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Best Practices
1. scan : scan the reference genome to get microsatellites information
msisensor-pro scan -d /path/to/reference.fa -o /path/to/reference.list
This module scans the reference genome to get microsatellites information. You need to input (-d) a reference file (*.fa or *.fasta), and you will get a microsatellites file (-o) for following analysis.
2. baseline : build baseline for tumor only detection
msisensor-pro baseline -d /path/to/reference.list -i /path/to/configure.txt -o /path/to/baseline/directory
This module builds baseline for the input microsatellites (-d) from the scan module output or our github. You also need to offer some normal sample sequence data (-i,click here for more detail about configure file) from the sample sequencing center or platform and the output directory (-o).
3. pro : evaluate MSI using single (tumor) sample sequencing data
msisensor-pro pro -d /path/to/baseline/directory/reference_baseline.list -t /path/to/tumor/case1_sorted.bam -o /path/to/output
This module scores the MSI using the tumor only sequence data. You need to offer the microsatellites with baseline (-d) from the baseline module, the aligned sequencing file (-t) and the output prefix (-o).
1. scan : scan the reference genome to get microsatellites information
msisensor-pro scan -d /path/to/reference.fa -o /path/to/reference.site
This module scans the reference genome to get microsatellites information. You need to input (-d) a reference file (*.fa or *.fasta), and you will get a microsatellites file (-o) for following analysis.
2. msi : evaluate MSI using paired tumor-normal sequencing data
msisensor-pro msi -d /path/to/reference.site -n /path/to/case1_normal_sorted.bam -t /path/to/case1_tumor_sorted.bam -o /path/to/output
This module scores the MSI using the tumor-normal paired sequeuence data. You need to offer the microsatellites (-d) from the scan module or our github (GRCh38.d1.vd1 ), the aligned sequencing file (-t ,-o ) and the output prefix (-o).