BOL: Related items

EAGER

Jit — Sat, 10 Dec 2016 18:07:23 -0600

The automated reconstruction of genome sequences in ancient genome analysis is a multifaceted process.

EAGER encompasses both state-of-the-art tools for each step as well as new complementary tools tailored for ancient DNA data within a single integrated solution in an easily accessible format.

https://genomebiology.biomedcentral.com/articles/10.1186/s13059-016-0918-z

Address of the bookmark: https://github.com/apeltzer/EAGER-GUI

LAST

Bulbul — Mon, 19 Dec 2016 14:07:53 -0600

LAST can:

Handle big sequence data, e.g:
- Compare two vertebrate genomes
- Align billions of DNA reads to a genome
Indicate the reliability of each aligned column.
Use sequence quality data properly.
Compare DNA to proteins, with frameshifts.
Compare PSSMs to sequences
Calculate the likelihood of chance similarities between random sequences.
Do split and spliced alignment.
Train alignment parameters for unusual kinds of sequence (e.g. nanopore).

Address of the bookmark: http://last.cbrc.jp/

J-Circos

Shruti Paniwala — Fri, 17 Feb 2017 09:06:54 -0600

Circos plot tool (J-Circos) that is an interactive visualization tool that can plot Circos figures, as well as being able to dynamically add data to the figure, and providing information for specific data points using mouse hover display and zoom in/out functions. J-Circos uses the Java computer language to enable it to be used on most operating systems (Windows, MacOS, Linux). Users can input data into J-Circos using flat data formats, as well as from the GUI. J-Circos will enable biologists to better study more complex chromosomal interactions and fusion transcripts that are otherwise difficult to visualize from next-generation sequencing data.

Address of the bookmark: http://www.australianprostatecentre.org/research/software/jcircos

Pacbio Long Reads Compatible Software and Tools

Archana Malhotra — Wed, 15 Mar 2017 14:19:01 -0500

The following software packages are known to be compatible with PacBio® data, in addition to PacBio's own SMRT® Analysis suite. All packages are believed to be open source or freely available for non-commercial use. See the individual project sites for up-to-date license information. A separate page lists commercial software.

Know of any other open source software for PacBio data? Email us.

Software categories:

Address of the bookmark: https://github.com/PacificBiosciences/DevNet/wiki/Compatible-Software

SSPACE

Jit — Fri, 05 May 2017 05:42:15 -0500

SSPACE standard is a stand-alone program for scaffolding pre-assembled contigs using NGS paired-read data. It is unique in offering the possibility to manually control the scaffolding process. By using the distance information of paired-end and/or matepair data, SSPACE is able to assess the order, distance and orientation of your contigs and combine them into scaffolds. Currently we offer this as a command-line tool in Perl. The input data is given by pre-assembled contig sequences (FASTA) and NGS paired-read data (Illumina/454/Solid FASTA or FASTQ). The final scaffolds are provided in FASTA format.

Address of the bookmark: https://www.baseclear.com/genomics/bioinformatics/basetools/SSPACE

You can't hide from Genome Hackers

Neel — Sat, 13 Oct 2018 14:17:28 -0500

Young computational biologist named Yaniv Erlich shocked the research world by showing it was possible to unmask the identities of people listed in anonymous genetic databases using only an Internet connection

Paper: http://science.sciencemag.org/content/early/2018/10/10/science.aau4832

More at https://www.wired.com/story/genome-hackers-show-no-ones-dna-is-anonymous-anymore/

AlignGraph: algorithm for secondary de novo genome assembly guided by closely related references

Manisha Mishra — Tue, 17 Apr 2018 16:21:20 -0500

AlignGraph is a software that extends and joins contigs or scaffolds by reassembling them with help provided by a reference genome of a closely related organism.

Using AlignGraph

AlignGraph --read1 reads_1.fa --read2 reads_2.fa --contig contigs.fa --genome genome.fa --distanceLow distanceLow --distanceHigh distancehigh --extendedContig extendedContigs.fa --remainingContig remainingContigs.fa [--kMer k --insertVariation insertVariation --coverage coverage --part p --fastMap --ratioCheck --iterativeMap --misassemblyRemoval --resume]

Address of the bookmark: https://github.com/baoe/AlignGraph

EAGLER: a scaffolding tool for long reads.

Jit — Mon, 04 Jun 2018 05:26:03 -0500

EAGLER is a scaffolding tool for long reads. The scaffolder takes as input a draft genome created by any NGS assembler and a set of long reads. The long reads are used to extend the contigs present in the NGS draft and possibly join overlapping contigs. EAGLER supports both PacBio and Oxford Nanopore reads.

The tool should be compatible with most UNIX flavors and has been successfully tested on the following operating systems:

Mac OS X 10.11.1
Mac OS X 10.10.3
Ubuntu 14.04 LTS

https://bib.irb.hr/datoteka/844447.Diplomski_2015_Luka_terbi.pdf

Address of the bookmark: https://github.com/mculinovic/EAGLER

Converting a VCF into a FASTA given some reference !

Jit — Fri, 20 Jul 2018 10:03:53 -0500

Samtools/BCFtools (Heng Li) provides a Perl script vcfutils.pl which does this, the function vcf2fq (lines 469-528)

This script has been modified by others to convert InDels as well, e.g. this by David Eccles

./vcf2fq.pl -f <input.fasta> <all-site.vcf> > <output.fastq>

https://github.com/gringer/bioinfscripts/blob/master/vcf2fq.pl

https://github.com/lh3/samtools/blob/master/bcftools/vcfutils.pl

SKESA: strategic k-mer extension for scrupulous assemblies

Jit — Wed, 14 Nov 2018 04:45:41 -0600

SKESA is a DeBruijn graph-based de-novo assembler designed for assembling reads of microbial genomes sequenced using Illumina. Comparison with SPAdes and MegaHit shows that SKESA produces assemblies that have high sequence quality and contiguity, handles low-level contamination in reads, is fast, and produces an identical assembly for the same input when assembled multiple times with the same or different compute resources.

Source code for SKESA is freely available at https://github.com/ncbi/SKESA/releases.

Research Paper @ Link

SKESA algorithm are as follows:

Address of the bookmark: https://github.com/ncbi/SKESA/releases