Package: exp-selection
ExP SelectionExP heatmap example - LCT geneThis is the ExP heatmap of human lactose (LCT) gene on chromosome 2 and its surrounding genomic region displaying population differences between 26 populations of 1000 Genomes Project, phase 3. Displayed values are the adjusted rank p-values for cross-population extended haplotype homozygosity (XPEHH) selection test.Requirementspython >= 3.8vcftools (repository)space on disk (.vcf files are usually quite large)Installpipinstallexp-selectionWorkflowUsageGet the dataVCF files (e.g.1000 Genomes ProjectandPhase 3, chr22)Panel file (e.g.1000 Genomes Project)Prepare the dataExtract only SNPYou can give an .vcf or .vcf.gz file# we will use SNPs only, so we remove insertion/deletion polymorphisms# another option would be to use only biallelic SNPs (--min-alleles 2 --max-alleles 2),# probably with minor allele frequency above 5% (--maf 0.05)# ouput VCF will be named DATA.recode.vcf# Gziped VCFvcftools--gzvcfDATA.vcf.gz--remove-indels--recode--recode-INFO-all--outDATA# Plain VCFvcftools--vcfDATA.vcf--remove-indels--recode--recode-INFO-all--outDATAPrepare data for computing# DATA.recode.vcf a vcf from previous step# DATA.zarr is path (folder) where zarr representation of the VCF input will be savedexp-selectionprepareDATA.recode.vcfDATA.zarrCompute pairwise values# DATA.zarr a zarr data from previous step# DATA.output a path (folder) where the results will be saved# in this step, by default Cross-population extended haplotype homozygosity (XPEHH) score will be computed for all positions provided together with their -log10 rank p-values.exp-selectioncomputeDATA.zarrgenotypes.panelDATA.outputDisplay ExP heatmap--begin,--end(required)plot boundaries--title(optional)name of the image--cmap(optional)color schemamore informations at seaborn package--output(optional)png output pathexp-selectionplotDATA.output--beginBEING--endEND--titleTITLE--outputNAMEExampleThis example shows an analysis of 1000 Genomes Project, phase 3 data of chromosome 22, chosen especially for its small size and thus reasonable fast computations. It is focused on ADM2 gene (link), which is active especially in reproductive system, and angiogenesis and cardiovascular system in general.# Download datasetswget"ftp.1000genomes.ebi.ac.uk/vol1/ftp/release/20130502/supporting/GRCh38_positions/ALL.chr22_GRCh38.genotypes.20170504.vcf.gz"-Ochr22.genotypes.vcf.gz
wget"ftp.1000genomes.ebi.ac.uk/vol1/ftp/release/20130502/integrated_call_samples_v3.20130502.ALL.panel"-Ogenotypes.panel# The 1000 Genomes Project ftp seems not working, you can get the VCF files (GRCh37 version) at this mirrorwget"https://ddbj.nig.ac.jp/public/mirror_database/1000genomes/release/20130502/ALL.chr22.phase3_shapeit2_mvncall_integrated_v5a.20130502.genotypes.vcf.gz"-Ochr22.genotypes.vcf.gz
wget"https://ddbj.nig.ac.jp/public/mirror_database/1000genomes/release/20130502/integrated_call_samples_v3.20130502.ALL.panel"-Ogenotypes.panel# Compute files for graphvcftools--gzvcfchr22.genotypes.vcf.gz\--remove-indels\--recode\--recode-INFO-all\--outchr22.genotypes

exp-selectionpreparechr22.genotypes.recode.vcfchr22.genotypes.recode.zarr
exp-selectioncomputechr22.genotypes.recode.zarrgenotypes.panelchr22.genotypes.output# Plot heatmapexp-selectionplotchr22.genotypes.output--begin50481556--end50486440--titleADM2--outputadm2_GRCh38
exp-selectionplotchr22.genotypes.output--begin50910000--end50950000--titleADM2--outputadm2_GRCh37# use this plotting if you use GRCh37 version of the VCF input files.# The heatmap is saved as adm2_GRCh38.png or adm2_GRCh37.png, depending on which version of plot function are you using.ContributorsEda Ehler (@EdaEhler)Jan Pačes (@hpaces)Mariana Šatrová (@satrovam)Ondřej Moravčík (@ondra-m)Acknowledgement