CloudMap2

A bulked segregant mapping tool that finds regions of linkage on each chromosome, color-codes SNPs in that region according to their source (e.g. EMS), and uses kernel density estimation to predict position of most likely causal SNP. Provides more accurate mapping than the original CloudMap.

Currently only supports C. elegans genome.

Inputs:

1. A list of GATK-called homozygous SNPs from pooled F2 strains with known Hawaiian mapping strain SNPs subtracted. < Bulked Segregant SNPs with mapping strain SNPs subtracted >

2. A list of GATK-called allele ratios (e.g. https://galaxyproject.org/) from pooled F2 strains at mapping strain SNP positions only. For example, if crossing an EMS mutagenized C. elegans strain to a Hawaiian mapping strain (CB4856), you would call SNPs at Hawaiian SNP positions only. < Allele ratios at mapping strain SNP positions >

Output:

A map of linked chromosomal regions with color-coded variants of interest.

gray: Non-EMS derived parental SNPs (e.g. due to genetic drift with respect to N2)

blue: SNPs likely caused by EMS.

red: For the purposes of paper figures, can plot the known causal variant in the context of other linked SNPs.

Linked regions with 3 or more SNPs have a predicted position of most likely causal SNP using kernel density estimation.

Usage:

python cloudmap2.py < Bulked Segregant SNPs with mapping strain SNPs subtracted > < Allele ratios at mapping strain SNP positions > -o <output pdf>

Simple Demo:

python cloudmap2.py Galaxy40-\[ot785HA_WS245_Homozygous_variants_SubtractedHobertHawaiianHomozygousAndHeterozygous\].vcf Galaxy45-\[ot785HA_VariantsAtHighQualityHAPositions_MQ30_WS245_DP_0_BiallelicPositions_SNPsOnly\].vcf -o ot785.pdf