Quick-start Guide
Quick-start dataset
An quick-start dataset (ciscall-quick-start-dataset.tar.gz
) is prepared here.
This contains the following files:
- fastq files
- Foreground (FFPE sample of tumor tissue)
- Background (Frozen sample of normal tissue)
- asset files
- Target BED
- Fusion BED
- Fusion gene pair
- Human gene BED
- VCF of SNPs
See cisCall Run Command for more details.
Quick-start tutorial using Docker
This tutorial is triable on Linux or macOS.
-
Get the source code of cisCall7 (See Request for Download).
-
Install Docker and Docker Compose.
-
Make a working directory for quick-start.
$ mkdir sandbox $ cd sandbox
-
Download the quick-start dataset.
$ wget https://static.ciscall.org/dataset/ciscall-quick-start-dataset.tar.gz $ tar xvf ciscall-quick-start-dataset.tar.gz $ mv ciscall-quick-start-dataset input
-
Set the environment variables for build and run (optional).
# User ID and Group ID $ export UID="$(id -u)" GID="$(id -g)" # HTTP proxy (if it exists) $ export http_proxy='http://example.proxy.com:8080/' $ export https_proxy='https://example.proxy.com:8080/'
UID
andGID
are used for ownership of output files from a container, andhttp_proxy
andhttps_proxy
are used for image build under proxy. -
Build an image of cisCall.
$ tar xvf /path/to/cisCall7.tar.gz $ docker-compose -f cisCall7/docker-compose.yml build
-
Create
docker-compose.yml
in the current directory (Copy the following YAML snippet).docker-compose.yml
:--- version: '3' services: ciscall: container_name: ciscall image: ciscall:latest user: ${UID}:${GID} volumes: - .:/sandbox working_dir: /sandbox command: - run - --analysis-mode - MUTON:WGENOME - CTON:WGENOME - FUSION:WGENOME - --work-dir=./ - --fg-r1-fastq=./input/test_tumor.fastq.R1.gz - --fg-r2-fastq=./input/test_tumor.fastq.R2.gz - --bg-r1-fastq=./input/test_normal.fastq.R1.gz - --bg-r2-fastq=./input/test_normal.fastq.R2.gz - --target-bed=./input/TESTPANEL.target.bed - --fusion-bed=./input/TESTPANEL.fusion.bed - --genome-fa=./input/ucsc_human_b37_chr1-22-X-Y-M.fa - --refgene-txt=./input/refGene.txt - --snp-vcf=./input/test_snp.vcf.gz - --mapability-bigwig=./input/wgEncodeDukeMapabilityUniqueness20bp.bigWig - --gene-bed=./input/hg19.gene.bed - --fusion-gene-txt=./input/main_fusion_gene.txt - --gene-family-txt=./input/genefamilies.txt - --decoy-fa=./input/hs37d5cs.fa - --random-seed=0
The command written in the above file is equivalent to the following command:
$ ciscall run \ --analysis-mode MUTON:WGENOME CTON:WGENOME FUSION:WGENOME \ --work-dir ./ \ --fg-r1-fastq ./input/test_tumor.fastq.R1.gz \ --fg-r2-fastq ./input/test_tumor.fastq.R2.gz \ --bg-r1-fastq ./input/test_normal.fastq.R1.gz \ --bg-r2-fastq ./input/test_normal.fastq.R2.gz \ --target-bed ./input/TESTPANEL.target.bed \ --fusion-bed ./input/TESTPANEL.fusion.bed \ --genome-fa ./input/ucsc_human_b37_chr1-22-X-Y-M.fa \ --refgene-txt ./input/refGene.txt \ --snp-vcf ./input/test_snp.vcf.gz \ --mapability-bigwig ./input/wgEncodeDukeMapabilityUniqueness20bp.bigWig \ --gene-bed ./input/hg19.gene.bed \ --fusion-gene-txt ./input/main_fusion_gene.txt \ --gene-family-txt ./input/genefamilies.txt \ --decoy-fa ./input/hs37d5cs.fa \ --random-seed 0
-
Check installation.
$ docker-compose run --rm ciscall --version
-
Download additional asset data.
$ docker-compose run --rm ciscall download-asset --dest-dir ./input
-
Execute variant calling with cisCall.
$ docker-compose up $ docker-compose rm -f # remove a container
-
Check results of variant calling
Results are generated in
output/
under a working directory (./work
in this page.).- SNVs/Indels
- result directory:
output/test_tumor/Muton/
- VCF file for finally called variant:
output/test_tumor/Muton/muton_wgenome.vcf
- result directory:
- Copy number alterations
- result directory:
output/test_tumor/Cton/
- VCF file for finally called variant:
output/test_tumor/Cton/gene.cnv_target_dup.vcf
- result directory:
- Fusion genes
- result directory:
output/test_tumor/Fusion/
- VCF files for finally called variant:
output/test_tumor/Fusion/AlnWgenome_LmtOneside_Paired.vcf
output/test_tumor/Fusion/AlnWgenome_LmtOneside_Paired_sv.vcf
- result directory:
- SNVs/Indels
See the following pages for more details: