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circos_plot_C0002_all_genome.sh
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circos_plot_C0002_all_genome.sh
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# Circos plots - test with two scaffolds
http://circos.ca/documentation/tutorials/quick_start/hello_world/configuration
to run ciros on biolinux:
perl PATH/bin/circos -conf circos_Mc.conf
# note see end of file for how RNAseq was mapped and some files were generated:
#########################################################
#prepare the gene files first:
python PATH_TO/Circos_python_scripts/gc_window_for_sequences.py JOTR01000003.fasta 250 > JOTR01000003.gc.250.txt
python PATH_TO/Circos_python_scripts/gc_window_for_sequences.py Mc6148.fasta 250 > Mc6148.gc.250.txt
python PATH_TO/Circos_python_scripts/gc_window_for_sequences.py Mp1087439_TGAC_V1.1_scaffold_1256.fasta 250 > Mp1087439_TGAC_V1.1_scaffold_1256.gc.250.txt
python PATH_TO/Circos_python_scripts/gc_window_for_sequences.py GL349723.fasta 250 > GL349723.gc.250.txt
python PATH_TO/Circos_python_scripts/gc_window_for_sequences.py Rp1101.fasta 250 > Rp1101.gc.250.txt
#cat the coverage files of the scaffolds together in one file. , make sue the scaff names are consistent with later names
cat *gc.250.txt > all.GC.250.txt
$ cat *gc.25.txt > all.GC.25.txt
#############################################################################################################
2) create a karytype file: save this file, as the confi file will use this
#e.g. chr - ID LABEL START END COLOR
# SPACE SEPAREATED!!!
chr - Gr1_EF193005 Gr1 0 9210 vvvlgrey
chr - Gr2_EF462976 Gr2 0 6604 vvvlgrey
chr - Gr3_EF462977 Gr3 0 3192 vvvlgrey
chr - Gr4_EF462978 Gr4 0 6010 vvvlgrey
chr - Gr5_EF462979 Gr5 0 5480 vvvlgrey
chr - Gr6_EF462980 Gr6 0 5797 vvvlgrey
chr - Gr7_EF462981 Gr7 0 5308 vvvlgrey
# so I wan to draw to scaffold. detail the star and end, and only put two scaffold in the file.
# get scaff len from files from step one
chr - Mc363 Mc363 0 74024 vvvlgrey
chr - scaffold_172 scaffold_172 0 382779 vvvlgrey
chr - Rp1827 Rp1827 0 90145 vvvlgrey
chr - GL349624 GL349624 0 2478080 vvvlgrey
chr - JOTR01000179 JOTR01000179 0 536200 vvvlgrey
#############################################################################################################
3) get the coverage plots.
#I am chosing RNAseq cov.
#map the RNAseq to the whole genome:
mkdir star_indicies
$ STAR --runMode genomeGenerate --runThreadN 10 --limitGenomeGenerateRAM 74554136874 --genomeDir /PATH_TO/Mp_O/Mp_O_host_non_RNAseq_assembly/star_indicies --genomeFastaFiles /PATH_TO/Mp_O/Mp_O_host_non_RNAseq_assembly/Mp1087439_TGAC_V1.1-scaffolds.fa
$ STAR --genomeDir star_indicies/ --runThreadN 12 --outFilterMultimapNmax 5 --outSAMtype BAM SortedByCoordinate --outFilterMismatchNmax 7 --readFilesCommand zcat --outFileNamePrefix Mp_O_RNA_mapped --readFilesIn ../Mp_O_RNAseq/Mp_O_R1.fq.gz ../Mp_O_RNAseq/Mp_O_R2.fq.gz
# index the genome
$ STAR --runMode genomeGenerate --runThreadN 10 --limitGenomeGenerateRAM 74554136874 --genomeDir /PATH_TO/M.cerasi/star_indicies --genomeFastaFiles /PATH_TO/M.cerasi/Mc_alt.fasta
$ STAR --genomeDir star_indicies/ --runThreadN 12 --outFilterMultimapNmax 5 --outSAMtype BAM SortedByCoordinate --outFilterMismatchNmax 7 --readFilesCommand zcat --outFileNamePrefix Mc_wild --readFilesIn /PATH_TO/M.cerasi/RNAseq/Mc_R1.fq.gz /PATH_TO/M.cerasi/RNAseq/Mc_R2.fq.gz
# sort the bam file
$ samtools sort -@ 16 Mc_wildAligned.sortedByCoord.out.bam mc_sorted
