BOL: Related items

Ancient whole genome duplication (WGD) detection tools !

Rahul Nayak — Sun, 07 Mar 2021 00:32:44 -0600

There are two methods for ancient WGD detection, one is collinearity analysis, and the other is based on the Ks distribution map. Among them, Ks is defined as the average number of synonymous substitutions at each synonymous site, and there is also a Ka corresponding to it, which refers to the average number of non-synonymous substitutions at each non-synonymous site.

At present, some people have posted articles about the analysis process of WGD. I searched for the keyword "wgd pipeline" and found the following:

GenoDup: https:// github.com/MaoYafei/GenoDup-Pipeline
https://peerj.com/articles/6303/
WGDdetector: https:// github.com/yongzhiyang2 012/WGDdetector
https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-2670-3
wgd: https:// github.com/arzwa/wgd
https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1142-2#Sec1
https://bmcbiol.biomedcentral.com/articles/10.1186/s12915-017-0399-x
GeNoGAP https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1142-2
https://bmcbiol.biomedcentral.com/articles/10.1186/s12915-017-0399-x
https://github.com/dfguan/purge_dups
https://www.biorxiv.org/content/10.1101/2020.01.24.917997v1

This article introduces the usage of wgd.

Wgd cannot be installed directly with bioconda at present, so it is a little troublesome to install, because it depends on a lot of software. wgd depends on the following software

BLAST
MCL
MUSCLE/MAFFT/PRANK
PAML
PhyML/FastTree
i-ADHoRe

But the good news is that most of the software it depends on can be installed with bioconda

conda create -n wgd python=3.5 blast mcl muscle mafft prank paml fasttree cmake libpng mpi=1.0=mpich
conda activate wgd

Here mpi=1.0=mpich is selected, because i-adhore depends on mpich. If openmpi is installed, an error will appear while loading shared libraries: libmpi_cxx.so.40: cannot open shared object file: No such file or directory

After that, the installation is much simpler

git clone https://github.com/arzwa/wgd.git
cd wgd
pip install .
pip install git+https://github.com/arzwa/wgd.git
For i-ADHoRe, you need to register at http:// bioinformatics.psb.ugent.be /webtools/i-adhore/licensing/Agree to the license to download i-ADHoRe-3.0

Since my miniconda3 installed ~/opt/, the installation path is so~/opt/miniconda3/envs/wgd/

tar -zxvf i-adhore-3.0.01.tar.gz
cd i-adhore-3.0.01
mkdir -p build && cd build
cmake .. -DCMAKE_INSTALL_PREFIX=~/opt/miniconda3/envs/wgd/
make -j 4
make insatall

Take the sugarcane genome Saccharum spontaneum L as an example. The genome is 8-ploid with 32 chromosomes (2n = 4x8 = 32)

Download the tutorial for CDS and GFF annotation files

mkdir -p wgd_tutorial && cd wgd_tutorial
wget http://www.life.illinois.edu/ming/downloads/Spontaneum_genome/Sspon.v20190103.cds.fasta.gz
wget http://www.life.illinois.edu/ming/downloads/Spontaneum_genome/Sspon.v20190103.gff3.gz
gunzip *.gz

First conda activate wgdstart our analysis environment, and then start the analysis

Step 1 : Use to wgd mclidentify homologous genes in the genome

wgd mcl -n 20 --cds --mcl -s Sspon.v20190103.cds.fasta -o Sspon_cds.out

Step 2 : Use to wgd ksdbuild Ks distribution

wgd ksd --n_threads 80 Sspon_cds.out/Sspon.v20190103.cds.fasta.blast.tsv.mcl Sspon.v20190103.cds.fasta

Step 3 : If the quality of the genome is good, then wgd syncollinearity analysis can be used . It can help us find the collinearity block in the genome and the corresponding anchor point

wgd syn --feature gene --gene_attribute ID \
-ks wgd_ksd/Sspon.v20190103.cds.fasta.ks.tsv \
Sspon.v20190103.gff3 Sspon_cds.out/Sspon.v20190103.cds.fasta.blast.tsv.mcl

