Table 1 Outline of the GBS-SNP-CROP workflow, featuring inputs and outputs of all seven steps (scripts)

  Step 1 Parse the raw reads

- CASAVA generated paired-end (R1, R2) files (.fastq.gz)

- Parsing summary information (.txt)

2:24

- Read length distribution summary (.txt)

- Barcode-ID file (.txt)

- Parsed paired-end [PE] reads (.fastq)

- Parsed, unpaired R1 reads (.fastq)

  Step 2 Trim based on quality

- Parsed PE reads (.fastq)

- High quality, parsed PE reads (.fastq)

0:10

- High quality, parsed singletons (.fastq)

  Step 3 Demultiplex

- One pair (R1, R2) of high quality files (.fastq) per library

- One pair (R1, R2) of high quality files (.fastq) per genotype

0:16

- Barcode-ID file (.txt)

  Step 4 Cluster reads and assemble the Mock Reference [MR]

- Genotype-specific PE files (.fastq)

- Mock Reference [centroids] (.fasta)

0:14^b

- Barcode-ID file (.txt)

- Mock Reference [genome] (.fasta)

  Step 5 Align with BWA-mem and process with SAM tools

- Genotype-specific high quality PE files (.fastq)

- Filtered reads (.bam)

3:36

- Sorted BAM files (.sorted.bam)

- Reference or MR [genome] (.fasta)

- Indexed BAM files (.sorted.bam.bai)

- Barcode-ID file (.txt)

- Indexed reference or MR (.fasta.idx)

- One base call alignment summary file (.mpileup) per genotype

  Step 6 Parse mpileup output and produce the SNP discovery master matrix

- One base call alignment summary file (.mpileup) per genotype

- One base call alignment summary count file (.txt) per genotype

4:37

- Barcode-ID file (.txt)

- SNP discovery master matrix (.txt)

  Step 7 SNP genotyping across the population

- SNP discovery master matrix (.txt)

- SNP genotyping matrix for the population (.txt)

0:04