RDXplorer is a read depth-based method to detect CNV. Moreover, RDXplorer developed the Event-Wise Testing (EWT) algorithm based on significant testing and has a good sensitivity to CNV which is larger than 1 kb.
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The m-HMM (Mixture-Hidden Markov Model) software based on a hidden Markov model (HMM) takes advantage of Expectation-Maximization (EM) algorithm for solving parameters in the model and thus identify CNV from NGS data.
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Wablco is used for correction of GC bias on the basis of multiresolution analysis.
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cnvOffSeq is a novel normalization framework for off-target read depth that is based on local adaptive singular value decomposition (SVD).
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ExomeCNV is a statistical method to detect CNV and LOH using depth-of-coverage and B-allele frequencies from mapped short sequence reads.
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ExomeCopy is applied to a large chromosome X exome sequencing project identifying a list of large unique CNV.
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CONTRA is a software package that takes standard alignment formats (BAM/SAM) and outputs in variant call format (VCF4.0), for easy integration with other next-generation sequencing analysis packages.
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ExomeDepth is a new CNV calling algorithm designed to control for this technical variability.
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CoNIFER can reliably be used to discover disruptive genic CNVs missed by standard approaches and should have broad application in human genetic studies of disease.
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CODEX is a normalization and CNV calling procedure for whole exome sequencing data.
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CLAMMS is highly scalable and suitable for detecting CNVs across the whole allele frequency spectrum.
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The CoNVaDING is used to detect simple and compound CNV.
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DECoN is a fast, accurate, exon CNV detection tool readily implementable in research and clinical NGS pipelines. It has high sensitivity and specificity and acceptable false discovery rate.
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The CNVkit software is straightforward to use and provides visualizations, detailed reporting of significant features, and export options for integration into existing analysis pipelines.
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The geneCNV software implements a read depth-based method with a hierarchical Bayesian model to conduct the identification of exon-level CNV by exome sequencing data from only a few genes.
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CNVrd2, an improved version of CNVrd, is also a read depth-based method. CNVrd2 measures copy number at the single gene level or a complex locus using NGS data.
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ReadDepth is a parallel R package which can detect these aberrations by measuring the depth of coverage obtained by massively parallel sequencing of the genome.
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PennCNV-Seq was able to find correct CNVs and can be integrated in existing CNV calling pipelines to report accurately the number of copies in specific genomic regions.
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OncoSNP-SEQ is a statistical approach for the identification of somatic copy number alterations from next-generation sequencing of cancer genomes.
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BIC-seq can accurately and efficiently identify CNVs via minimizing the Bayesian information criterion.
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BIC-seq2 combines normalization of the data at the nucleotide level and Bayesian information criterion-based segmentation to detect both somatic and germline CNVs accurately.
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CNVnator is an approach to discover, genotype, and characterize typical and atypical CNVs from family and population genome sequencing.
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MATCHCLIP software identifies the breakpoints and CNV based on WGS or WES data using CIGAR (Concise Idiosyncratic Gapped Alignment Report) strings.
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Magnolya uses a Poisson mixture model for copy number estimation of contigs assembled from sequencing data.
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cnvHiTSeq is an integrative probabilistic method for CNV discovery and genotyping that jointly analyzes multiple features at the population level.
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ERDS accommodates both unique and highly amplified regions of the genome and does so without requiring separate alignments for calling CNVs and other variants.
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iCopyDAV is a integrated platform for copy number variations-Detection, annotation and visualization.
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Ginkgo automatically constructs copy-number profiles of cells from mapped reads and constructs phylogenetic trees of related cells.
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AneuFinder allows annotation of copy number changes in a fully automated fashion and quantification of CNV heterogeneity between cells.
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The R package copynumber is a software suite for segmentation of single- and multi-track copy number data using algorithms based on coherent least squares principles.
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SCONCE is a method based on a Hidden Markov Model to analyze read depth data from tumor cells using matched normal cells as negative controls.
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HMMcopy is a R package for detecting and visualizing CNV
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SciClone is a computational method that identifies the number and genetic composition of subclones by analyzing the variant allele frequencies of somatic mutations.
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SVDetect is a program designed to identify genomic structural variations from paired-end and mate-pair next-generation sequencing data produced by the Illumina GA and ABI SOLiD platforms.
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SVfinder is a tool to detect SV from whole-genome PE or MP sequencing data.
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Ulysses achieves high specificity over the complete spectrum of variants by assessing, in a principled manner, the statistical significance of each possible variant (duplications, deletions, translocations, insertions and inversions) against an explicit model for the generation of experimental noise.