# index the sorted bam file
$ samtools index mc_sorted
#get the depth of coverage at each postition: samtools depth
$ samtools depth mc_sorted.bam > Mc_whole_genome.RNAseq.depth
$ samtools depth Mp_O_RNA_mappedAligned.sortedByCoord.out.bam > Mp_O_RNA.depth
# python to return the cov of ONLY the scaffold of interest
# have to set up a file with the scaffolds of interest in arg.var[2]
$
$ python PATH_TO/Circos_python_scripts/get_scaffold_cov_only.py /PATH_TO/M.cerasi/Mc_whole_genome.RNAseq.depth wanted.scaff > Mc6148_RNAseq.dpeth.out
cd /home/PATH_TO/scratch/diagram_drawing_test/circos/c002_scaffold
python PATH_TO/Circos_python_scripts/get_scaffold_cov_only.py /PATH_TO/Mp_O/Mp_O_host_non_RNAseq_assembly/Mp_whole_genome.RNAseq.depth wanted.scaff > Mp1087439_TGAC_V1.1_scaffold_1256_RNAseq.dpeth.out
python PATH_TO/Circos_python_scripts/get_scaffold_cov_only.py /PATH_TO/wheat_aphid_RNAseq/wheat_whole_genome.RNAseq.depth wanted.scaff > JOTR01000003_RNAseq.dpeth.out
python PATH_TO/Circos_python_scripts/get_scaffold_cov_only.py /PATH_TO/RNAseq_host_non_host/Rp_whole_genome.RNAseq.depth wanted.scaff > Rp1101_RNAseq.dpeth.out
python PATH_TO/Circos_python_scripts/get_scaffold_cov_only.py /PATH_TO/RNAseq_host_non_host/Rp_whole_genome.RNAseq.depth scaff_of_interests.txt > Rp33.RNA.depth.out
#python cov_window_for_covfile.py covfile window_size karyoteyp_file > output_file.txt
python PATH_TO/Circos_python_scripts/cov_window_for_bedfile.py Mc363_RNAseq.dpeth.out 250 ./plotting_files/karyotype.c002_all.txt > Mc363_RNAseq.dpeth.250.window
# fill in the gap in coverage
#python PATH_TO/Circos_python_scripts/fill_in_cov_gaps.py Mp1087439_TGAC_V1.1_scaffold_1256_RNAseq.dpeth.out > temp
python PATH_TO/Circos_python_scripts/cov_window_for_bedfile.py temp 250 ./plotting_files/karyotype.c002_all.txt > Mp1087439_TGAC_V1.1_scaffold_1256_RNAseq.dpeth.out.250.window
python PATH_TO/Circos_python_scripts/cov_window_for_bedfile.py Mp1087439_TGAC_V1.1_scaffold_1256_RNAseq.dpeth.out 250 ./plotting_files/karyotype.c002_all.txt > Mp1087439_TGAC_V1.1_scaffold_1256_RNAseq.dpeth.out.250.window
python PATH_TO/Circos_python_scripts/cov_window_for_bedfile.py Rp1101_RNAseq.dpeth.out 250 ./plotting_files/karyotype.c002_all.txt > Rp1101_RNAseq.dpeth.out.250.window
python PATH_TO/Circos_python_scripts/cov_window_for_bedfile.py JOTR01000003_RNAseq.dpeth.out 250 ./plotting_files/karyotype.c002_all.txt > JOTR01000003_RNAseq.dpeth.out.250.window
#cat the cov plots:
#cat *cov.100.txt > all.RNAseq.dpeth.out.100.windw
cat *out.250.window > all_RNAseq.cov
#############################################################################################################
4) blast the proteins sequences already ...
# sensitive blastx vs nr
# --max-target-seqs 5 if required
diamond blastp -p 16 --sensitive -e 1e-5 -v -q Mc_Mp.fasta -d Mc_Mp.dmnd -a p.Mc_Mp_vs_mc_mp.da
diamond view -a p.Mc_Mp_vs_mc_mp.da*.daa -f tab -o p.Mc_Mp_vs_mc_mp.tab
cp p.Mc_Mp_vs_mc_mp.tab Mc_Mp.blast
# individual species Mc
diamond blastp -p 16 --sensitive -e 1e-10 -v -q ./fastafile/M.cerasi.V1.AA.fasta -d Mc.dmnd -a p.Mc_vs_mc.da
diamond view -a p.Mc_vs_mc.da*.daa -f tab -o p.Mc_vs_mc.tab
cp p.Mc_vs_mc.tab Mc_Mc.blast
# individual species Mp
diamond blastp -p 16 --sensitive -e 1e-10 -v -q ./fastafile/Mp_O_v1.AA.fasta -d Mp.dmnd -a p.Mp_vs_mp.da
diamond view -a p.Mp_vs_mp.da*.daa -f tab -o p.Mp_vs_mp_.tab
cp p.Mp_vs_mp.tab Mp_Mp.blast
#############################################################################################################
5) parse the blast file.
