BOL: Related items

Genome assembly training tutorial at Galaxy !

Jit — Sun, 27 Dec 2020 05:25:45 -0600

In this tutorial we assemble and annotate the genome of E. coli strain C-1. This strain is routinely used in experimental evolution studies involving bacteriophages. For instance, now classic works by Holly Wichman and Jim Bull (Bull 1997, Bull 1998, Wichman 1999) have been performed using this strain and bacteriophage phiX174.

Address of the bookmark: https://training.galaxyproject.org/training-material/topics/assembly/tutorials/unicycler-assembly/tutorial.html

IVA: accurate de novo assembly of RNA virus genomes

Neel — Wed, 23 Jun 2021 07:51:59 -0500

IVA (Iterative Virus Assembler) designed specifically for read pairs sequenced at highly variable depth from RNA virus samples. We tested IVA on datasets from 140 sequenced samples from human immunodeficiency virus-1 or influenza-virus-infected people and demonstrated that IVA outperforms all other virus de novo assemblers.

Availability and implementation: The software runs under Linux, has the GPLv3 licence and is freely available from http://sanger-pathogens.github.io/iva

https://pubmed.ncbi.nlm.nih.gov/25725497/

Address of the bookmark: https://github.com/sanger-pathogens/iva

Short-read assembly using Spades !

Abhimanyu Singh — Mon, 31 Jan 2022 07:18:16 -0600

If we only had Illumina reads, we could also assemble these using the tool Spades.

You can try this here, or try it later on your own data.

Get data

We will use the same Illumina data as we used above:

illumina_R1.fastq.gz: the Illumina forward reads
illumina_R2.fastq.gz: the Illumina reverse reads

Assemble

Run Spades:

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

-1 is input file of forward reads
-2 is input file of reverse reads
--careful minimizes mismatches and short indels
--cov-cutoff auto computes the coverage threshold (rather than the default setting, “off”)
-o is the output directory

Results

Move into the output directory and look at the contigs:

infoseq contigs.fasta

Mitochondrial genome assembly tools !

Abhi — Wed, 06 Sep 2023 00:37:18 -0500

Mitochondrial genome assembly tools are specialized software and algorithms designed to accurately reconstruct the mitochondrial genome (mitogenome) from sequencing data, typically obtained through techniques like next-generation sequencing (NGS). The mitochondrial genome is relatively small compared to the nuclear genome, making it an ideal target for assembly. Here are some commonly used mitochondrial genome assembly tools:

MitoFinder: Mitofinder is a pipeline to assemble mitochondrial genomes and annotate mitochondrial genes from trimmed read sequencing data.

MitoHiFi: a python pipeline for mitochondrial genome assembly from PacBio high fidelity reads

MITObim: MITObim is a tool specifically developed for the iterative assembly of mitochondrial genomes. It starts with a reference mitogenome and iteratively refines the assembly using the read data.

MITOS: MITOS is a web-based platform that provides a pipeline for annotating mitochondrial genomes. It integrates multiple software tools for assembly, annotation, and visualization of mitogenomes.

MIRA: MIRA (Mimicking Intelligent Read Assembly) is a versatile genome assembly tool that can be used for mitochondrial genome assembly. It supports various sequencing technologies and allows for reference-based or de novo assembly.

NOVOPlasty: NOVOPlasty is a user-friendly tool designed for de novo assembly of organelle genomes, including mitochondria. It utilizes a seed-and-extend algorithm and is suitable for both short-read and long-read data.

MITOS2: MITOS2 is an updated version of the MITOS pipeline, which automates the annotation of mitochondrial genomes. It provides improved accuracy and additional features for mitochondrial genome analysis.

GetOrganelle: While primarily designed for chloroplast genome assembly, GetOrganelle can also be used for mitochondrial genome assembly. It is particularly useful for dealing with high-throughput sequencing data.

SPAdes: SPAdes (St. Petersburg genome assembler) is a versatile genome assembly tool that can be employed for mitochondrial genome assembly, especially when dealing with complex datasets that may contain nuclear mitochondrial DNA sequences (numts).

IDBA-UD: IDBA-UD (Iterative De Bruijn Graph De Novo Assembler) is another de novo assembly tool that can be used for mitochondrial genome assembly, especially in cases with relatively low coverage.

Velvet: Velvet is a de novo assembly tool that can be applied to mitochondrial genome assembly, especially when working with short-read data.

When selecting a mitochondrial genome assembly tool, it's important to consider the specific characteristics of your sequencing data, such as read length and coverage, as well as the complexity of the mitochondrial genome. Additionally, some tools are better suited for specific organisms or research objectives, so choosing the right tool will depend on your particular project requirements.

Sequence assembly with MIRA 4

Priya Singh — Wed, 06 Apr 2016 08:21:22 -0500

MIRA is a multi-pass DNA sequence data assembler/mapper for whole genome and EST/RNASeq projects. MIRA assembles/maps reads gained by

electrophoresis sequencing (aka Sanger sequencing)
454 pyro-sequencing (GS20, FLX or Titanium)
Ion Torrent
Solexa (Illumina) sequencing
(in development) Pacific Biosciences sequencing

into contiguous sequences (called contigs). One can use the sequences of different sequencing technologies either in a single assembly run (a true hybrid assembly) or by mapping one type of data to an assembly of other sequencing type (a semi-hybrid assembly (or mapping)) or by mapping a data against consensus sequences of other assemblies (a simple mapping).

