STEP 1: Base calling and Quality Control (QC)
o Most high throughput sequencers generate output in FastQ format.
o Raw data reads – .fastq (uncompressed) or .fastq.gz (compressed)
| Platform | Basecall File Format | Basecaller |
|---|---|---|
| Illumina | Binary Base Call (BCL) | |
| PacBio | Basecall File (bash.h5/bax.h5) | |
| ONT | FASTQ | Dorado |
o Dorado is a basecaller for Oxford Nanopore Technology (ONT) reads
o Base quality (BQ) score = Phred score. Base quality is important for variant calling.
o Q20 and higher is generally a good score.
o QC tool
- FASTQC is a quality control tool for high throughput sequence data.
- It is written in Java.
- http://www.bioinformatics.babraham.ac.uk/projects/fastqc/
- MultiQC is used to aggregate results from multiple FastQC runs into one single html report
| Platform | QC |
|---|---|
| ONT | NanoQC |
STEP 2: Trimming
o Involves removal of poor quality reads and trim adapter sequences
o Trimming tool
- http://www.usadellab.org/cms/?page=trimmomatic
| Platform | Tool |
|---|---|
| Illumina | BBduk or Cutadapt |
| ONT | Porechop |
STEP 3: Mapping or Alignment
o .sam – sequence alignment map; .bam – binary alignment map; .cram – reference based compressed alignment map
o Mapping quality (MQ) is a phred-score of the quality of the alignment
o Mapping methods
| Burrows-Wheeler | Hashing |
|---|---|
| BWA, Bowtie | Stampy |
o Mapping tools
| Platform | Tool |
|---|---|
| Illumina | BWA MEM |
| ONT | Minimap2 |
o Post-mapping data QC tools
- Qualimap
STEP 4: Variant calling