https://prakharg24.github.io/papers/401851.full.pdf

Address of the bookmark: https://prakharg24.github.io/papers/401851.full.pdf

unzip blatSrc35.zip

to unpack the archive. This gives a directory blatSrc now move into that directory.

#cd blatSrc

before you begin read the README file that comes with the source code.

One thing about building blat is that you need to set the MACHTYPE variable so that the BLAT sources know what type of machine you are compiling the software on.

on most *nix machines, typing

echo $MACHTYPE

will return the machine architecture type.

On my CentOS 6 based system this gave:

x86_64-redhat-linux-gnu

However, what BLAT requires is the 'short value' (ie the first part of the MACHTYPE). To correct this, in the bash shell type (change this to the correct MACHTYPE for your system)

MACHTYPE=x86_64
export MACHTYPE

now running the command:

echo $MACHTYPE

should give the correct short form of the MACHTYPE:

x86_64

now create the directory lib/$MACHTYPE in the source tree. ie:

mkdir lib/$MACHTYPE

For my machine, lib/x86_64 already existed, so I did not have to do this, but this is not the case for all architectures.

The BLAT code assumes that you are compiling BLAT as a non-privileged (ie non-root) user. As a result, you must create the directory for the executables to go into:

mkdir ~/bin/$MACHTYPE

If you are installing as a normal user, edit your .bashrc to add the following (change the x86_64 to be your MACHTYPE):

export PATH=~/bin/x86_64::$PATH

For me, though, this was not good enough. I wanted the executables in /usr/local/bin where all my other code goes. As a result I did some hackery...

There is a master make template in the inc directory called common.mk and I edited this file with the command:

vi inc/common.mk

I replaced the line

    BINDIR=${HOME}/bin/${MACHTYPE}

with

    BINDIR=/usr/local/bin

saved and quit (as this is in my path, I do not need to do anything else)

All the preparation is now done and you can create the blat executables by going into the toplevel of the blat source tree (for me it was /usr/local/src/blat/blatSrc, but change to wherever you unpacked blat into).

Now simply run the command:

make

to compile the code.

Blat installed cleanly and the executables were all neatly placed in /usr/local/bin/x86_64, just like I wanted.

now simply running the command:

blat

on the command line gives me information on blat and sample usage.

Blat is installed and it's installed properly in my system code tree!!!

When the query file format is fasta, you can specify many threads to process it. It can reduce run time linearly, and use almost equal memory as the original lastz program. This is useful when you lastz a big query file to a huge reference like human whole genome sequence.

The program is an extension on the original lastz program which was written by Bob Harris (the LASTZ guy).

Address of the bookmark: https://github.com/jnarayan81/parallelLastz

Handle sequence locations for bioinformatics http://www.ingolia-lab.org/seqloc-tutorial.html

Address of the bookmark: http://www.stackage.org/snapshot/nightly-2014-12-28/package/seqloc-0.6

Krona

https://sourceforge.net/p/krona/home/krona/

Address of the bookmark: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4053813/

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

Address of the bookmark: https://github.com/Reedwarbler/GAPPadder

Address of the bookmark: http://www.phrap.org/consed/consed.html

Address of the bookmark: http://www.ub.edu/dnasp/