BOL: Related items

Evaluation of genome assembly software based on long reads

BioStar — Fri, 01 Feb 2019 11:55:54 -0600

TGS technologies have been used to produce highly accurate de novo assemblies of hundreds of microbial genomes and highly contiguous reconstructions of many dozens of plant and animal genomes, enabling new insights into evolution and sequence diversity. They have also been applied to resequencing analyses, to create detailed maps of structural variations in many species. Also, these new technologies have been used to fill in many of the gaps in the human reference genome.

In this report, we compare and evaluate several genome assembly software based on TSG technology. The experimentation has been performed on 4 reference genomes and the results evaluated with the QUAST software. The 11 software that have been evaluated are: Celera Assembler , Falcon , Miniasm, Newbler , SGA Assembler, Smartdenovo, Abruijn, Ra, DBG2OLC, Spades and Cerulean. The first 8 software use only long reads, while the 3 last software can merge long and short reads

NextDenovo: string graph-based de novo assembler for TGS long reads

Jit — Sun, 05 Jan 2020 04:08:29 -0600

NextDenovo is a string graph-based de novo assembler for TGS long reads. It uses a "correct-then-assemble" strategy similar to canu, but requires significantly less computing resources and storages. After assembly, the per-base error rate is about 97-98%, to further improve single base accuracy, please use NextPolish.

NextDenovo contains two core modules: NextCorrect and NextGraph. NextCorrect can be used to correct TGS long reads with approximately 15% sequencing errors, and NextGraph can be used to construct a string graph with corrected reads. It also contains a modified version of minimap2 for adapting input and output and producing more sensitive and accurate dovetail overlaps, and some useful utilities (see here for more details).

Address of the bookmark: https://github.com/Nextomics/NextDenovo

Deepbinner: a signal-level demultiplexer for Oxford Nanopore reads

Jit — Mon, 10 Feb 2020 02:45:53 -0600

Deepbinner is a tool for demultiplexing barcoded Oxford Nanopore sequencing reads. It does this with a deep convolutional neural network classifier, using many of the architectural advances that have proven successful in image classification. Unlike other demultiplexers (e.g. Albacore and Porechop), Deepbinner identifies barcodes from the raw signal (a.k.a. squiggle) which gives it greater sensitivity and fewer unclassified reads.

Address of the bookmark: https://github.com/rrwick/Deepbinner

SHAMAN: a user-friendly website for metataxonomic analysis from raw reads to statistical analysis

BioStar — Mon, 17 Aug 2020 05:21:09 -0500

SHAMAN is a shiny application for differential analysis of metagenomic data (16S, 18S, 23S, 28S, ITS and WGS) including bioinformatics treatment of raw reads for targeted metagenomics, statistical analysis and results visualization with a large variety of plots (barplot, boxplot, heatmap, …).
The bioinformatics treatment is based on Vsearch [Rognes 2016] which showed to be both accurate and fast [Wescott 2015].The statistical analysis is based on DESeq2 R package [Anders and Huber 2010] which robustly identifies the differential abundant features as suggested in [McMurdie and Holmes 2014] and [Jonsson2016]. SHAMAN robustly identifies the differential abundant genera with the Generalized Linear Model implemented in DESeq2 [Love 2014].
SHAMAN is compatible with standard formats for metagenomic analysis (.csv, .tsv, .biom) and figures can be downloaded in several formats. A presentation about SHAMAN is available here and a poster here.

More at https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-03666-4

Address of the bookmark: https://github.com/aghozlane/shaman

AlignGraph2: similar genome-assisted reassembly pipeline for PacBio long reads

Rahul Nayak — Sun, 14 Mar 2021 09:42:47 -0500

AlignGraph2 is the second version of AlignGraph for PacBio long reads. It extends and refines contigs assembled from the long reads with a published genome similar to the sequencing genome.

More at https://academic.oup.com/bib/advance-article-abstract/doi/10.1093/bib/bbab022/6146772

Address of the bookmark: https://github.com/huangs001/AlignGraph2

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

SqueezeMeta: a fully automated metagenomics pipeline, from reads to bins

BioStar — Sat, 06 Jul 2024 04:29:16 -0500

SqueezeMeta is a full automatic pipeline for metagenomics/metatranscriptomics, covering all steps of the analysis. SqueezeMeta includes multi-metagenome support allowing the co-assembly of related metagenomes and the retrieval of individual genomes via binning procedures. Thus, SqueezeMeta features several unique characteristics:

Co-assembly procedure with read mapping for estimation of the abundances of genes in each metagenome
Co-assembly of a large number of metagenomes via merging of individual metagenomes
Includes binning and bin checking, for retrieving individual genomes
The results are stored in a database, where they can be easily exported and shared, and can be inspected anywhere using a web interface.
Internal checks for the assembly and binning steps inform about the consistency of contigs and bins, allowing to spot potential chimeras.
Metatranscriptomic support via mapping of cDNA reads against reference metagenomes

Address of the bookmark: https://github.com/jtamames/SqueezeMeta

mrFAST: Micro Read Fast Alignment Search Tool

Neel — Tue, 26 Apr 2016 03:50:06 -0500

mrFAST is a read mapper that is designed to map short reads to reference genome with a special emphasis on the discovery of structural variation and segmental duplications. mrFAST maps short reads with respect to user defined error threshold, including indels up to 4+4 bp. This manual, describes how to choose the parameters and tune mrFAST with respect to the library settings. mrFAST is designed to find 'all' mappings for a given set of reads, however it can return one "best" map location if the relevant parameter is invoked.

More at http://mrfast.sourceforge.net/manual.html

Address of the bookmark: http://mrfast.sourceforge.net/manual.html

LoRMA: a tool for correcting sequencing errors in long reads such those produced by Pacific Biosciences sequencing machines

Jit — Wed, 15 Jun 2016 17:18:36 -0500

LoRMA is a tool for correcting sequencing errors in long reads such those produced by Pacific Biosciences sequencing machines.

Publication:

L. Salmela, R. Walve, E. Rivals, and E. Ukkonen: Accurate selfcorrection of errors in long reads using de Bruijn graphs. Accepted to RECOMB-Seq 2016.

Download:

Address of the bookmark: https://www.cs.helsinki.fi/u/lmsalmel/LoRMA/

ART: Set of Simulation Tools

Jit — Thu, 03 Nov 2016 08:28:25 -0500

ART is a set of simulation tools to generate synthetic next-generation sequencing reads. ART simulates sequencing reads by mimicking real sequencing process with empirical error models or quality profiles summarized from large recalibrated sequencing data. ART can also simulate reads using user own read error model or quality profiles. ART supports simulation of single-end, paired-end/mate-pair reads of three major commercial next-generation sequencing platforms: Illumina's Solexa, Roche's 454 and Applied Biosystems' SOLiD. ART can be used to test or benchmark a variety of method or tools for next-generation sequencing data analysis, including read alignment, de novo assembly, SNP and structure variation discovery. ART was used as a primary tool for the simulation study of the 1000 Genomes Project . ART is implemented in C++ with optimized algorithms and is highly efficient in read simulation. ART outputs reads in the FASTQ format, and alignments in the ALN format. ART can also generate alignments in the SAM alignment or UCSC BED file format. ART can be used together with genome variants simulators (e.g. VarSim) for evaluating variant calling tools or methods.

Address of the bookmark: http://www.niehs.nih.gov/research/resources/software/biostatistics/art/