RabbitVar is a high-performance and versatile mutation detection tool, which distinguishes between somatic and germline sequencing applications and simultaneously calls single nucleotide variants (SNVs), multiple-nucleotide variants (MNVs), insertions, and deletions(InDels) and complex variants.
- htslib
- zlib (included with most Linuxes)
yum install bzip2-devel yum install zlib
- If you want to use XGBoost based filter, you should download the XGBoost model(pretrained-model). Besides, it also needs Python3.8 enviorment, we recommend conda enviorment:
conda create -n rabbitvar python=3.8 conda activate rabbitvar
RabbitVar is written in c++ for Linux platforms, you can download the source code and RabbitVar use some features supported by std-c++-11. So, c++ 11 or higher version is required. If you do not want the XGBoost based filter, Just Comipile RabbitVar with CMake:
$ mkdir build && cd build
$ cmake -DHTS_PREFIX=<path to htslib> -DCMAKE_INSTALL_PREFIX=<install path> ..
$ make -j4
$ make install
Then the binary file of RabbitVar will be installed as bin/RabbitVar if CMAKE_INSTALL_PREFIX not specified.
If you want to use XGBoost based filter, it need Python3.8 enviorment, we recommend conda enviorment:
conda create -n rabbitvar python=3.8
conda activate rabbitvar
./install.shif you have the python3.8 enviorment locally, just run:
./install.shIn terms of somatic benchmarking, we use tumor and normal datasets from National Center for Clinical Laboratories (NCCL) for quality assessment of somatic mutations detection. Raw sequencing files containing 97 somatic variants.There are two sequence file (both 14GB) which contains 116M reads in B1701 tumor dataset, and two sequence file (both 11GB) which contains 92M reads in B17NC normal dataset data can be requested in NCCL
In RabbitVar, the following input are required:
-
Alignment
.bamfiles.The
.bamfile should be sorted and indexed. -
Region file
.bed, or specify the region by -R parameter -
Genome reference file
.faor.fasta, like hg19.fa or hg38.fa.the reference file should be indexed (
.fai).
User can specify one region with -r parameter:
./RabbitVar \
-R chr1:2829690-4918526 \
-G /home/data/hg38.fa \
-f 0.01 -N 'TUMORSMAPLE|NORMALSAMPLE' -b 'PATH_TO_TUMORSAMPLE|PATH_TONORMALSAMPLE' \
-c 1 -S 2 -E 3 -g 4 \
--fisher \
--out ./out.txt
NOTE:
- Use '' to enclose the SAMPLE_NAMEs and SMPALE_PATHs to avoid redirection
- if you want to use XGBoost or RandomForest filter in next step, you must add '--fisher' parameter while runing RabbitVar, it performs the fisher exact tests.
User can also specify multi pregions with bed file:
./RabbitVar \
-i /home/data/NA12878/WGSRegions.bed \
-G /home/data/hg38.fa \
-f 0.01 -N 'TUMORSMAPLE|NORMALSAMPLE' -b 'PATH_TO_TUMORSAMPLE|PATH_TONORMALSAMPLE' \
-c 1 -S 2 -E 3 -g 4 \
--fisher \
--out ./out.vcf
This script filtering SNV or INDEL variants separatly:
time python PATH_TO_RABBITVAR/XGBoost/call_xgboost.py \
--in_file ${IN_FILE}\
--model ${MODEL} \
--scale "0.5" \
--var_type ${VTYPE} \
--out_file ./${OUT}${VTYPE} is "SNV" or "INDEL"
You can run RabbitVar with directly or using python script run_rabbitvar.py. run_rabbitvar.py provide a python3 script wapper to RabbitVar, a randomforest filter and formater.
A simple example is:
run_rabbitvar.py \
--BIN ./build/RabbitVar \
-R chr1:2829690-4918526 \
-G /home/data/hg38.fa \
-f 0.01 -N 'TUMORSMAPLE|NORMALSAMPLE' -b 'PATH_TO_TUMORSAMPLE|PATH_TONORMALSAMPLE' \
-c 1 -S 2 -E 3 -g 4 --fisher \
--indelmod ./XGBoost/models/INDEL_model.pkl \
--snvmod ./XGBoost/models/SNV_model.pkl \
--vcf ./variants.vcfNOTE: use '' to enclose the SAMPLE_NAMEs and SMPALE_PATHs to avoid redirection
- create .tsv file (after [detection](#1. Variant Detection))
cd XGBoost
# DATA: the output file of RabbitVar(detect step without filter)
# TRUTH: ground truth file
# VTYPE: INDEL or SNV
./make_data_new.py --in_file ${DATA} --truth_file ${TRUTH} --var_type "${VTYPE}" --tsv data_${prefix}.tsv- train SNV or INDEL
python train_rf.py \
--tsv data_${prefix}.tsv \
--var_type "INDEL" \
--out_model ./models/train_${prefix}.pkloptions:
-H, --help Print this help page
-p, --pileup Do pileup regardless of the frequency
-t, --dedup Indicate to remove duplicated reads. Only one pair with same start positions will be kept
-3, --3-prime Indicate to move indels to 3-prime if alternative alignment can be achieved.
-u, --uni Indicate unique mode, which when mate pairs overlap, the overlapping part will be counted only once
using forward read only.
--UN Indicate unique mode, which when mate pairs overlap, the overlapping part will be counted only once
using first read only.
--chimeric Indicate to turn off chimeric reads filtering.
--deldupvar Turn on deleting of duplicate variants. Variants in this mode are considered and outputted only if
start position of variant is inside the region interest.
