BOL: Related items

Hapsembler: An Assembler for Highly Polymorphic Genomes

Jit — Tue, 22 May 2018 04:09:53 -0500

Hapsembler is a haplotype-specific genome assembly toolkit that is designed for genomes that are rich in SNPs and other types of polymorphism. Hapsembler can be used to assemble reads from a variety of platforms including Illumina and Roche/454. http://compbio.cs.toronto.edu/hapsembler/

Address of the bookmark: http://compbio.cs.toronto.edu/hapsembler/

Protocol for De novo Genome Assembly using Illumina Reads

BioStar — Sat, 16 Jan 2021 21:42:11 -0600

In this protocol, we address and describe the de novo assembly method for small to medium-sized genomes.

What is de novo genome assembly?
The method of taking a large number of short DNA sequences and placing them back together to create a reflection of the original chromosomes from which the DNA originated relates to genome assembly. No previous knowledge of the source DNA sequence length, structure or composition is inferred by De novo genome assemblies. The DNA of the target organism is split up into millions of tiny parts and read on a sequencing computer in a genome sequencing experiment. Depending on the sequencing system used, these "reads" range from 20 to 1000 nucleotide base pairs (bp) in length. Usually, length reads of 36 - 150 bp are produced for Illumina style short read sequencing. These reads can be either “single ended” as described above or “paired end.”

Why genome assembly?
In basic research into why and how they live, as well as in applied topics, identifying the DNA sequence of an organism is useful. Awareness of a DNA sequence may be useful in virtually any biological research because of the relevance of DNA to living things. For example, it may be used in medicine to classify, diagnose and eventually improve genetic disorder therapies. Similarly, pathogens study can lead to treatments for infectious diseases.

Raw NGS data
Reads can be saved as a Fasta file as text or in a FastQ file with their attributes. FastQ is the most common read file format since this is what the Illumina sequencing pipeline creates. This will henceforth be the subject of our conversation.

In a nutshell the protocol:
Get the sequence file(s) read from the sequencing machine (s).
Look at the readings - have an idea of what you have and what the standard is like.
If required, raw data cleanup/quality trimming.
Choose an adequate parameter set for assembly.
Assemble the data into scaffolds/contigs.
Examine the assembly performance and determine the efficiency of the assembly.

Read Quality Control:
Check the qualiy with fastQC.
Script
https://bioinformaticsonline.com/snippets/view/42540/install-fastqc-using-conda

Quality trimming/cleanup of read files.
This function trims adapters, barcodes and other contaminants from the reads.
Script
https://bioinformaticsonline.com/snippets/view/42542/trimmomatic-command

Genome Assembly:
The object of this portion of the protocol is to explain the method of assembling the reads trimmed by quality into draft contigs.

spades.py -1 illumina_R1.fastq.gz -2 illumina_R2.fastq.gz --careful --cov-cutoff auto -o result_of_spades_assembly_all_illumina

A significant range of short-read assemblers are available. Everyone with strengths and disadvantages of their own.
Some of the assemblers available include:
Velvet
SOAP-denovo
MIRA
ALLPATHS

Next step is to assess the suitability and what to do with a draft package of contiguous details for the remainder of the study now. Few stuff you can note about the contigs you just created: They're the draft Contigs. Any mis-assemblies can occur.

Mis-assembly checking and assembly metric tools:
QUAST - Quality assessment tool for genome assembly http://bioinf.spbau.ru/quast
Mauve assembly metrics - http://code.google.com/p/ngopt/wiki/How_To_Score_Genome_Assemblies_with_Mauve
InGAP-SV - https://sites.google.com/site/nextgengenomics/ingap and http://ingap.sourceforge.net/
inGAP is also useful for finding structural variants between genomes from read mappings.

Genome finishing tools:
Semi-automated gap fillers:
Gap filler - http://www.baseclear.com/landingpages/basetools-a-wide-range-of-bioinformatics-solutions/gapfiller/

IMAGE (V2) - http://sourceforge.net/apps/mediawiki/image2/index.php?title=Main_Page

Genome visualisers and editors:
Artemis - http://www.sanger.ac.uk/resources/software/artemis/
IGV - http://www.broadinstitute.org/igv/

Automated and semi automated annotation tools:
Prokka - https://github.com/tseemann/prokka
RAST - http://www.nmpdr.org/FIG/wiki/view.cgi/FIG/RapidAnnotationServer
JCVI Annotation Service - http://www.jcvi.org/cms/research/projects/annotation-service/

Frequent command use for the analysis are at:

https://bioinformaticsonline.com/blog/view/38765/list-of-tools-frequently-used-while-genome-assembly
https://bioinformaticsonline.com/pages/view/42275/frequent-parameters-for-bioinformatics-tools

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

Bandage: interactive visualization of de novo genome assemblies

Shruti Paniwala — Mon, 04 Dec 2017 10:09:37 -0600

Bandage (a Bioinformatics Application for Navigating De novo Assembly Graphs Easily) is a tool for visualizing assembly graphs with connections. Users can zoom in to specific areas of the graph and interact with it by moving nodes, adding labels, changing colors and extracting sequences. BLAST searches can be performed within the Bandage graphical user interface and the hits are displayed as highlights in the graph. By displaying connections between contigs, Bandage presents new possibilities for analyzing de novo assemblies that are not possible through investigation of contigs alone.