For more reading - There are 9 sub-modules in WGD

kde: KDE fitting to the Ks distribution
ksd: Ks distribution construction
mcl: BLASP comparison of All-vs-ALl + MCL classification analysis.
mix: Hybrid modeling of Ks distribution.
pre: preprocess the CDS file
syn: Call I-ADHoRe 3.0 to use GFF files for collinearity analysis
viz: draw histogram and density plot
wf1: Ks standard analysis procedure of the whole genome paranome (paranome), call mcl, ksd and syn
wf2: Ks standard analysis procedure of one-vs-one homologous gene (ortholog), call wcl and kSD

Strudel

Anjana — Fri, 30 Sep 2016 09:47:02 -0500

Strudel is our graphical tool for visualizing genetic and physical maps of genomes for comparative purposes. The application aims to let the user examine their data at a variety of different levels of resolution, from entire maps to individual markers, and explore syntenic relationships between genomes. All browsing and interaction with Strudel happens in real-time – there is no need to wait while the maps are generated. It is built using Java 1.6 and ships with its own JRE, so there is no need for users to install or update Java.

Address of the bookmark: https://ics.hutton.ac.uk/strudel/

DESCHRAMBLER

Jit — Thu, 29 Jun 2017 11:54:59 -0500

DESCHRAMBLER is shown to produce highly accurate reconstructions using data simulation and by benchmarking it against other reconstruction tools

You can find the detail of reconstructed data at http://bioinfo.konkuk.ac.kr/DESCHRAMBLER/

Address of the bookmark: https://github.com/jkimlab/DESCHRAMBLER

Rectangle Graph for Repeat Resolution in Genome Assembly

Rahul Nayak — Thu, 28 Dec 2017 09:43:03 -0600

Ultimate tool for resolving repeats in genome assemblies.

Though the specific implementation of the idea of the rectangle graph approach is already included into the current SPAdes distribution, we're also releasing the Rectangle Graph Module (RGM) as the separate code which can be run independently of SPAdes. Although RGM differs from the current implementation of the rectangle graph approach in SPAdes, in the future we plan to integrate RGM in SPAdes. RGM can be run with other genome assemblers if they use the graph format as SPAdes files.

For more details see: Nikolay Vyahhi, Son K. Pham, Pavel Pevzner. From de Bruijn Graphs to Rectangle Graphs for Genome Assembly, Lecture Notes in Bioinformatics 7534 (2012), pp. 249-261.

Address of the bookmark: http://bioinf.spbau.ru/en/rectangles

fragScaff: Genome Assembly with Contiguity Preserving Transposition

Jit — Mon, 14 May 2018 04:28:14 -0500

Contiguity preserving transposition and sequencing (CPT-seq) is an entirely in vitro means of generating libraries comprised of 9216 indexed pools, each of which contains thousands of sparsely sequenced long fragments ranging from 5 kilobases to >1 megabase. This software, fragScaff, leverages coincidences between the content of different pools as a source of contiguity information for scaffolding de novo genome assemblies. FragScaff is complementary to Lachesis, providing midrange contiguity to support robust, accurate chromosome-scale de novo genome assemblies without the need for laborious in vivo cloning steps.

Further information about fragScaff, including source code, is available at:https://sourceforge.net/projects/fragscaff/files.

Manuscript describing fragScaff was published as: Adey A, Kitzman JO, Burton JN, Daza R, Kumar A, Christiansen L, Ronaghi M, Amini S, L Gunderson K, Steemers FJ, Shendure J#. In vitro, long-range sequence information for de novo genome assembly via transposase contiguity. Genome Research 2014 Dec;24(12):2041-9. doi: 10.1101/gr.178319.114. PubMed PMID: 25327137.

