客户需要使用hg38基因组进行融合基因的分析及可视化。
目前国内流程暂无针对于hg38基因组的高级分析。
融合基因及分析及可视化。
1. somatic的sv检测结果:
*crest.somatic.sv.predSV.txt/*lumpy.somatic.sv.vcf.gz
1. 融合基因检测:
python /PUBLIC/software/CANCER/Module/CancerGenome/Advance/FusionGene.py -i info.list -o ./FusionGenes -s crest
info.list格式:
#样本名 | *somatic.sv.predSV.txt |
---|---|
B4T | B4T.somatic.sv.predSV.txt |
B9T | B9T.somatic.sv.predSV.txt |
2. 可视化:
/PUBLIC/software/public/Graphics/circos-0.64/bin/circos -conf PC9_ER.circos.conf -outputfile sample -outputdir ./
conf格式 :
karyotype =/PUBLIC/software/public/Graphics/circos-0.64/data/karyotype/karyotype.human.txt chromosomes_units = 1000000 <colors> ctx = chr6 itx = chr14 </colors> «include ideogram.conf» «include ticks.conf» #The remaining content is standard and required. <image> «include etc/image.conf» </image> «include etc/colors_fonts_patterns.conf» «include etc/housekeeping.conf» data_out_of_range* = trim <plots>
</plots> <links> z = 50 radius = 0.97r crest = 1 bezier_radius = 0r bezier_radius_purity = 0.2 <link> thickness = 10 file = ./PC9_ER.circos.input </link> </links>
示例脚本:
/TJNAS01/AFS_RESEQ/Proj/hongxiang/05.AFS/FusionGenes/FusionGenes_crest/PC9_ER/PC9_ER.crest.annotate.sh