We proposed a framework to capture individual-specific DNA microbial fingerprints from 616 skin metagenomic sequencing data. The fingerprints are identified on the frequency of 31-mers free from reference genomes and sequence alignments. Ultimately, one contig for each individual is assembled as a fingerprint. And results showed that 89.78% of the skin samples despite of body sites could identify their donors correctly.
An demo of fingerprint running is given here.
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If you first use, please type the command:
sudo chmod +x ./bin/* -
Get kmer matrix of all data:
python3 KmerGO_for_cmd.py [optional options] -i <input_files_folder> -t <input_trait_information> -
Split dataset and get individual-specific kmer in details:
python3 split_matrix_train_and_test.py -
Processing file formats for subsequent runs:
python3 get_kmer.py -
Obtain individual-specific contigs by cap3:
./bin/cap3 <input_files> [optional options]
The dataset was randomly generated. There were 20 contigs only exists in HV01.Testing dataset Download
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Get kmer matrix of all data, the results save in ./kmer_matrix/son_matrix_*.txt.
python3 KmerGO_for_cmd.py -k 25 -ci 1 -cs 1000000000 -n 16 -i ./Demo_data -t trait information.csv -
Split dataset to train and test and save individual specific kmer with details in train_specific_kmer_09.txt for training data and kmer_details.txt for testing data.
python3 split_matrix_train_and_test.py -i input_kmer_matrix_folder -fon final_output_file_name -
Processing file formats for subsequent runs. The output file is output_kmer.fa.
python3 get_kmer.py -
Using software(cap3) to obatin individual-specific contigs. The contigs file is under the same path as the output_kmer.fa file with name output_kmer.fa.cap.contigs.
./bin/cap3 output_kmer.fa -i 30 -j 31 -o 18 -s 300
Please send bug reports, comments, or questions to
Prof. Ying Wang: wangying@xmu.edu.cn
Yiluan Zheng: 23220191151270@stu.xmu.edu.cn