Installation & Quickstart:

Prerequisite tools

• Note: you will need to include the directory containing runnable UCSC blat in your PATH (or set the parameter blat_path for misaligned_reads_filter).

  
  

Download the MosaicHunter program and the required resource files

• Clone the MosaicHunter repository

•    cd your_path

•    git clone https://github.com/zzhang526/MosaicHunter.git

• Some large required resource files (gzip-compressed) can be accessed by URL

  1.human_g1k_v37.fasta

  2.dbsnp_137.b37.tsv

• You also need to download these files, and move them into your_path/resources/ directory.

Quick usage of a pre-compiled binary code release

• In order to make it easy to install MosaicHunter, we have provided the pre-compiled release, which is in the unpacked build/ directory. To use it, simply type:

  
  

•    cd your_path/MosaicHunter

•    java -jar build/mosaichunter.jar

Build MosaicHunter from source




• We also provide the source code of MosaicHunter. If you want to build it from source, you need to install ant first (http://ant.apache.org/bindownload.cgi), then type:

•    cd your_path/MosaicHunter

•    ant

• The newly compiled mosaichunter.jar file will overwrite the pre-compiled one in build/ directory, and you can run MosaicHunter with:

•    java -jar build/mosaichunter.jar

Preparing your reference:




• MosaicHunter requires a fasta file (.fasta, .fa) for your reference genome. It is better to make sure that your reference file has the same name and order of contigs to your .bam file(s) and .bed file(s). Reads aligned to any contigs which do not appear in the reference file will be ignored. When running MosaicHunter, you need to set the top parameter reference_file.

Preparing your reads:




• MosaicHunter currently accepts aligned reads from whole-genome or whole-exome sequencing. We recommend bwa for read mapping and GATK/Picard for read pre-processing (Picard's SortSam and MarkDuplicates, GATK's IndelRealignment and BaseRecalibration). These pre-processing steps are important in order to reduce false positives in identifying mosaic sites.

  
  

• MosaicHunter uses the sorted and indexed .bam file(s) to identify mosaic sites, as set by the top parameter input_file to the path of your major .bam file.

• For the 'trio' mode, you need to specify two additional files, father_bam_file, mother_bam_file; and for the 'paired' mode, the additional control_bam_file must be specified.

• In addition, we suggest to only keep proper-mapped reads (for paired-end reads; with flag 0x2), and drop reads with NM > 4, to make the input cleaner. The command to achieve this is as follows:

•    samtools view -h -f 0x2 input.bam | perl -ne 'print if (/^@/||(/NM:i:(\d+)/&&$1cleaner.bam

Preparing sample-specific files:

• False mosaic sites can be caused by alignment errors in the genomic regions containing INDELs and CNVs, thus we suggest that you generate a list of such error-prone regions for MosaicHunter to mask. We recommend to identify and filter INDELs and CNVs from the processed .bam file following the pipelines of GATK and CNVnator, respectively. The regions of called INDELs (with +/-5bp flanks) and CNVs should be then converted to the .bed format and specify the corresponding parameter indel_region_filter.bed_file when running MosaicHunter.

Running MosaicHunter:




• The standard command-line usage of MosaicHunter is

•    java -jar your_path/build/mosaichunter.jar -P param_1=value_1 [-P param_2=value_2 [...]]

• (Note: predefined_configuration could be 'genome', 'exome', or 'exome_parameters'.)

• or

•    java -jar your_path/build/mosaichunter.jar -C -P param_1=value_1 [-P param_2=value_2 [...]]

• The output files will be put into the path set by the top parameter output_dir.

Running MosaicHunter demo:




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• We provided demo files in your_path/MosaicHunter/demo to show how to run MosaicHunter. The command to run the demo is

•    cd your_path/MosaicHunter/

•    java -jar build/mosaichunter.jar genome \

•    -P input_file=demo/demo_sample.bam \

•    -P reference_file=demo/hg37_chr18.fa \

•    -P mosaic_filter.sex=M \

•    -P mosaic_filter.dbsnp_file=demo/dbsnp137_hg37_chr18_demo.tsv \

•    -P repetitive_region_filter.bed_file=resources/all_repeats.b37.bed \

•    -P indel_region_filter.bed_file=demo/demo_sample.indel_CNV.bed \

•    -P common_site_filter.bed_file=resources/WGS.error_prone.b37.bed \

•    -P output_dir=demo_output

  
  

• You can find the final passed list in demo_output/final.passed.tsv, which should contain only one row for the candidate SNM site of 18:70512197.

Output format:




• All of the output files are in the specified directory output_dir, including the final candidate list final.passed.tsv, the filtered and remained remaining variant lists of each filters (.filtered.tsv, .passed.tsv), and other temporary files, such as blat input and output.

• The final.passed.tsv files are in tab-separated format, whose columns' meanings for single mode are listed below:

Contig / chromosome name

1. Contig / chromosome name

2. Position / coordinate on the contig (1-based)

3. Base of reference allele

4. Total depth of this site

5. Pileuped sequencing bases at this site

6. Pileuped sequencing baseQs at this site

7. Base of major allele

8. Depth of major allele

9. Base of minor allele

10. Depth of minor allele

11. dbSNP allele frequency of major and minor alleles

12. log10 prior probability of major-homozygous genotype

13. log10 prior probability of heterozygous genotype

14. log10 prior probability of minor-homozygous genotype

15. log10 prior probability of mosaic genotype

16. log10 likelihood of major-homozygous genotype

17. log10 likelihood of heterozygous genotype

18. log10 likelihood of minor-homozygous genotype

19. log10 likelihood of mosaic genotype

20. log10 posterior probability of major-homozygous genotype

21. log10 posterior probability of heterozygous genotype

22. log10 posterior probability of minor-homozygous genotype

23. log10 posterior probability of mosaic genotype

24. Mosaic posterior probability

• You can get a high-confidence candidate list of mosaic sites by filtering the 24th column (mosaic posterior probability) or sorting this column from high to low.

• The 11+ columns are dependent on different modes of MosaicHunter's Bayesian genotypes, and you can find all of the details from the detailed version of the manual.

  
  

Detailed manual:

• The detailed version of the manual, including best-practice and parameter descriptions, is available here. You can also find it on the MosaicHunter repository at GitHub.