This article explains how to set up the environment required
to use the FASTQ to VCF (RNA-Seq) tool in Subio Platform for Windows.
For the macOS setup instructions, see
Setting Up the FASTQ to VCF (RNA-Seq) Environment on macOS.
Before You Begin
Before proceeding, complete the WSL, fastp, and HISAT2 setup described in Setting Up the RNA-Seq FASTQ Processing Pipeline on Windows. These components are also used by FASTQ to VCF (RNA-Seq), so their setup is not repeated here.
Environment Settings Panel
FASTQ to VCF (RNA-Seq) also requires Java 17, GATK, Python 3, and additional reference data. We have confirmed that the tool works with Java 17 and GATK 4.7.0.0.
The GATK Resource Bundle provides reference data for human genome assemblies (b37/hg19 and GRCh38/hg38). The reference data used by this tool are intended for human analysis, so other species are not supported.
The GRCh38 index distributed through the official HISAT2 website uses chromosome names without the "chr" prefix, such as "1". In contrast, the GATK reference data use chromosome names with the prefix, such as "chr1". Using these files together without matching the chromosome names causes errors. To resolve this issue, we provide a HISAT2 Index with "chr" prefixes and a corresponding GTF file for GRCh38. Download and extract the ZIP files before using them.
1. Java 17 Executable
Download the Linux x64 JDK for Java 17 from
Eclipse Temurin.
Extract the downloaded archive.
In the Subio Platform settings panel, specify the path
to the bin/java executable in the extracted directory.
2. GATK jar Executable
Open the official GATK releases page
and download the tested version,
gatk-4.7.0.0.zip.
Extract the ZIP file.
In the Subio Platform settings panel, specify the path to
gatk-package-4.7.0.0-local.jar in the extracted directory.
3. Python 3 Executable
Specify a version of Python 3 that can run the HISAT2
hisat2-inspect utility.
In the Subio Platform settings panel,
click the "Find" button next to the Python 3 field.
If compatible Python installations are found,
they will be displayed as candidates.
Select one from the list.
If no candidates appear, install a compatible Python version
and click "Find" again.
HISAT2 2.2.1 requires the imp module,
which was removed in Python 3.12.
Therefore, use Python 3.11 or earlier.
If you need to install Python 3.11 separately,
you do not need to replace the existing system Python.
4. GTF/GFF3 File
For GRCh38, download the GTF file here. This file differs from the original Ensembl GTF file in that the "chr" prefix has been added to chromosome names. To ensure compatibility, use it together with the HISAT2 Index with "chr" prefixes.
5. dbSNP VCF File
Download the file from
gcp-public-data--broad-references.
For GRCh38, download
Homo_sapiens_assembly38.dbsnp.vcf
from the hg38/v0 folder.
6–7. Known Indels VCF Files
As with dbSNP, download
Homo_sapiens_assembly38.known_indels.vcf
and Mills_and_1000G_gold_standard.indels.hg38.vcf
from the
hg38/v0 folder.
If the files are not listed on the first page, check the second page.
About VCF File Extensions
Files listed with a .vcf.gz extension on Google Cloud
may have a different extension, such as .vcf,
after downloading.
Both uncompressed VCF files and gzip-compressed VCF files are supported,
but make sure the file extension matches the actual file format.
Using GRCh37 (hg19)
When analyzing data using GRCh37 (hg19), use the HISAT2 Index (grch37_genome.tar.gz) provided on the official HISAT2 website and a corresponding GRCh37 GTF file. For dbSNP and Known Indels, use the following files.
- hg19_v0_Homo_sapiens_assembly19.dbsnp138.vcf.gz
- hg19_v0_Homo_sapiens_assembly19.known_indels.vcf.gz
- hg19_v0_Mills_and_1000G_gold_standard.indels.b37.vcf.gz
Use grch37_genome.tar.gz as the HISAT2 Index, not hg19_genome.tar.gz. The GTF and VCF files used here have chromosome names without the "chr" prefix.