cuteSV

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Getting Start

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Installation

$ pip install cuteSV
or
$ conda install -c bioconda cutesv
or 
$ git clone https://github.com/tjiangHIT/cuteSV.git && cd cuteSV/ && python setup.py install 

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Introduction

Long-read sequencing enables the comprehensive discovery of structural variations (SVs). However, it is still non-trivial to achieve high sensitivity and performance simultaneously due to the complex SV characteristics implied by noisy long reads. Therefore, we propose cuteSV, a sensitive, fast and scalable long-read-based SV detection approach. cuteSV uses tailored methods to collect the signatures of various types of SVs and employs a clustering-and-refinement method to analyze the signatures to implement sensitive SV detection. Benchmarks on real Pacific Biosciences (PacBio) and Oxford Nanopore Technology (ONT) datasets demonstrate that cuteSV has better yields and scalability than state-of-the-art tools.

The benchmark results of cuteSV on the HG002 human sample are below:

BTW, we used Truvari to calculate the recall, precision, and f-measure. For more detailed implementation of SV benchmarks, we show an example here.

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Dependence

1. python3
2. pysam
3. Biopython
4. cigar
5. numpy

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Usage

cuteSV <sorted.bam> <output.vcf> <work_dir>

Suggestions

> For PacBio CLR/ONT data:
	--max_cluster_bias_INS		100
	--diff_ratio_merging_INS	0.2
	--diff_ratio_filtering_INS	0.6
	--diff_ratio_filtering_DEL	0.7
> For PacBio CCS(HIFI) data:
	--max_cluster_bias_INS		200
	--diff_ratio_merging_INS	0.65
	--diff_ratio_filtering_INS	0.65
	--diff_ratio_filtering_DEL	0.35

Parameter	Description	Default
--threads	Number of threads to use.	16
--batches	Batch of genome segmentation interval.	10,000,000
--sample	Sample name/id	NULL
--max_split_parts	Maximum number of split segments a read may be aligned before it is ignored.	7
--min_mapq	Minimum mapping quality value of alignment to be taken into account.	20
--min_read_len	Ignores reads that only report alignments with not longer than bp.	500
--merge_del_threshold	Maximum distance of deletion signals to be merged.	0
--merge_ins_threshold	Maximum distance of insertion signals to be merged.	100
--min_support	Minimum number of reads that support a SV to be reported.	10
--min_size	Minimum length of SV to be reported.	30
--max_size	Minimum length of SV to be reported.	100000
--genotype	Enable to generate genotypes.	False
--hom	Threshold on allele frequency for homozygous.	0.8
--het	Threshold on allele frequency for heterozygous.	0.2
--max_cluster_bias_INS	Maximum distance to cluster read together for insertion.	100
--diff_ratio_merging_INS	Do not merge breakpoints with basepair identity more than the ratio of default for insertion.	0.2
--diff_ratio_filtering_INS	Filter breakpoints with basepair identity less than the ratio of default for insertion.	0.6
--max_cluster_bias_DEL	Maximum distance to cluster read together for deletion.	200
--diff_ratio_merging_DEL	Do not merge breakpoints with basepair identity more than the ratio of default for deletion.	0.3
--diff_ratio_filtering_DEL	Filter breakpoints with basepair identity less than the ratio of default for deletion.	0.7
--max_cluster_bias_INV	Maximum distance to cluster read together for inversion.	500
--max_cluster_bias_DUP	Maximum distance to cluster read together for duplication.	500
--max_cluster_bias_TRA	Maximum distance to cluster read together for translocation.	50
--diff_ratio_filtering_TRA	Filter breakpoints with basepair identity less than the ratio of default for translocation.	0.6

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Datasets generated from cuteSV

We provided the SV callsets of the HG002 human sample produced by cuteSV form three different long-read sequencing platforms (i.e. PacBio CLR, PacBio CCS, and ONT PromethION).

You can download them at:

Please cite the manuscript of cuteSV before using these callsets.

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Changelog

cuteSV (v1.0.5):
1.Add new options for specificly setting the threshold of deletion/insertion signals merging in the same read. The default parameters are 0 bp for deletion and 100 bp for insertion.
2.Remove parameter --merge_threshold.
3.Fix bugs in inversion and translocation calling.
4.Add new option for specificly setting the maximum size of SV to be discovered. The default value is 100,000 bp. 


cuteSV (v1.0.4):
1.Add a new option for specificly setting the threshold of SV signals merging in the same read. The default parameter is 500 bp. You can reduce it for high-quality sequencing datasets like PacBio HiFi (CCS).
2.Make the genotyping function optional.
3.Enable users to set the threshold of SV allele frequency of homozygous/heterozygous.
4.Update the description of recommendation parameters in processing ONT data.

cuteSV (v1.0.3):
1.Refine the genotyping model.
2.Adjust the threshold value of heterozygosis alleles.

cuteSV (v1.0.2):
1.Improve the genotyping performance and enable it to be default option.
2.Make the description of parameters better.
3.Modify the header description of vcf file.
4.Add two new indicators, i.e., BREAKPOINT_STD and SVLEN_STD, to further characterise deletion and insertion.
5.Remove a few redundant functions which will reduce code readability.

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Citation

Long Read based Human Genomic Structural Variation Detection with cuteSV. Tao Jiang, et al. bioRxiv 780700; doi: https://doi.org/10.1101/780700

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Contact

For advising, bug reporting and requiring help, please post on Github Issue or contact [email protected].