With Single Molecule, Real-Time (SMRT) Sequencing, you can access structural variations having a broad range of sizes, types, and GC content with the ability to:

• Uncover missing heritability linked to structural variation
• Unambiguously identify genomic context and variant breakpoints at the sequence level to unravel the genetic etiology of disease
• Resolve structural variation across the complete size spectrum with basepair resolution

Following are the SV tools, which can assist you to achieve your goal.

Sniffles: Structural variation caller using third generation sequencing

Sniffles is a structural variation caller using third generation sequencing (PacBio or Oxford Nanopore). It detects all types of SVs using evidence from split-read alignments, high-mismatch regions, and coverage analysis. Please note the current version of Sniffles requires sorted output from BWA-MEM (use -M and -x parameter) or NGM-LR with the optional SAM attributes enabled! 

More at https://github.com/fritzsedlazeck/Sniffles

MultiBreak-SV: It identifies structural variants from next-generation paired end data, third-generation long read data, or data from a combination of sequencing platforms.

There are two pieces of software in this release: (1) a pre-processor that takes machineformat (.m5) BLASR files, and (2) MultiBreak-SV. For installation and usage instructions, see doc/MultiBreakSV-Manual.txt.

More at https://github.com/raphael-group/multibreak-sv

Parliament: A Structural Variation Tool. Why ask a single sv-detection approach to find every variant when you can have a parliament of tools deciding?

Publication about the algorithm and “…the first long-read characterization of structural variation in a diploid human personal genome…” (HS1011) - “Assessing structural variation in a personal genome—towards a human reference diploid genome”

More at https://sourceforge.net/projects/parliamentsv/

https://www.dnanexus.com/papers/Parliament_Info_Sheet.pdf

PBHoney: the structural variation discovery tool 

PBHoney is an implementation of two variant-identification approaches designed to exploit the high mappability of long reads (i.e., greater than 10,000 bp). PBHoney considers both intra-read discordance and soft-clipped tails of long reads to identify structural variants.

Read The Paper http://www.biomedcentral.com/1471-2105/15/180/abstract

More at https://sourceforge.net/projects/pb-jelly/

SMRT-SV: Structural variant and indel caller for PacBio reads

Structural variant (SV) and indel caller for PacBio reads based on methods from Chaisson et al. 2014.

SMRT-SV provides an official software package for tools described in Chaisson et al. 2014 and adds several key features including the following.

• Unified variant calling user interface with built-in cluster compute support
• Small indel calling (2-49 bp)
• Improved inversion calling (screenInversions)
• Quality metric for SV calls based on number of local assemblies supporting each call
• Higher sensitivity for SV calls using tiled local assemblies across the entire genome instead of "signature" regions
• Genotyping of SVs with Illumina paired-end reads from WGS samples

More at https://github.com/EichlerLab/pacbio_variant_caller

Further information about LACHESIS, including source code, documentation and a user's guide are available at: http://shendurelab.github.io/LACHESIS.

Manuscript describing LACHESIS was published as: Burton JN#, Adey A, Patwardhan RP, Qiu R, Kitzman JO, Shendure J#. Chromosome-scale scaffolding of de novo genome assemblies based on chromatin interactions. Nature Biotechnology 2013 Dec;31(12):1119-25. doi: 10.1038/nbt.272. PubMed PMID: 24185095.

http://shendurelab.github.io/LACHESIS/

Address of the bookmark: http://shendurelab.github.io/LACHESIS/

Features

• Circular and linear views of genomes

• Capable of drawing genomes up to 10 Mbp with 1000's of features and 100's contigs

• Smooth zooming down to the sequence level

• Easily generate features and plots directly form the sequence (e.g. ORFs, GC-content and GC-Skew)

• Save high resolution PNG maps up to 8000x8000px

• Fully documented API for interacting with CGView.js maps

Address of the bookmark: https://js.cgview.ca/

Breeding Insight is funded by the U.S. Department of Agriculture (USDA) Agricultural Research Service (ARS) through Cornell University. The USDA ARS delivers scientific solutions to national and global agricultural challenges. As a global leader in agricultural discovery through scientific excellence, ARS is committed to delivering cutting-edge, scientific tools and innovative solutions for American farmers, producers, industry, and communities to support the nourishment and well-being of all people; sustaining our nation’s agroecosystems and natural resources; and ensuring the economic competitiveness and excellence of our agriculture.

Address of the bookmark: https://www.breedinginsight.org/

• Bioconductor – A plethora of tools for analysis and comprehension of high-throughput genomic data, including 1500+ software packages. [ paper-2004 | web ]
• Biopython – Freely available tools for biological computing in Python, with included cookbook, packaging and thorough documentation. Part of the Open Bioinformatics Foundation. Contains the very useful Entrez package for API access to the NCBI databases. [ paper-2009 | web ]
• Bioconda – A channel for the conda package manager specializing in bioinformatics software. Includes a repository with 3000+ ready-to-install (with conda install) bioinformatics packages. [ paper-2018 | web ]
• BioJulia – Bioinformatics and computational biology infastructure for the Julia programming language. [ web ]
• Rust-Bio – Rust implementations of algorithms and data structures useful for bioinformatics. [ paper-2016 ]
• SeqAn – The modern C++ library for sequence analysis.

KisSplice is not a full-length transcriptome assembler. This means that it will output the variable regions of the transcripts, not reconstruct them entirely.

KisSplice comes as a workflow, with several possible post-treatments meant to facilitate the analysis of the results. The choice of the post-treatment depends on the availability of a reference genome/transcriptome and on the need to perform a differential analysis, as summarised in the following table.

Address of the bookmark: http://kissplice.prabi.fr/

Address of the bookmark: http://crossmap.sourceforge.net/

Address of the bookmark: https://urgi.versailles.inra.fr/Tools/REPET/TEannot-tuto

Ryan M Layer, Colby Chiang, Aaron R Quinlan, and Ira M Hall. 2014. "LUMPY: a Probabilistic Framework for Structural Variant Discovery." Genome Biology 15 (6): R84. doi:10.1186/gb-2014-15-6-r84.

More at https://github.com/arq5x/lumpy-sv

Address of the bookmark: https://github.com/arq5x/lumpy-sv

Look for KaKs calculation:

https://github.com/fumba/kaks-calculator

http://longlab.uchicago.edu/?q=gKaKs

http://www.ncbi.nlm.nih.gov/pubmed/23314322

Address of the bookmark: http://longlab.uchicago.edu/?q=gKaKs