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VariationHunter is combinatorial algorithms for structural variation detection in high-throughput sequenced genomes.
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Pindel is a pattern growth approach to detect break points of large deletions and medium sized insertions from paired-end short reads.
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Socrates (SOft Clip re-alignment To idEntify Structural variants) is a highly efficient and effective method for detecting genomic rearrangements in tumours that uses only split-read data.
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Sprites (SPlit Read re-alIgnment To dEtect Structural variants) is a novel method which finds deletions from sequencing data.
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SVseq2 enables accurate and efficient SV calling through split-read mapping within focal regions using paired-end reads.
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Cortex software, a de novo assembly-based variant detector, takes advantage of colored de Bruijn graphs that provide overlap information within a set of DNA sequences for the de novo assembly.
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FermiKit is a variant calling pipeline for Illumina whole-genome germline data. It de novo assembles short reads and then maps the assembly against a reference genome to call SNPs, short insertions/deletions and structural variations.
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laSV detects SVs with high accuracy from paired-end high-throughput genomic sequencing data and pinpoints their breakpoints at single base-pair resolution.
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MindTheGap is used for the integrated detection and assembly of insertion variants from re-sequencing data. Importantly, it is designed to call insertions of any size, whether they are novel or duplicated, homozygous or heterozygous in the donor genome.
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Hydra-sv is an algorithm to localize SV breakpoints by paired-end mapping, and a general approach for the genome-wide assembly and interpretation of breakpoint sequences.
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BASIL-ANISE is the approach for detecting insertion breakpoints and targeted assembly of large insertions from HTS paired data
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BreakSeek is a novel breakpoint-based algorithm, which can unbiasedly and efficiently detect both homozygous and heterozygous INDELs, ranging from several base pairs to over thousands of base pairs, with accurate breakpoint and heterozygosity rate estimations.
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DELLY integrates short insert paired-ends, long-range mate-pairs and split-read alignments to accurately delineate genomic rearrangements at single-nucleotide resolution.
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DIGTYPER (Duplication and Inversion GenoTYPER) computes genotype likelihoods for a given inversion or duplication and reports the maximum likelihood genotype.
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indelMINER uses a split-read approach to identify the precise breakpoints for indels of size less than a user specified threshold, and supplements that with a paired-end approach to identify larger variants that are frequently missed with the split-read approach.
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Mobster is used to detect non-reference mobile element insertions in next generation sequencing data from both whole genome and whole exome studies.
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PRISM (pair-read informed split mapping) is a method that identifies SVs and their precise breakpoints from whole-genome resequencing data.
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RAPTR-SV is a program designed to process previously aligned, Illumina Paired-end whole genome sequence data to identify structural variants such as deletions, insertions and tandem duplications.
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SoftSearch identifies breakpoints from a small number of soft-clipped bases from split reads and a few discordant read-pairs which on their own would not be sufficient to make an SV call.
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SoftSV is a method for exact breakpoint detection for small and large deletions, inversions, tandem duplications and inter-chromosomal translocations, which relies solely on the mutual alignment of soft-clipped reads within the neighborhood of discordantly mapped paired-end reads.
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Wham is able to pinpoint SVs in pooled and genotypic data associated with phenotypic variation.
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forestSV integrates prior knowledge about the characteristics of structural variants and leads to improved discovery in high-throughput sequencing data. It offers high sensitivity and specificity coupled with the flexibility of a data-driven approach.
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GASVPro is an algorithm combining both paired read and read depth signals into a probabilistic model which can analyze multiple alignments of reads.
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GenomeSTRiP software could detect DNA segment deletion via the combination between depth of coverage and pair-end mapping method.
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inGAP-sv is a novel scheme to identify and visualize structural variation from paired end mapping data.
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SoloDel is a novel computational method that accurately classifies low-frequent somatic deletions from germline ones with or without matched control samples.
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GINDEL is an approach for calling genotypes of both insertions and deletions from sequence reads.
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CREST (clipping reveals structure) is an algorithm that uses next-generation sequencing reads with partial alignments to a reference genome to directly map structural variations at the nucleotide level of resolution.
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GRIDSS is a multithreaded structural variant (SV) caller that performs efficient genome-wide break-end assembly prior to variant calling using a novel positional de Bruijn graph-based assembler.
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LUMPY is a novel SV discovery framework that naturally integrates multiple SV signals jointly across multiple samples.
