Haplotype filter adapting to 10X genomics (HP) is added in the recent update.

• use --phasing_mode Y to activate HP filter.
• detailed description will appear in a manuscript of 10X genomic sequencing.

Installation

git clone https://github.com/jcarrotzhang/LoLoPicker
cd LoLoPicker
python setup.py install

dependencies pysam 0.8.4; pysamstats

pip install pysam==0.8.4
pip install pysamstats

Please note that LoLoPicker is no longer available on PyPI

Step one: calling raw, somatic variants using matched tumor/normal

python LoLoPicker_somatic.py -t tumor.bam -n normal.bam -r reference.fa -b interval.bed -o outputpath 

options:

• --basequality: only_count_reads_with_base_quality_above_cutoff
• --mappingquality: only_count_reads_with_mapping_quality_above_cutoff
• --tumoralteredreads: keep_variants_where_number_of_altered_reads_in_tumor_more_than_cutoff
• --normalalteredreads: keep_variants_where_number_of_altered_reads_in_normal_less_than_cutoff

Step two: inspecting your control cohort

python LoLoPicker_control.py -l samplelist.txt -r reference.fa -o outputpath

options:

• --basequality
• --mappingquality
• -n: number of threads

please provide your control panel in samplelist.txt using the following tab-delimited format:

Bam_file_of_each_control      control_sampleID 

Step three: performing core stats

python LoLoPicker_stats.py -o outputpath --method FDR (or Bonferroni)

options:

• --genome: for_analyzing_WGS_data
• --SNPcutoff: keep_variants_present_in_number_of_normal_samples_less_than_cutoff
• --intervalsize: size_of_the_targeted_region_of_your_experiment

Note:

• For analyzing whole-genome sequencing data, please split your job by genomic intervals (e.g. chromosomes) and merge all your control_stats.txt files before going to step three.
• For analyzing data from targeted re-sequencing, --intervalsize option is required. If the size of the targeted region of your experiment is 1000 base-pair, you should use interval size as 1000.