VCF2Dis: an ultra-fast and efficient tool to calculate pairwise genetic distance and construct population phylogeny from VCF files
The VCF2Dis article has been published in GigaScience, please cited this article if possible
Acceptance Date :2025 Mar 5
Publication : GigaScience
Title : VCF2Dis: an ultra-fast and efficient tool to calculate pairwise genetic distance and construct population phylogeny from VCF files
Doi : https://doi.org/10.1093/gigascience/giaf032
-
- Install
The new version will be updated and maintained in hewm2008/VCF2Dis, please click below Link to download the latest version
Just sh make.sh
to compile. The executable VCF2Dis
can be found in the folder of bin/VCF2Dis
For Linux /Unix and macOS
tar -zxvf VCF2DisXXX.tar.gz # if Link do not work ,Try re-install [zlib]library cd VCF2DisXXX; # [zlib] and copy them to the library Dir sh make.sh; # VCF2Dis-xx/src/include/zlib ./bin/VCF2Dis
Note: If fail to link,try to re-install the libraries zlib
Note:: R with ape, dplyr and ggtree are recommended
You can use Docker to install and run VCF2Dis. Follow the steps below:
- Install Docker: Ensure Docker is installed on your system. If not, you can install it by following the Docker Official Documentation.
- Pull the Docker Image: Use the following command to pull the VCF2Dis Docker image from the Alibaba Cloud Container Registry:
docker pull registry.cn-shenzhen.aliyuncs.com/knight134/vcf2dis:v1.53e ## Docker image from the Alibaba Cloud Container Registry docker run -it --rm vcf2dis:v1.53e VCF2Dis ## After pulling the image, you can run the containe
- Install Singularity: Ensure Singularity is installed on your system. If not, you can install it by following the Singularity Official Documentation.
- Build the SIF File: Use the following command to build a Singularity image file (SIF) from the Docker image:
singularity build vcf2dis_1.53e.sif docker://registry.cn-shenzhen.aliyuncs.com/knight134/vcf2dis:v1.53e # you can download follows singularity exec vcf2dis_1.53e.sif VCF2Dis
- Download the SIF File:Alternatively, you can download the built SIF file directly from the vcf2dis_1.53e.sif. Once downloaded, you can run it using Singularity.
-
- Main parameter description:
Usage: VCF2Dis -InPut <in.vcf> -OutPut <p_dis.mat>
-InPut <str> Input one or muti GATK VCF genotype File
-OutPut <str> OutPut Sample p-Distance matrix
-InList <str> Input GATK muti-chr VCF Path List
-SubPop <str> SubGroup SampleList of VCF File [ALLsample]
-Rand <float> Probability (0-1] for each site to join Calculation [1]
-help Show more help [hewm2008 v1.53s]
For more details, please use -help and see the example
-InFormat <str> Input File is [VCF/FA/PHY] Format,defaut: [VCF]
-InSampleGroup <str> InFile of sample Group info,format(sample groupA)
-TreeMethod <int> Construct Tree Method,1:NJ-tree 2:UPGMA-tree [1]
-KeepMF Keep the Middle File diff & Use matrix
Three examples were provided in the directory of example/Example*
-
- To Create the p_distance matrix and construct nj-tree newick tree
# 1.1) To new all the sample p_distance matrix and newick tree based VCF, run VCF2Dis directly
./bin/VCF2Dis -InPut in.vcf.gz -OutPut p_dis.mat
# ./bin/VCF2Dis -InPut in.fa.gz -OutPut p_dis.mat -InFormat FA
# 2.2) To new sub group sample p_distance matrix and and newick tree ; put their sample name into File sample.list
./bin/VCF2Dis -InPut chr1.vcf.gz chr2.vcf.gz -OutPut p_dis.mat -SubPop sample.list
-
- Simple tree visualization (for advanced tree display and annotation please refer to
iTOL
,Evolview
,MEGA
)
you will obtain thep_dis.nwk
tree file and neighbor-joining tree in pdf formatp_dis.pdf
after VCF2Dis.
- Simple tree visualization (for advanced tree display and annotation please refer to
Note::if you can't get the p_dis.nwk tree file but had the p_dis.mat, here are the 3 methods to get the tree file.
-
- Running multiple times by using a method of sampling with replacement. Users can randomly select a part of the sites [-Rand] and construct a new nj-tree as above, and Repeat NN times [recommand NN=100]. X=(1,2....NN);
#!/bin/bash
NN=100
if [ "$#" -eq 1 ]; then
NN=$1
fi
for X in $(seq 1 $NN)
do
./bin/VCF2Dis -InPut in.vcf.gz -OutPut p_dis_${X}.mat -Rand 0.25
# PHYLIPNEW-3.69.650/bin/fneighbor -datafile p_dis_${X}.mat -outfile tree.out1_${X}.txt -matrixtype s -treetype n -outtreefile tree.out2_${X}.tre
done
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- Merge all the nj-tree and construct and display a boostrap nj-tree. (For advanced display tree and annotation please refer to
iTOL
,Evolview
andMEGA
)
- Merge all the nj-tree and construct and display a boostrap nj-tree. (For advanced display tree and annotation please refer to
#!/bin/bash
NN=100
if [ "$#" -eq 1 ]; then
NN=$1
fi
cat p_*.nwk > alltree_merge.tre # cat tree*.tre > alltree_merge.tre
PHYLIPNEW-3.69.650/bin/fconsense -intreefile alltree_merge.tre -outfile out -treeprint Y
perl ./bin/percentageboostrapTree.pl alltree_merge.treefile $NN Final_boostrap.tre # NN is the input number
How to Install PHYLIPNEW please Click on here or Click on here(Chinese)
The formula for calculating p-distance between indivisuals from VCF SNP datasets was listed below:
D_ij=(1/L) * [(sum(d(l)_ij))]
Where L is the length of regions where SNPs can be identified, and given the alleles at position l
are A/C between sample i
and sample j
:
d(l)_ij=0.0 if the genotypes of the two individuals were AA and AA;
d(l)_ij=0.5 if the genotypes of the two individuals were AA and AC;
d(l)_ij=0.0 if the genotypes of the two individuals were AC and AC;
d(l)_ij=1.0 if the genotypes of the two individuals were AA and CC;
d(l)_ij=0.0 if the genotypes of the two individuals were CC and CC;
To further know about the p_distance matrix based the VCF file, please refer to this website.
VCF2Dis have been cited in more than 170 times by searching against google scholar.
Below were some NJ-tree images that I draw in the paper before.
- 50 Rices NBT
- 31 soybeans NG
Display tree by MAGA after test Data VCF2Dis -i ALL.chr*.genotypes.vcf.gz -SubPop subsample203.list -InSampleGroup pop.info
- 📧 hewm2008@gmail.com / hewm2008@qq.com /
- join the QQ Group : 125293663
- other Contributors : Lian Xu (xulian@ntu.edu.cn); Xun Liao (1911751806@qq.com)
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