Availability and implementation: Source code and binaries are freely available at https://github.com/rrwick/Bandage. Bandage is implemented in C++ and supported on Linux, OS X and Windows. A full feature list and screenshots are available at http://rrwick.github.io/Bandage.

Address of the bookmark: http://rrwick.github.io/Bandage/

DFAST: a flexible prokaryotic genome annotation pipeline for faster genome publication

Jit — Tue, 14 Nov 2017 10:26:16 -0600

We developed a prokaryotic genome annotation pipeline, DFAST, that also supports genome submission to public sequence databases. DFAST was originally started as an on-line annotation server, and to date, over 7,000 jobs have been processed since its first launch in 2016. Here, we present a newly implemented background annotation engine for DFAST, which is also available as a standalone command-line program. The new engine can annotate a typical-sized bacterial genome within 10 minutes, with rich information such as pseudogenes, translation exceptions, and orthologous gene assignment between given reference genomes. In addition, the modular framework of DFAST allows users to customize the annotation workflow easily and will also facilitate extensions for new functions and incorporation of new tools in the future.

Availability and Implementation

The software is implemented in Python 3 and runs in both Python 2.7 and 3.4– on Macintosh and Linux systems. It is freely available at https://github.com/nigyta/dfast_core/ under the GPLv3 license with external binaries bundled in the software distribution. An on-line version is also available at https://dfast.nig.ac.jp/.

Address of the bookmark: https://dfast.nig.ac.jp/

Genome U-Plot: a whole genome visualization

Rahul Nayak — Fri, 13 Jul 2018 19:50:41 -0500

Genome U-Plot for producing clear and intuitive graphs that allows researchers to generate novel insights and hypotheses by visualizing SVs such as deletions, amplifications, and chromoanagenesis events. The main features of the Genome U-Plot are its layered layout, its high spatial resolution and its improved aesthetic qualities.

https://github.com/gaitat/GenomeUPlot

Address of the bookmark: https://github.com/gaitat/GenomeUPlot

GRSR: a tool for deriving genome rearrangement scenarios from multiple unichromosomal genome sequences

Jit — Fri, 28 Sep 2018 09:35:10 -0500

GRSR is a Tool for Deriving Genome Rearrangement Scenarios for Multiple Uni-chromosomal Genomes. This tool will do the following steps:

Step 1. Run mugsy to get multiple sequence alignment results.
Step 2 & 3. Extraction of the Coordinates of Core Blocks, Construction of Synteny Blocks and Generating Signed Permutations.
Step 4. Generate pairwise genome rearrangement scenarios and find repeats at the breakpoints of each rearrangement events.

https://github.com/DanwangJessica/GRSR

Address of the bookmark: https://github.com/DanwangJessica/GRSR

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

Genome Workbench 2.10.7

Gudiya Pal — Fri, 01 Jul 2016 12:09:59 -0500

Genome Workbench 2.10.7 is here! New features include added support for local custom BLAST databases and improvements to Tree View.

For the full list of features, improvements and fixes, see the release notes:https://ncbi.nlm.nih.gov/tools/gbench/releasenotes

New Features

BLAST Tool: added support for local custom BLAST databases
Graphical Sequence View: added log scaling option for graph tracks
Generic Table View: new tutorial added

Bug Fixes and Improvements

Project Tree View: Genomic Collections/Assemblies now show accessions, not just names
Tree View: layout updated to better accommodate nodes of different sizes
Table Import Dialog (MacOS): fixed issue with table visibility
Fixed bug where different molecules IDs in GenBank could resolve to the same sequence
Graphical Sequence View: fixed issue where sequence track was not shown for some sequences
Graphical Sequence View: fixed protein coloration methods
Graphical Sequence View: improved rendering of Markers to better indicate boundaries and produce higher quality PDF images
Create Gene Model tool: fixed scenario when gene model tool failed with local sequences
Search View: ORF Finder – fixed incorrect protein lengths
Fixed bug with not opening project file (.gbp) on a click
Fixed issues in GVF import
Fixed BLAST Search tool against NCBI databases not working
Fixed tblastn (protein BLAST) not working in standalone mode
Fixed GTF export failure

RepeatModeler

Jit — Thu, 18 Aug 2016 09:57:15 -0500

RepeatModeler is a de-novo repeat family identification and modeling package. At the heart of RepeatModeler are two de-novo repeat finding programs ( RECON and RepeatScout ) which employ complementary computational methods for identifying repeat element boundaries and family relationships from sequence data. RepeatModeler assists in automating the runs of RECON and RepeatScout given a genomic database and uses the output to build, refine and classify consensus models of putative interspersed repeats.

Address of the bookmark: http://www.repeatmasker.org/RepeatModeler.html