Address of the bookmark: https://sourceforge.net/projects/fragscaff/files/

Peregrine & SHIMMER Genome Assembly Toolkit

Abhi — Thu, 16 Dec 2021 02:50:19 -0600

Peregrine is a fast genome assembler for accurate long reads (length > 10kb, accuracy > 99%). It can assemble a human genome from 30x reads within 20 cpu hours from reads to polished consensus. It uses Sparse HIereachical MimiMizER (SHIMMER) for fast read-to-read overlaping without quadratic comparisions used in other OLC assemblers.

Address of the bookmark: https://github.com/cschin/Peregrine

Delta: a new Web-based 3D genome visualization and analysis platform

Jit — Wed, 20 Dec 2017 08:49:55 -0600

Delta is an integrative visualization and analysis platform to facilitate visually annotating and exploring the 3D physical architecture of genomes. Delta takes Hi-C or ChIA-PET contact matrix as input and predicts the topologically associating domains and chromatin loops in the genome. It then generates a physical 3D model which represents the plausible consensus 3D structure of the genome. Deltafeatures a highly interactive visualization tool which enhances the integration of genome topology/physical structure with extensive genome annotation by juxtaposing the 3D model with diverse genomic assay outputs.

https://github.com/zhangzhwlab/delta

Address of the bookmark: https://github.com/zhangzhwlab/delta

JBrowse: Embeddable genome browser built completely with JavaScript and HTML5

Jit — Fri, 29 Jun 2018 09:19:56 -0500

JBrowse is a fast, embeddable genome browser built completely with JavaScript and HTML5, with optional run-once data formatting tools written in Perl. Headline Features: Fast, smooth scrolling and zooming. Explore your genome with unparalleled speed. Scales easily to multi-gigabase genomes and deep-coverage sequencing. Quickly open and view data files on your computer without uploading them to any server. Supports GFF3, BED, FASTA, Wiggle, BigWig, BAM, VCF (with either .tbi or .idx index), REST, and more. BAM, BigBed, BigWig, and VCF data are displayed directly from chunks of the compressed binary files, no conversion needed. Includes an optional “faceted” track selector (see demo) suitable for large installations with thousands of tracks. Very light server resource requirements. In fact, JBrowse has no back-end server code, just tools for formatting data files to be read directly over HTTP. Serve huge datasets from a single low-cost cloud instance. Can run as a stand-alone app on OSX and Windows using the Electron platform Highly extensible plugin architecture, with a large plugin registry of existing examples here https://gmod.github.io/jbrowse-registry https://jbrowse.org/

Address of the bookmark: https://github.com/GMOD/jbrowse

Synima: a Synteny imaging tool for annotated genome assemblies

Abhimanyu Singh — Tue, 30 Oct 2018 10:49:13 -0500

Synima written in Perl, which uses the graphical features of R. Synima takes orthologues computed from reciprocal best BLAST hits or OrthoMCL, and DAGchainer, and outputs an overview of genome-wide synteny in PDF. Each of these programs are included with the Synima package, and a pipeline for their use. Synima has a range of graphical parameters including size, colours, order, and labels, which are specified in a config file generated by the first run of Synima – and can be subsequently edited. Synima runs quickly on a command line to generate informative and publication quality figures. Synima is open source and freely available from https://github.com/rhysf/Synima under the MIT License.

Address of the bookmark: https://github.com/rhysf/Synima

Cogent: a tool for reconstructing the coding genome using high-quality full-length transcriptome sequences.

Jit — Tue, 18 Jun 2019 05:33:04 -0500

Cogent is a tool that identifies gene families and reconstructs the coding genome using high-quality transcriptome data without a reference genome, and can be used to check assemblies for the presence of these known coding sequences.

Cogent is a tool for reconstructing the coding genome using high-quality full-length transcriptome sequences. It is designed to be used on Iso-Seq data and in cases where there is no reference genome or the ref genome is highly incomplete.

See a recent presentation on Cogent being applied to the Cuttlefish Iso-Seq data.

Cogent preliminary draft paper (updated 2016Dec version), Supplementary

Please see wiki for details on usage.

Address of the bookmark: https://github.com/Magdoll/Cogent