BaseVar is a specialized tool tailored for variant calling using ultra low-depth (<1x) sequencing data, particularly catering to non-invasive prenatal test (NIPT) data in human genetic studies. Leveraging maximum likelihood and likelihood ratio models, BaseVar accurately identifies polymorphisms at genomic positions and calculates allele frequencies. For in-depth mathematical explanations, refer to the comprehensive documentation available here.
Now, BaseVar has been fully implemented by C++. BaseVar showcases significant enhancements over its original Python counterpart. The C++ implementation delivers a computing speed exceeding 20 times that of the Python version, all while demanding substantially less memory. Typically, each thread (-t/--thread) consumes merely 3GB to 4GB of memory when the -B (--batch-count) option is configured to 200, a stark contrast to the Python version's requirement of over 20GB.
Please cite the follow paper if you use BaseVar in your publish projects or papers.
Liu, S., Huang, S., Chen, F., Zhao, L., Yuan, Y., Francis, S.S., Fang, L., Li, Z., Lin, L., Liu, R., et al. (2018). Genomic Analyses from Non-invasive Prenatal Testing Reveal Genetic Associations, Patterns of Viral Infections, and Chinese Population History. Cell 175, 347–359.e14. doi:10.1016/j.cell.2018.08.016.
BaseVar requires C++17 or higher. Compile the program from source codes step-by-step.
1. Download BaseVar from github
BaseVar is hosted on Github and can be downloaded with the following command:
$ git clone --recursive https://github.com/ShujiaHuang/basevar.gitWARNING: Please try several times if fail to clone the data causing by the network problem.
2. Navigate into htslib/htscodecs folder and run the following commands
After cloing, navigate into the basevar folder (cd basevar) and execute the following:
$ cd htslib/htscodecs
$ autoreconf -i
$ ./configure
$ make
3. Go back to the upper folder and install main htslib by running following commands
$ cd htslib
$ autoreconf -i
$ ./configure
$ make
Note: If you encounter an error message similar to the following during the compilation of htslib, you can safely disregard it as the code should continue to function properly:
test/test_khash.c: In function 'write_stats_str2int':
test/test_khash.c:53:9: warning: implicit declaration of function 'kh_stats' [-Wimplicit-function-declaration]
53 | if (kh_stats(str2int, h, &empty, &deleted, &hist_size, &hist) == 0) {
| ^~~~~~~~
test/test_khash.c:53:18: error: 'str2int' undeclared (first use in this function)
53 | if (kh_stats(str2int, h, &empty, &deleted, &hist_size, &hist) == 0) {
| ^~~~~~~
test/test_khash.c:53:18: note: each undeclared identifier is reported only once for each function it appears in
make: *** [test/test_khash.o] Error 1Feel free to proceed with your installation tasks despite encountering this error during the compilation process.
4. Go back to the upper directory and install basevar by running the commands below
Navigate into bin/ folder (cd basevar/bin) first and execute the following commands:
For Linux
$ cd bin/
$ g++ -O3 -fPIC ../src/main.cpp ../src/basetype.h ../src/basetype.cpp ../src/basetype_caller.cpp ../src/utils.cpp ../src/fasta.cpp ../src/bam_header.cpp ../src/bam.cpp ../src/bam_record.cpp ../src/basetype_utils.cpp ../htslib/libhts.a -I ../htslib -lz -lbz2 -lm -llzma -lpthread -lcurl -lssl -lcrypto -o basevarFor MacOS
$ cd bin/
$ g++ -O3 -fPIC ../src/main.cpp ../src/basetype.h ../src/basetype.cpp ../src/basetype_caller.cpp ../src/utils.cpp ../src/fasta.cpp ../src/bam_header.cpp ../src/bam.cpp ../src/bam_record.cpp ../src/basetype_utils.cpp ../htslib/libhts.a -I ../htslib -lz -lbz2 -lm -llzma -lpthread -lcurl -o basevar
To review each of the parameters, you can type basevar basetype -h in the Linux/MacOS Terminal.
$ /path/to/basevar basetype -h
BaseVar: A software for calling variants efficiently from low-pass whole genome sequencing data.
About: Calling variants by BaseVar.
Usage: basevar basetype [options] <-R Fasta> <--output-vcf> <--output-cvg> [-I input] ...
optional arguments:
-I, --input=FILE BAM/CRAM file containing reads.
-L, --align-file-list=FILE BAM/CRAM files list, one file per row.
-R, --reference FILE Input reference fasta file.
-m, --min-af=float Setting prior precision of MAF and skip uneffective caller positions.
Usually you can set it to be min(0.001, 100/x), x is the number of input
BAM files.[min(0.001,100/x)]. In generally, you don't have to worry about
this parameter.
-q, --mapq=INT Only include reads with mapping quality >= INT. [10]
-B, --batch-count=INT INT simples per batchfile. [200]
-t, --thread=INT Number of threads. [4]
-G, --pop-group=FILE Calculating the allele frequency for specific population.
-r, --regions=chr:start-end Skip positions which not in these regions. This parameter could be a list
of comma deleimited genome regions(e.g.: chr:start-end) or a file contain
the list of regions.
--output-vcf FILE Output VCF file.
--output-cvg FILE Output position coverage file.
--filename-has-samplename If the name of bamfile is something like 'SampleID.xxxx.bam', set this
argrument could save a lot of time during get the sample id from BAMfile
header information.
--smart-rerun Rerun process by checking batchfiles.
-h, --help Show this help message and exit.This command will provide detailed information about the parameters of basevar.
basevar basetype -R reference.fasta \
-B 200 -t 4 \
-I 00alzqq6jw.bam \
-I 09t3r9n2rg.bam \
-I 0fkpl1p55b.bam \
-I 13dg1gvsfk.bam \
-I 17phildszl.bam \
-I 1dbpgqt0dq.bam \
-I 1kyws27hoc.bam \
--pop-group=sample_group.info \
--regions=chr11:5246595-5248428,chr17:41197764-41276135 \
--output-vcf test.vcf.gz \
--output-cvg test.cvg.tsv.gzThe format of sample_group.info could be found here.
basevar basetype -R reference.fasta -B 200 -t 4 \
-L bamfile.list \
--regions=chr11:5246595-5248428,chr17:41197764-41276135 \
--output-vcf test.vcf.gz \
--output-cvg test.cvg.tsv.gzBaseVar is under active development. Obtain the newest version by pulling the newest version and compilling again.