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Manta is a rapid detection of structural variants and indels for germline and cancer sequencing applications
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MetaSV is an integrated SV caller which leverages multiple orthogonal SV signals for high accuracy and resolution.
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Pamir is a new algorithm to efficiently and accurately discover and genotype novel sequence insertions using either single or multiple genome sequencing datasets.
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PopIns can discover and characterize non-reference insertions of 100 bp or longer on a population scale.
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SV2 is a machine-learning algorithm for genotyping deletions and duplications from paired-end sequencing data.
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SvABA is an efficient and accurate method for detecting SVs from short-read sequencing data using genome-wide local assembly with low memory and computing requirements.
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SVelter is an algorithm that identifies regions of the genome suspected to harbor a complex event and then resolves the structure by iteratively rearranging the local genome structure, in a randomized fashion, with each structure scored against characteristics of the observed sequencing data.
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TIDDIT utilizes discordant pairs and split reads to detect the genomic location of structural variants, as well as the read depth information for classification and quality assessment of the variants.
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intansv is an R package for integrative analysis of structural variations.
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BreakSeq is the approach for scanning the reads from short-read sequenced genomes against the breakpoint library to accurately identify previously overlooked SVs an approach, for scanning the reads from short-read sequenced genomes against our breakpoint library to accurately identify previously overlooked SVs.
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DeepSVFilter is used for filtering structural variants in short read whole genome sequencing data.
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Cnngeno is a high-precision deep learning based strategy for the calling of structural variation genotype
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DeepSV is accurate calling of genomic deletions from high-throughput sequencing data using deep convolutional neural network
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AS-GENSENG not only predicts accurate ASCN calls but also improves the accuracy of total copy number calls, owing to its unique ability to exploit information from both total and allele-specific read counts while accounting for various experimental biases in sequence data.
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Control-FREEC is a tool for assessing copy number and allelic content using next-generation sequencing data.
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PEMer is a computational framework with simulation-based error models for inferring genomic structural variants from massive paired-end sequencing data.
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PSSV is a novel pattern-based probabilistic approach for somatic structural variation identification.
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1-2-3-SV detected SV with a high precision and recall rate based on NGS for the capability of detecting four types of SV (deletions, duplications, insertions, and inversions) via benchmark test.
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BreakDancer sensitively and accurately detected indels ranging from 10 base pairs to 1 megabase pair that are difficult to detect via a single conventional approach.
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Breakway is a project dedicated to the identification of genomic breakpoints utilizing freely available tools and custom analytical techniques.
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CLEVER is a clique-enumerating variant finder.
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SVision-pro is a neural-network-based instance segmentation framework that represents genome-to-genome-level sequencing differences visually and discovers SV comparatively between genomes without any prerequisite for inference models.
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Cue is a deep-learning framework for structural variant discovery and genotyping
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SVcnn is an accurate deep learning-based method for detecting structural variation based on long-read data
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cnnLSV is applied for detecting structural variants by encoding long-read alignment information and convolutional neural network
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SVDSS is the tool for structural variation discovery in hard-to-call genomic regions using sample-specific strings from accurate long reads
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cuteSV2 is the tool for regenotyping structural variants through an accurate force-calling method.
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SENSV is used for detecting structural variations with precise breakpoints using low-depth WGS data from a single oxford nanopore MinION flowcell
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Duet is applied for SNP-assisted structural variant calling and phasing using Oxford nanopore sequencing.
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MAMnet is used for detecting and genotyping deletions and insertions based on long reads and a deep learning approach
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SVision is a deep learning approach to resolve complex structural variants.
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PAV enables reliable graph-based genotyping from short reads of up to 50,340 SVs, resulting in the identification of 1526 expression quantitative trait loci as well as SV candidates for adaptive selection within the human population.
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SKSV is used for ultrafast structural variation detection from circular consensus sequencing reads.
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BreakNet is applied for detecting deletions using long reads and a deep learning approach.
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A benchmark of structural variation detection by long reads through a realistic simulated model
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The pdsv (PacBio structural variation calling and analysis tools) software developed by Pacific Biosciences is a suite of tools for determining SV for long reads from PacBio sequencing. The pdsv allows CLR reads or HiFi reads as input and map raw BAM files to the reference genome.
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OMSV enables accurate and comprehensive identification of large structural variations from nanochannel-based single-molecule optical maps.
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SVIM-asm is for structural variant detection from haploid and diploid genome assemblies.
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cuteSV is 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 implement sensitive SV detection.