-y, --verbose
-F, --Filter The hexical to filter reads using samtools. Default: 0x504 (filter 2nd alignments, unmapped reads
and duplicates). Use -F 0 to turn it off. (string [=0x504])
-z, --zero_based Indicate whether coordinates are zero-based, as IGV uses. Default: 1 for BED file or amplicon BED
file.Use 0 to turn it off. When using the -R option, it's set to 0
-k, --local_realig Indicate whether to perform local realignment. Default: 1. Set to 0 to disable it. For Ion or
PacBio, 0 is recommended. (int [=1])
-a, --amplicon Indicate it's amplicon based calling. Reads that don't map to the amplicon will be skipped. A read
pair is considered belonging to the amplicon if the edges are less than int bp to the amplicon,
and overlap fraction is at least float. Default: 10:0.95 (string [=])
-c, --column The column for chromosome (int [=2])
-G, --Genome_fasta The reference fasta. Should be indexed (.fai). (string)
-R, --Region The region of interest. In the format of chr:start-end. If end is omitted, then a single position.
No BED is needed. (string [=])
-d, --delemiter The delimiter for split region_info, default to tab "\t" (string [= ])
-n, --regular_expression The regular expression to extract sample name from BAM filenames.
Default to: /([^\/\._]+?)_[^\/]*.bam/ (string [=/([^\/\._]+?)_[^\/]*.bam/])
-N, --Name The sample name to be used directly. Will overwrite -n option (string [=])
-b, --in_bam The indexed BAM file (string)
-S, --region_start The column for region start, e.g. gene start (int [=6])
-E, --region_end The column for region end, e.g. gene end (int [=7])
-s, --seg_start The column for segment starts in the region, e.g. exon starts (int [=9])
-e, --seg_end The column for segment ends in the region, e.g. exon ends (int [=10])
-g, --gene_name The column for gene name, or segment annotation (int [=12])
-x, --numcl_extend The number of nucleotide to extend for each segment, default: 0 (int [=0])
-B, --min The minimum # of reads to determine strand bias, default 2 (int [=2])
-Q, --Quality If set, reads with mapping quality less than INT will be filtered and ignored (int [=0])
-q, --phred_score The phred score for a base to be considered a good call. Default: 25 (for Illumina) For PGM, set
it to ~15, as PGM tends to under estimate base quality. (double [=22.5])
-m, --mismatch If set, reads with mismatches more than INT will be filtered and ignored. Gaps are not counted as
mismatches. Valid only for bowtie2/TopHat or BWA aln followed by sampe. BWA mem is calculated as
NM - Indels. Default: 8, or reads with more than 8 mismatches will not be used. (int [=8])
-T, --trim Trim bases after [INT] bases in the reads (int [=0])
-X, --extension Extension of bp to look for mismatches after insersion or deletion. Default to 2 bp, or only calls
when they're within 2 bp. (int [=2])
-P, --Position The read position filter. If the mean variants position is less that specified, it's considered
false positive. Default: 5 (int [=5])
-I, --Indel_size The indel size. Default: 50bp (int [=50])
--th Threads count. (int [=0])
--fisher Experimental feature: fisher test
-M, --Min_macth The minimum matches for a read to be considered. If, after soft-clipping, the matched bp is less
than INT, then the read is discarded. It's meant for PCR based targeted sequencing where there's no
insert and the matching is only the primers. Default: 0, or no filtering (int [=0])
-Y, --ref-extension Extension of bp of reference to build lookup table. Default to 1200 bp. Increase the number will
slowdown the program. The main purpose is to call large indels with 1000 bit that can be missed by
discordant mate pairs. (int [=1200])
-r, --minimum_reads The minimum # of variant reads, default 2 (int [=2])
-o, --Qratio The Qratio of (good_quality_reads)/(bad_quality_reads+0.5). The quality is defined by -q option.
Default: 1.5 (double [=1.5])
-O, --MapQ The reads should have at least mean MapQ to be considered a valid variant.
Default: no filtering (double [=0])
-V, --freq The lowest frequency in the normal sample allowed for a putative somatic mutation.
Defaults to 0.05 (double [=0.05])
-f, --allele_fre The threshold for allele frequency, default: 0.01 or 1% (double [=0.01])
-Z, --downsample For downsampling fraction. e.g. 0.7 means roughly 70% downsampling. Default: No downsampling.
Use with caution. The downsampling will be random and non-reproducible. (double [=0])
--adaptor Filter adaptor sequences so that they aren't used in realignment. Multiple adaptors can be supplied
by setting them with comma, like: --adaptor ACGTTGCTC,ACGGGGTCTC,ACGCGGCTAG . (string [=])
-J, --crispr The genomic position that CRISPR/Cas9 suppose to cut, typically 3bp from the PAM NGG site and
within the guide. For CRISPR mode only. It will adjust the variants (mostly In-Del) start and end
sites to as close to this location as possible,if there are alternatives. The option should only be
used for CRISPR mode. (int [=0])
-j, --CRISPR_fbp In CRISPR mode, the minimum amount in bp that a read needs to overlap with cutting site. If a read does not meet the criteria,
it will not be used for variant calling, since it is likely just a partially amplified PCR. Default: not set, or no filtering (int [=0])
--mfreq The variant frequency threshold to determine variant as good in case of monomer MSI.
Default: 0.25 (double [=0.25])
--nmfreq The variant frequency threshold to determine variant as good in case of non-monomer MSI.
Default: 0.1 (double [=0.1])
--out The out put file path.
Default: ./out.txt (string [=./out.txt])
-i, --bed The region file to be processed (string [=])
--version Print RabbitVar version information
--auto_resize Auto resize the bed region size for better performance
RabbitVar paper is under reivew.
Licensed under the GPL v3.0 License.