One important advantage in plant&animal genetic studies is the availability of experimental populations. A Recombinant Inbred Line (RIL) population can be maintained and used over and over again to map all kinds of different traits. Now, RIL population is not confined to bi-parental RIL population. It can be nested association mapping (NAM) population or multiparent advanced generation intercross (MAGIC) population of arbitrary number of founders. I present a method BCFR for constructing bin-map for RILs of arbitrary number of founders. BCFR use identity by state between RILs and their founders in sliding windows, and a pedigree relationship can be optionally used to refine the bin-map, that is, individuals derived from single F1 hybrid can only have two types of alleles.
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Python (>=3.5.5)
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Click (>=7.0)
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Numpy (>=1.13.1)
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Pandas (>=0.21.0)
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Matplotlib (>=1.5.0)
Unzip the bcfr code and install
unzip bcfr-master.zip
cd bcfr-master
python setup.py install
List all the options and commands:
bcfr --help
Convert the VCF file to bcfr format:
bcfr converter --v my_genotypes.vcf --d output_dir --n number_of_founder
Construct bin map without pedigree:
bcfr birds --n number_of_founder --d output_dir
Construct bin map with pedigree:
bcfr birds --n number_of_founder --d output_dir --p pedigree.txt
Plot individual haplotype map:
bcfr plot-hap --r ril_individual_name --d output_dir
Note: the output_dir should be the same directory in all these steps.
โ pedigree template was offered as foder.txt
bimDic.pkl is the pickled bin map object created by birds command which can be loaded in python:
with open('bimDic.pkl','rb') as f:
bin_size,bin_map=pickle.load(f)
bin_size and bin_map are dictionary with chromosome names as key. bin_size stores the start position and end position of each bin; bin_map stores the genotypes.
The individual-wise haplotype map data was hpfDic.pkl.
The whole genome bin map chart was output as whole_genome_bin_map.jpg:
The plot-hap command output individual haplotype map chart haplotype_ril_individual_name.jpg:
Zhongmin Han - National Key Laboratory of Crop Genetic Improvement, Huazhong Agriculture University
Bin-based genome-wide association analyses improve power and resolution in QTL mapping and identify favorable alleles from multiple parents in a 4-way MAGIC rice population. Theoretical and Applied Genetics by Zhongmin Han, Gang Hu, Hua Liu, Famao Liang, Lin Yang, Hu Zhao, Qinghua Zhang, Zhixin Li, Qifa Zhang, Yongzhong Xing
- Lots of memory and fast disk for large projects