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NanoVar is used for accurate characterization of patients' genomic structural variants using low-depth nanopore sequencing
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MUM&Co is applied for accurate detection of all SV types through whole-genome alignment.
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MsPAC software combines SNV phasing information and long-read sequencing to discover SV.MsPAC software combines SNV phasing information and long-read sequencing to discover SV. The whole run time of MsPAC could expend 3-8 days on the HG002 dataset from the Genome in A Bottle Consortium (GIAB).
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SyRI is used for finding genomic rearrangements and local sequence differences from whole-genome assemblies.
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Local assembly based SV detection using single-molecule sequencing reads and a phased SNV VCF file.
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SVIM is for structural variant identification using mapped long reads.
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A synthetic-diploid benchmark for accurate variant-calling evaluation.
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Smartie-SV aligns query contigs against a reference genome and calls SV.
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Picky comprehensively detects high-resolution structural variants in nanopore long reads.
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NextSV is a meta-caller for structural variants from low-coverage long-read sequencing data.
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CORGi is used for detection and visualization of complex structural variants from long reads.
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PEHoney software could detect four types of SV from data produced by the aligners. PEHoney leverages intra-read discordance and soft-clipped tails of long reads to determine the type and length of SV.
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NanoSV is used for mapping and phasing of structural variation in patient genomes using nanopore sequencing.
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SMRT-SV could align raw PacBio reads and reference genome, and locally assemble regions for the SV discovery. It currently could detect not only SV containing deletions, duplications, insertions, and inversions but also small indels.
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Assemblytics is a web analytics tool for the detection of variants from an assembly.
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Accurate detection of complex structural variations using single-molecule sequencing.
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Sniffles2 is 11.8 times faster and 29% more accurate than state-of-the-art SV callers across different coverages (5-50×), sequencing technologies (ONT and HiFi) and SV types.
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DeBreak is a computational method for comprehensive and accurate SV discovery.
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Ribbon is an alignment visualization tool that shows how alignments are positioned within both the reference and read contexts, giving an intuitive view that enables a better understanding of structural variants and the read evidence supporting them.
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TDSCNV is a tool for inferring haplotypes by implementing CNV or SNP genotype data.
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Ginkgo automatically constructs copy-number profiles of cells from mapped reads and constructs phylogenetic trees of related cells.
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CNVRanger is a comprehensive analytic tool for GWAS and difference analysis, which could process variant calling data or genotype data.
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CONAN could visualize Manhattan plot depicting significant CNV associated with phenotype and the graph that display all detected CNV in every chromosome.
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GISTIC has enhanced power and specificity to identify genes targeted by somatic copy-number alterations (SCNAs) that drive cancer growth.
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SVScore aggregates per-base single nucleotide polymorphism (SNP) pathogenicity scores across relevant genomic intervals for each SV in a manner that considers variant type, gene features and positional uncertainty.
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AnnotSV software could fast annotate SV from NGS data with functional and clinical information for identification of disease SV and improve false positive rate for high-quality SV.
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RSVSim is a tool for the simulation of deletions, insertions, inversions, tandem duplications and translocations of various sizes in any genome available as FASTA-file or data package in R.
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iCopyDAV is a integrated platform for copy number variations-Detection, annotation and visualization.
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PhenoSV is the interpretable phenotype-aware model for the prioritization of genes affected by structural variants.
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SvAnna is used for the efficient and accurate pathogenicity prediction of coding and regulatory structural variants in long-read genome sequencing.
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StrVCTVRE is a supervised learning method to predict the pathogenicity of human genome structural variants.
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SVPath is an accurate pipeline for predicting the pathogenicity of human exon structural variants.
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A framework to score the effects of structural variants in health and disease.
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X-CNV is used for genome-wide prediction of the pathogenicity of copy number variations
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SVFX is a machine learning framework to quantify the pathogenicity of structural variants.
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DeepSVP is applied to the integration of genotype and phenotype for structural variant prioritization using deep learning.
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Samplot is a platform for structural variant visual validation and automated filtering.
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svviz is a read viewer for validating structural variants
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SVJedi is used for genotyping structural variations with long reads.
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SVJedi-graph is used for improving the genotyping of close and overlapping structural variants with long reads using a variation graph.
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A recurrence-based approach for validating structural variation using long-read sequencing technology.
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LRCaller is the software for SV assessment based on haplotype-resolved assemblies.
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TT-Mars is applied for structural variants assessment based on haplotype-resolved assemblies.
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