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Visualization of genotype profiles on population genomics data for detection of abnormal genotypes pattern.

Project description

Pop-Con: a tool to visualize genotype profiles on Site Frequency Spectrum


Pop-Con is a tool designed to visualize genotype profiles of a Site Frequency Spectrum (SFS) from a Variant Calling Format (VCF) file [1] for SNP and indel variant. We define a genotype profile as the list of genotypes for all individuals at a given site. For example, "0/1,1/1,0/1,0/1" is the genotype profile corresponding to the VCF line below:

Dst_b1v03_scaf00008 54329 . G A 1970.68 PASS AC=6;AF=0.500;AN=12;BaseQRankSum=-6.140e-01;ClippingRankSum=0.00;DP=144;ExcessHet=4.8280;FS=6.723;MLEAC=5;MLEAF=0.417;MQ=60.00;MQRankSum=0.00;QD=15.28;ReadPosRankSum=-8.460e-01;SOR=0.440 GT:AD:DP:GQ:PL 0/1:16,22:38:99:558,0,409 1/1:1,11:12:3:309,3,0 0/1:26,28:54:99:750,0,617 0/1:8,11:19:99:286,0,203

Pop-Con takes as input a VCF file and uses the cyvcf2 python package [2] to read and parse the VCF file To be readable and parsable by cyvcf2 the VCf file has to be compressed and indexed with one of the 2 following command lines:

bgzip input_vcf_file.vcf
tabix -p input_vcf_file.vcf.gz


bcftools view input_vcf_file.vcf -Oz -o input_vcf_file.vcf.gz
bcftools index input_vcf_file.vcf.gz

Pop-Con has been developped on VCF files produced with GATK [3] and read2snp [4] variant callers. Variant caller used to produced VCF file has to be given with option --tool (GATK is the default variant caller).

--read and --marft filtering options can be used to test different set of genotype filtering:

  • --read option take as input a list of read coverage threshold. Genotype with read coverage lower than threshold will be tagged lowCov
  • --marft option take as input a list of minor allele read frequency threshold. Genotype with minor allele read frequency lower than threshold will be tagged lowMARF

For each filtering combination ("read coverage" + "minor allele read frequency"), Pop-Con plots 2 figures (for SNP and indel):

  1. with sites where all individuals are genotyped and passed read coverage and minor allele read frequency filtering.
  2. with all sites where at least 1 individual is genotyped and passed read coverage and minor allele read frequency filtering.

For figure 1, two plots are produced:

  • an upper plot representing the observed proportion of the X most represented genotype profiles for each SFS pic (X is set with the --max_profiles option)
  • a lower plot representing for each pic the expected proportion of genotype profile under the Hardy-Weinberg equilibrium. Genotype profiles are colored in red if observed genotype profile is 2 times upper Hardy-Weinberg expectation, blue if 2 times lower and grey if at equilibrum (between 2 times upper and 2 times lower).

For figure 2, only SFS plot with observed genotype profiles proportion is produced. This plot can be used to detect abnormal porpotion of low read coverage, low minor allele read frequency or ungenotyped individuals.

Pop-Con is supported on Linux with python2 (version==2.7) and python3 (versions>=3.4).


Source from GitHub

This assumes that you have the python modules cyvcf2, numpy and matplotlib installed (cf requirements.txt).

git clone
cd Pop-Con
python ./Pop-Con

Using pip (recommended)

sudo pip install Pop-Con

Manual installation

In the Pop-Con folder where "" is located, run:

sudo python install

If you encountered problem during the installation of cyvcf2, you have to install it manually from the source:


usage: Pop-Con [-h] -i VCF_FILE
               [-m MARFT [MARFT ...]] [-f VARIANT_CALLER_FILTERING]
               [-fmono MONOMORPH_FILTERING] [-t VARIANT_CALLER] [-p PREFIX]
               [-sep SEP] [-max MAX_PROFILES]

Pop-Con - A tool for Population genomic Conflicts detection.

