path to reference genome # Make sure you have also generated the reference dictionary as /path/to/reference.dict reference = /Users/cancerbio/Desktop/Bioinformatics_tools/humanRefGenome/UCSC-hg19/UCSC-hg19.fa # Make sure you have generated the .bam.bai files at the same locations as these bam files normal = /Users/cancerbio/Desktop/UCSF500_WGD_HATCHET/CGP-4959.deduplicated.realign.bam # Space-delimited list of tumor BAM locations bams = /Users/cancerbio/Desktop/UCSF500_WGD_HATCHET/CGP-4960+CGP-4992.deduplicated.realign.bam # Space-delimited list of tumor names samples = CGP4960 # Output path of the run script output = /Users/cancerbio/Desktop/UCSF500_HATCHET_RESULTS/wwu_1 # How many cores to use for the end-end pipeline? # This parameter, if specified, will override corresponding 'processes' parameters in individual <step> sections below. processes = 6 #[download_panel] #ref_panel = 1000GP_Phase3 #refpaneldir = /Users/cancerbio/Desktop/UCSF500_WGD_HATCHET/1000gp3/1000GP_Phase3 download_panel.refpaneldir = /Users/cancerbio/Desktop/UCSF500_WGD_HATCHET/1000gp3/1000GP_Phase3/1000GP_phase3_WWU #[genotype_snps] # Reference version used to select list of known germline SNPs; # Possible values are "hg19" or "hg38", or leave blank "" if you wish for all positions to be genotyped by bcftools reference_version = hg19 # Does your reference name chromosomes with "chr" prefix?; True or False chr_notation = True # Use 8 for WGS with >30x and 20 for WES with ~100x mincov = 20 # Use 300 for WGS with >30x and Use 1000 for WES with ~100x maxcov = 1000 config.paths.mosdepth = /opt/anaconda3/envs/hatchet/bin/mosdepth # Path to SNP list # If unspecified, HATCHet selects a list of known germline SNPs based on <run.reference_version> and <run.chr_notation> # If not, please provide full path to a locally stored list (.vcf.gz) here. snps = [combine_counts] # Minimum number of SNP-covering reads per bin and sample msr = 5000 # Minimum number of total reads per bin and sample mtr = 5000 [cluster_bins_loc] diploidbaf = 0.08 # Minimum and maximum number of clusters to infer # (using silhouette score for model selection) minK = 2 maxK = 30 # You can instead specify an exact number of clusters: # exactK = 15 [plot_bins] sizethreshold = 0.01 figsize = "6,3" [compute_cn] clones = 2,6 seeds = 400 minprop = 0.03 diploidcmax = 6 tetraploidcmax = 12 ghostprop = 0.35 limitinc = 0.6