SimulatedReads_v1.0.0

1.0.0

Initial release

This workflow perform simulations of one or more (defined by number_of_families) bi-parental outcrossing population haplotypes using PedigreeSim software based on a provided linkage map and SNP markers. It uses RADinitio software, the simulated haplotypes and a reference genome to also simulate genotyping-by-sequencing read sequences. After, it performs the SNP and genotype calling and builds 68 linkage maps from the combinations:

• SNP calling: GATK and Freebayes
• Dosage/genotype calling: updog, polyRAD and SuperMASSA
• Linkage map build software: OneMap 3.0 and GUSMap
• Using genotype probabilities from GATK, Freebayes, updog, polyRAD and SuperMASSA, and a global error rate of 5% and 0.001% in the OneMap HMM.

It also has the options to:

• Include or not multiallelic (MNP) markers
• Apply filters using VCFtools

This workflow uses:

• A reference linkage map
• A reference VCF file
• A single chromosome from a reference genome
• Diploid bi-parental F1 population
• Genomic positions for markers order

PreprocessingReads_v1.0.0

1.0.0

Initial release

This workflow use STACKS process_radtags plugin to demultiplex GBS FASTQ files, filter by presence of the enzyme cut site and sequence quality. The cutadapt software is also implemented to remove adaptors sequences.

This workflow requires:

EmpiricalSNPCalling_v1.0.0

1.0.0

Initial release

This workflow performs the alignment of FASTQ to a reference genome, SNP calling with GATK tools (HaplotypeCaller, GenomicsDBImport, and GenotypeGVCFs) and Freebayes. The samples are splitted into chunks to be run in different nodes and optimize the analyses. Set the number of samples by chunk in the 'chunk_size' input. Use 'max_cores' to define number of cores to be used in each node.

The workflow also include de options to:

• Remove of not the read duplicates
• Perform the Hard Filtering in GATK results
• Replace the VCF AD format field by counts from BAM files
• Run MCHap software to build haplotypes based on GATK called markers

This workflow requires:

• Diploid or polyploid specie
• Single-end reads

EmpiricalMaps_v1.0.0

1.0.0

Initial release

This workflow receives as input VCF files from EmpiricalSNPCalling workflow and result in 34 linkage maps for a single chromosome running the combinations:

• SNP calling: GATK and Freebayes
• Dosage/genotype calling: updog, polyRAD and SuperMASSA
• Linkage map build software: OneMap 3.0 and GUSMap
• Using genotype probabilities from GATK, Freebayes, updog, polyRAD and SuperMASSA, and a global error rate of 5% and 0.001% in the OneMap HMM.

It also has the options to:

• Include or not multiallelic (MNP) markers
• Apply filters using VCFtools

This workflow uses:

• Diploid bi-parental F1 population
• Genomic positions for markers order

SimulatedReads_develop

1.0.0

Initial release

This workflow perform simulations of one or more (defined by number_of_families) bi-parental outcrossing population haplotypes using PedigreeSim software based on a provided linkage map and SNP markers. It uses RADinitio software, the simulated haplotypes and a reference genome to also simulate genotyping-by-sequencing read sequences. After, it performs the SNP and genotype calling and builds 68 linkage maps from the combinations:

• SNP calling: GATK and Freebayes
• Dosage/genotype calling: updog, polyRAD and SuperMASSA
• Linkage map build software: OneMap 3.0 and GUSMap
• Using genotype probabilities from GATK, Freebayes, updog, polyRAD and SuperMASSA, and a global error rate of 5% and 0.001% in the OneMap HMM.

It also has the options to:

• Include or not multiallelic (MNP) markers
• Apply filters using VCFtools

This workflow uses:

• A reference linkage map
• A reference VCF file
• A single chromosome from a reference genome
• Diploid bi-parental F1 population
• Genomic positions for markers order