optional arguments:
  -h, --help            show this help message and exit
  -i VCF_FILE, --input_file VCF_FILE
                        Variant Calling Format file containing variant calling
                        List of read coverage threshold filtering for each
                        genotype. Values range: [0,infinity[. (Default: 0)
  -m MARFT [MARFT ...], --marft MARFT [MARFT ...]
                        List of Minor Allele Read Frequency threshold for
                        heterozygote genotypes filtering. Values range:
                        [0.0,0.5]. (Default: 0.0)
                        Boolean to set if variant caller filtering is consider
                        or not. (if "True", sites with TAG column are not
                        empty are filtered out from analysis). (Default: True)
                        Boolean to set if monomorph have to be filtered out.
                        (if "True", monomorph sites will be filtered out from
                        analysis). (Default: False)
                        Variant calling tool used to call variant. Values:
                        "read2snp" or "GATK". (Default: "GATK")
  -p PREFIX, --prefix PREFIX
                        Experiment name (used as prefix for output files).
                        (Default: "exp1")
  -v VERBOSE, --verbose VERBOSE
                        Verbose intensity. (Default: 1)
  -o OUTPUT_DIR, --output OUTPUT_DIR
                        Output directory path. (Default: ./)
                        Boolean to set if the heterozygosity files
                        (summarizing VCF file for each combination of read
                        coverage and MARF threshold filtering) have to be
                        written or not. (Default: True)
  -sep SEP, --separator SEP
                        Separator used in genotype profiles. (Default: ",")
  -max MAX_PROFILES, --max_profiles MAX_PROFILES
                        Maximum number of genotype profiles displayed in SFS
                        plot. (Default: 10)

Source code and manual:


Below, the minimal command line to run Pop-Con:

python Pop-Con -i input_vcf_file.vcf.gz

If the VCF file contains SNP and indel variants, Pop-Con will create two directories "SNP/" and "indel/" in current directory.

Below, an example on VCF file present in directory "example/data/Lineus_longissimus/":

python Pop-Con -i example/data/Lineus_longissimus/Lineus_longissimus_read10_par0.vcf.gz -p Lineus_longissimus -o example/results/Lineus_longissimus/ -t read2snp -fmono True -max 20

Below the architecture of the output directory "example/results/Lineus_longissimus/" produced by Pop-Con with command line above:

└── SNP
	├── heterozygosity
	│   └──
	└── MARFt0.0
		├── heterozygosity
		│	└── read0
		│		├──
		│	    ├──
		│		├──
		│		└──
		└── SFS_profiles
			└── read0
				├── SFSplot_genotypes_profiles_read0_Lineus_longissimus_SNP_MARFt0.0_max20_all_positions.pdf
				└── SFSplot_genotypes_profiles_read0_Lineus_longissimus_SNP_MARFt0.0_max20.pdf

The 2 SFS plot with genotype profiles produced:

For sites where all individuals are genotyped and passed read coverage + minor allele read frequency filtering

File: "SFSplot_genotypes_profiles_read0_Lineus_longissimus_SNP_MARFt0.0_max20.pdf" Lineus longissimus SFS plot with genotype profiles (only individuals genotyped)

For sites where at least 1 individual is genotyped and passed read coverage + minor allele read frequency filtering

File: "SFSplot_genotypes_profiles_read0_Lineus_longissimus_SNP_MARFt0.0_max20_all_positions.pdf" Lineus longissimus SFS plot with genotype profiles (all positions)


[1] Danecek, P. et al. The variant call format and VCFtools. Bioinformatics 27, 2156–2158 (2011). [2] Pedersen, B. S. & Quinlan, A. R. cyvcf2: fast, flexible variant analysis with Python. Bioinformatics 33, 1867–1869 (2017). [3] McKenna, A. et al. The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297–1303 (2010). [4] Gayral, P. et al. Reference-Free Population Genomics from Next-Generation Transcriptome Data and the Vertebrate–Invertebrate Gap. PLOS Genetics 9, e1003457 (2013).


For R lovers, there is an extra script ("scripts/SFS_genotypes_profiles_plot.R") to plot SFS with genotype profiles from file. Example:

Rscript ./scripts/SFS_genotypes_profiles_plot.R example/results/Lineus_longissimus/SNP/MARFt0.0/heterozygosity/read0/ 20 6 Lineus_longissimus example/results/Lineus_longissimus/SNP/MARFt0.0/SFS_profiles/read0/SFSplot_genotypes_profiles_read0_Lineus_longissimus_SNP_MARFt0.0_max20_with_Rscript.pdf 0

This script only plot SFS with observed porportion of genotype profiles and the one with comparison to the expected values under the Hardy-Weinberg equilibrium: Lineus longissimus SFS plot with genotype profiles (only individuals genotyped) with Rscript


Yoann Anselmetti :

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