The MIRA acronym stands for Mimicking Intelligent Read Assembly and the program pretty well does what its acronym says (well, most of the time anyway). It is the Swiss army knife of sequence assembly that I've used and developed during the past 14 years to get assembly jobs I work on done efficiently - and especially accurately. That is, without me actually putting too much manual work into it.

More at http://mira-assembler.sourceforge.net/docs/DefinitiveGuideToMIRA.html

Address of the bookmark: http://mira-assembler.sourceforge.net/docs/DefinitiveGuideToMIRA.html

Understanding Fastqc Output

Jit — Fri, 15 Apr 2016 05:47:40 -0500

Understanding Following table and graphs

Duplication level
kmer profile
per base GC content
per base N content
per base quality
per base sequence content
per sequence GC content
per sequence quality
sequence length distribution

More at http://www.bioinformatics.babraham.ac.uk/projects/fastqc/Help/3%20Analysis%20Modules/

Address of the bookmark: http://www.bioinformatics.babraham.ac.uk/projects/fastqc/Help/3%20Analysis%20Modules/

ALE: a Generic Assembly Likelihood Evaluation Framework for Assessing the Accuracy of Genome and Metagenome Assemblies

Neel — Tue, 26 Apr 2016 03:38:43 -0500

Assembly Likelihood Evaluation (ALE) framework that overcomes these limitations, systematically evaluating the accuracy of an assembly in a reference-independent manner using rigorous statistical methods. This framework is comprehensive, and integrates read quality, mate pair orientation and insert length (for paired-end reads), sequencing coverage, read alignment and k-mer frequency. ALE pinpoints synthetic errors in both single and metagenomic assemblies, including single-base errors, insertions/deletions, genome rearrangements and chimeric assemblies presented in metagenomes. At the genome level with real-world data, ALE identifies three large misassemblies from the Spirochaeta smaragdinae finished genome, which were all independently validated by Pacific Biosciences sequencing. At the single-base level with Illumina data, ALE recovers 215 of 222 (97%) single nucleotide variants in a training set from a GC-rich Rhodobacter sphaeroides genome. Using real Pacific Biosciences data, ALE identifies 12 of 12 synthetic errors in a Lambda Phage genome, surpassing even Pacific Biosciences' own variant caller, EviCons. In summary, the ALE framework provides a comprehensive, reference-independent and statistically rigorous measure of single genome and metagenome assembly accuracy, which can be used to identify misassemblies or to optimize the assembly process.

More at http://www.ncbi.nlm.nih.gov/pubmed/23303509

Address of the bookmark: http://sc932.github.io/ALE/about.html

GAM-NGS: genomic assemblies merger for next generation sequencing

Jit — Mon, 19 Dec 2016 06:07:05 -0600

GAM-NGS (Genomic Assemblies Merger for Next Generation Sequencing), whose primary goal is to merge two or more assemblies in order to enhance contiguity and correctness of both. GAM-NGS does not rely on global alignment: regions of the two assemblies representing the same genomic locus (called blocks) are identified through reads' alignments and stored in a weightedgraph. The merging phase is carried out with the help of this weighted graph that allows an optimal resolution of local problematic regions.

Address of the bookmark: https://github.com/vice87/gam-ngs

BRIG

Jit — Thu, 16 Feb 2017 13:14:25 -0600

BRIG is a free cross-platform (Windows/Mac/Unix) application that can display circular comparisons between a large number of genomes, with a focus on handling genome assembly data. The application is available at:http://sourceforge.net/projects/brig

If you have any questions or comments, post them on one of the trackers on BRIG’s SourceForge page:http://sourceforge.net/tracker/?group_id=328245.

Features:

Images show similarity between a central reference sequence and other sequences as concentric rings.
BRIG will perform all BLAST comparisons and file parsing automatically via a simple GUI.
Contig boundaries and read coverage can be displayed for draft genomes; customized graphs and annotations can be displayed.
Using a user-defined set of genes as input, BRIG can display gene presence, absence, truncation or sequence variation in a set of complete genomes, draft genomes or even raw, unassembled sequence data.
BRIG also accepts SAM-formatted read-mapping files enabling genomic regions present in unassembled sequence data from multiple samples to be compared simultaneously

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

PBSuite: Software for Long-Read Sequencing Data from PacBio

Jit — Mon, 27 Feb 2017 09:54:47 -0600

PBJelly - the genome upgrading tool.
PBHoney - the structural variation discovery tool

Both are contained within the PBSuite code found in downloads.

----- PBJelly -----
Read The Paper
http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0047768

PBJelly is a highly automated pipeline that aligns long sequencing reads (such as PacBio RS reads or long 454 reads in fasta format) to high-confidence draft assembles. PBJelly fills or reduces as many captured gaps as possible to produce upgraded draft genomes.

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

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.

Address of the bookmark: https://sourceforge.net/projects/pb-jelly/