python PATH_TO/Circos_python_scripts/DNA_blast_analysis.py mp1_mpsec5_scff.blast 30 > mc_mp_ribbon.bit30.between.txt
python PATH_TO/Circos_python_scripts/DNA_blast_analysis.py all_vs_all.tab 30 | grep -v ".t2" > all_blast.bit30.between.txt
python PATH_TO/Circos_python_scripts/DNA_blast_analysis.py all_vs_all.tab 50 > all_blast.bit50.between.txt
python PATH_TO/Circos_python_scripts/DNA_blast_analysis.py all_vs_all.tab 70 > all_blast.bit70.between.txt
python PATH_TO/Circos_python_scripts/DNA_blast_analysis.py all_vs_all.tab 1000 > all_blast.bit100.between.txt
python PATH_TO/Circos_python_scripts/DNA_blast_analysis.py all_vs_all.tab 100 | grep -v ".t2" | grep -v ".12" > all_blast.bit100.between.txt
python PATH_TO/Circos_python_scripts/DNA_blast_analysis.py all_vs_all.tab 150 | grep -v ".t2" | grep -v ".12" > all_blast.bit150.between.txt
cat all_blast.bit100.between.txt | grep -v ".t2" > all_blast.bit100.between2.txt
cat all_blast.bit30.between.txt | grep -v ".t2" > all_blast.bit30.between2.txt
cat all_blast.bit70.between.txt | grep -v ".t2" > all_blast.bit70.between2.txt
cat all_blast.bit150.between.txt | grep -v ".t2" > all_blast.bit150.between2.txt
cat all_blast.bit50.between.txt | grep -v ".t2" > all_blast.bit50.between2.txt
rm all_blast.bit100.between.txt
rm all_blast.bit30.between.txt
rm all_blast.bit70.between.txt
rm all_blast.bit150.between.txt
rm all_blast.bit50.between.txt
python PATH_TO/Circos_python_scripts/re_format_blast_results.py -i all_blast.bit50.between2.txt -o temp
python PATH_TO/Circos_python_scripts/re_format_blast_results.py -i all_blast.bit100.between2.txt -o all_blast.bit100.between.txt
python PATH_TO/Circos_python_scripts/re_format_blast_results.py -i all_blast.bit70.between2.txt -o all_blast.bit70.between.txt
python PATH_TO/Circos_python_scripts/re_format_blast_results.py -i all_blast.bit150.between2.txt -o all_blast.bit150.between.txt
python PATH_TO/Circos_python_scripts/re_format_blast_results.py -i all_blast.bit50.between2.txt -o all_blast.bit50.between.txt
python PATH_TO/Circos_python_scripts/re_format_blast_results.py -i all_blast.bit30.between.txt --gff all.gff -o all_blast.bit30.between.genecoordinates.txt
python PATH_TO/Circos_python_scripts/re_format_blast_results.py -i all_blast.bit100.between.txt --gff all.gff -o all_blast.bit100.between.genecoordinates.txt
python PATH_TO/Circos_python_scripts/re_format_blast_results.py -i all_blast.bit150.between.txt --gff all.gff -o all_blast.bit150.between.genecoordinates.txt
the blast file needs to be formatted correctly. - save as file so config can get it
python PATH_TO/Circos_python_scripts/re_format_blast_results.py -i all_blast.bit50.between2.txt -o temp
#scaffold start stop saff2 start stop colour
scaffold_172 103340 104192 Mc363 54754 55592 color=red
scaffold_172 108506 109843 Mc363 60978 61364 color=red
scaffold_172 273725 274104 scaffold_172 482 614 color=lgrey
scaffold_172 297225 301530 scaffold_172 297225 301530 color=lgrey
#############################################################################################################
6) creat a bands file
cat Rpa.v1.gff | grep -Ff RPgenes | grep "gene" | cut -f1,4,5,9 > Rp_gene_coordinates
#saffold start stop tag/info label
scaffold_172 9486 16018 Mpe06376|beat lable=gene
scaffold_172 31923 32321 Mpe06377|NA lable=gene
