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Lundberg_et_al_gIMble_commands.txt
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Lundberg_et_al_gIMble_commands.txt
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# preprocess
gIMble preprocess -f ww_pacbio_bionano_arcs_pbjelly_pilon.filt_with_mt.filt.fasta -v pacbio.vcf.gz -b bam_symlinks -g 2 -m 8 -M 0.75 -t 8
# set up zarr stores
gIMble setup -g chromosome_1.gimble.genomefile -b chromosome_1.gimble.bed -s chromosome_1.gimble.samples -v gimble.vcf.gz -o chromosome_1.64
gIMble setup -g chromosome_3.gimble.genomefile -b chromosome_3.gimble.bed -s chromosome_3.gimble.samples -v gimble.vcf.gz -o chromosome_3.64
gIMble setup -g chromosome_5.gimble.genomefile -b chromosome_5.gimble.bed -s chromosome_5.gimble.samples -v gimble.vcf.gz -o chromosome_5.64
# get blocks
gIMble blocks -z chromosome_1.64.z -l 64 --force
gIMble blocks -z chromosome_3.64.z -l 64 --force
gIMble blocks -z chromosome_5.64.z -l 64 --force
# set up models
gIMble model -p 2 -s A,B -n 1,1 -j A,B
gIMble model -p 2 -s A,B -n 1,1 -j A,B -m 'A>B'
gIMble model -p 2 -s A,B -n 1,1 -j A,B -m 'B>A'
# for each divergent region, optimise each model
gIMble optimize -z chromosome_1.64.z -c gimble.model.s_A_B.n_1_1.J_A_B.ini -m gimble.model.s_A_B.n_1_1.J_A_B.tsv -b -t 16,1 -i 1000
gIMble optimize -z chromosome_3.64.z -c gimble.model.s_A_B.n_1_1.J_A_B.ini -m gimble.model.s_A_B.n_1_1.J_A_B.tsv -b -t 16,1 -i 1000
gIMble optimize -z chromosome_5.64.z -c gimble.model.s_A_B.n_1_1.J_A_B.ini -m gimble.model.s_A_B.n_1_1.J_A_B.tsv -b -t 16,1 -i 1000
gIMble optimize -z chromosome_1.64.z -c gimble.model.s_A_B.n_1_1.M_A_B.J_A_B.ini -m gimble.model.s_A_B.n_1_1.M_A_B.J_A_B.tsv -b -t 16,1 -i 1000
gIMble optimize -z chromosome_3.64.z -c gimble.model.s_A_B.n_1_1.M_A_B.J_A_B.ini -m gimble.model.s_A_B.n_1_1.M_A_B.J_A_B.tsv -b -t 16,1 -i 1000
gIMble optimize -z chromosome_5.64.z -c gimble.model.s_A_B.n_1_1.M_A_B.J_A_B.ini -m gimble.model.s_A_B.n_1_1.M_A_B.J_A_B.tsv -b -t 16,1 -i 1000
gIMble optimize -z chromosome_1.64.z -c gimble.model.s_A_B.n_1_1.M_B_A.J_A_B.ini -m gimble.model.s_A_B.n_1_1.M_B_A.J_A_B.tsv -b -t 16,1 -i 1000
gIMble optimize -z chromosome_3.64.z -c gimble.model.s_A_B.n_1_1.M_B_A.J_A_B.ini -m gimble.model.s_A_B.n_1_1.M_B_A.J_A_B.tsv -b -t 16,1 -i 1000
gIMble optimize -z chromosome_5.64.z -c gimble.model.s_A_B.n_1_1.M_B_A.J_A_B.ini -m gimble.model.s_A_B.n_1_1.M_B_A.J_A_B.tsv -b -t 16,1 -i 1000
# simulate SI data for each divergent region
gIMble simulate -z chromosome_1.64.z -c gimble.model.s_A_B.n_1_1.J_A_B.sims_1_SI.ini -b 72432 -r 100 -t 8 -l optimised_SI
gIMble simulate -z chromosome_3.64.z -c gimble.model.s_A_B.n_1_1.J_A_B.sims_3_SI.ini -b 83537 -r 100 -t 8 -l optimised_SI
gIMble simulate -z chromosome_5.64.z -c gimble.model.s_A_B.n_1_1.J_A_B.sims_5_SI.ini -b 28351 -r 100 -t 8 -l optimised_SI
# for each simulated SI dataset, optimise under an SI and the best fitting (IM) model
gIMble optimize -z chromosome_1.64.z -c gimble.model.s_A_B.n_1_1.J_A_B.ini -m gimble.model.s_A_B.n_1_1.J_A_B.tsv -s -t 7,7 -i 1000 -l optimised_SI
gIMble optimize -z chromosome_3.64.z -c gimble.model.s_A_B.n_1_1.J_A_B.ini -m gimble.model.s_A_B.n_1_1.J_A_B.tsv -s -t 7,7 -i 1000 -l optimised_SI
gIMble optimize -z chromosome_5.64.z -c gimble.model.s_A_B.n_1_1.J_A_B.ini -m gimble.model.s_A_B.n_1_1.J_A_B.tsv -s -t 7,7 -i 1000 -l optimised_SI
gIMble optimize -z chromosome_1.64.z -c gimble.model.s_A_B.n_1_1.M_A_B.J_A_B.ini -m gimble.model.s_A_B.n_1_1.M_A_B.J_A_B.tsv -s -t 7,7 -i 1000 -l optimised_SI
gIMble optimize -z chromosome_3.64.z -c gimble.model.s_A_B.n_1_1.M_B_A.J_A_B.ini -m gimble.model.s_A_B.n_1_1.M_B_A.J_A_B.tsv -s -t 7,7 -i 1000 -l optimised_SI
gIMble optimize -z chromosome_5.64.z -c gimble.model.s_A_B.n_1_1.M_A_B.J_A_B.ini -m gimble.model.s_A_B.n_1_1.M_A_B.J_A_B.tsv -s -t 7,7 -i 1000 -l optimised_SI
# for the chromosome 3 region, simulate and optimise IM2 data to obtain 95%CIs
gIMble simulate -z chromosome_3.64.z -c gimble.model.s_A_B.n_1_1.M_B_A.J_A_B.sims_3_SI.ini -b 83537 -r 100 -t 8 -l optimised_IM
gIMble optimize -z chromosome_3.64.z -c gimble.model.s_A_B.n_1_1.M_B_A.J_A_B.ini -m gimble.model.s_A_B.n_1_1.M_B_A.J_A_B.tsv -s -t 7,7 -i 1000 -l optimised_IM