scaffold_172 47231 47605 Mpe06378|NA lable=gene
scaffold_172 72647 72952 Mpe06379|NA lable=gene
scaffold_172 103340 104192 Mpe06380|LOC100165393 lable=effector
scaffold_172 108506 109843 Mpe06381|LOC100167427 lable=effector
scaffold_172 117114 117401 Mpe06382|NA lable=gene
scaffold_172 120130 120610 Mpe06383|NA lable=gene
scaffold_172 142290 142616 Mpe06384|NA lable=gene
scaffold_172 168389 168634 Mpe06385|NA lable=gene
scaffold_172 169387 171558 Mpe06386|NA lable=gene
scaffold_172 190768 191079 Mpe06387|NA lable=gene
scaffold_172 217249 254885 Mpe06388|thiamine lable=gene
scaffold_172 255459 260980 Mpe06389|nuclear lable=gene
scaffold_172 266885 272296 Mpe06390|polymerase lable=gene
scaffold_172 273725 274104 Mpe06391|prestin lable=gene
scaffold_172 297225 301530 Mpe06392|prestin lable=gene
scaffold_172 366032 366484 Mpe06393|NA lable=gene
Mc363 17340 17753 Mca02123|NA lable=gene
Mc363 18196 18558 Mca02124|NA lable=gene
Mc363 19125 19403 Mca02125|NA lable=gene
Mc363 48996 49592 Mca02126|NA lable=gene
Mc363 54754 55592 Mca02127|LOC100165393 lable=effector
Mc363 60978 61364 Mca02128|Me10 lable=effector
#############################################################################################################
7)
#########################
cd /PATH_TO/Pea_aphid
cat /PATH_TO/Pea_aphid/data/read_R1_Q30paired.fq.gz /PATH_TO/Pea_aphid/data/read2_R1_Q30paired.fq.gz > R1.fq.gz
cat /PATH_TO/Pea_aphid/data/read_R2_Q30paired.fq.gz /PATH_TO/Pea_aphid/data/read2_R2_Q30paired.fq.gz > R2.fq.gz
STAR --genomeDir star_indicies/ --runThreadN 12 --sjdbGTFfile ./A.pisum.gtf --quantMode TranscriptomeSAM --outFilterMultimapNmax 5 --outSAMtype BAM SortedByCoordinate --outSAMmapqUnique 255 --outFilterMismatchNmax 5 --readFilesCommand zcat --outFileNamePrefix Pea --readFilesIn R1.fq.gz R2.fq.gz
#1) create a GC window
# arguments: in.fasta windowsize > pipe_to_file
python PATH_TO/Circos_python_scripts/gc_window_for_sequences.py GL349624.scaffold.fasta 25 > GL349624.scaffold.fasta.gc.25.txt
python PATH_TO/Circos_python_scripts/gc_window_for_sequences.py GL349624.scaffold.fasta 250 > GL349624.scaffold.fasta.gc.250.txt
samtools sort -@ 12 PeaAligned.sortedByCoord.out.bam Pea_sorted
samtools index Pea_sorted.bam
#get the depth of coverage at each postition: samtools depth
samtools depth Pea_sorted.bam > Pea_whole_genome.RNAseq.depth
#GL349624 wanted scaffold
python PATH_TO/Circos_python_scripts/get_scaffold_cov_only.py Pea_whole_genome.RNAseq.depth wanted.scaff > GL349624_RNAseq.depth.out
#python cov_window_for_covfile.py covfile window_size karyoteyp_file > output_file.txt
python PATH_TO/Circos_python_scripts/cov_window_for_bedfile.py GL349624_RNAseq.depth.out 250 /home/PATH_TO/scratch/diagram_drawing_test/circos/mp1_mpsec5/plotting_files/karyotype.Mc.txt > GL349624_RNAseq.depth.out_RNAseq.dpeth.out.250.window
python PATH_TO/Circos_python_scripts/cov_window_for_bedfile.py GL349624_RNAseq.depth.out 100 /home/PATH_TO/scratch/diagram_drawing_test/circos/mp1_mpsec5/plotting_files/karyotype.Mc.txt > GL349624_RNAseq.depth.out_RNAseq.dpeth.out.100.window
python PATH_TO/Circos_python_scripts/cov_window_for_bedfile.py GL349624_RNAseq.depth.out 50 /home/PATH_TO/scratch/diagram_drawing_test/circos/mp1_mpsec5/plotting_files/karyotype.Mc.txt > GL349624_RNAseq.depth.out_RNAseq.dpeth.out.500.window