BOL: Related items

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

HGA

Jit — Tue, 29 Nov 2016 07:25:53 -0600

HGA tool version 1.0 This tool helps to apply the Hierarchical Genome Assembly (HGA) method. The tool will apply: 1. Partitioning a given reads dataset into a given number of partitions. 2. Assembling each partitions using a pre-specified assembler (Velvet or SPAdes in this version) and using a given kmer size. 3. Merging all the assemblies of the partition. 4. Combining all the assemblies of the partition (using velvet with kmer value of 31). 5. Finaly, re-assembling the whole dataset with the merged contigs or the combined contigs, using a given kmer size.

https://github.com/aalokaily/Hierarchical-Genome-Assembly-HGA

Address of the bookmark: https://github.com/aalokaily/Hierarchical-Genome-Assembly-HGA

Bioinformatics Scientist, Production Bioinformatics @ South San Francisco, CA

Thu, 19 Aug 2021 08:45:24 -0500

wist is looking for a Bioinformatics Scientist to join our Production Bioinformatics Team. You will work alongside research scientists, software engineers and data scientists to further deliver on our mission to expand access to best-in-class synthetic biology and next-generation sequencing applications. You will be developing and engineering tools to better evaluate and build hardened, production quality pipelines, optimize data quality, and automate lab and bioinformatics processes. Our ideal candidate is an organized problem solver with a background in developing and building novel production-quality bioinformatics tools and packages. Equally excellent communication skills and a proven ability to work independently are required.

More at https://boards.greenhouse.io/twistbioscience/jobs/3135495?gh_src=9ecc0b941us

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

Job offer for a postdoctoral researcher in genomics / bioinformatics (2 years)

Fri, 22 Oct 2021 04:44:33 -0500

Ongoing research in the group of Karine Van Doninck involves topics at the core of
evolutionary biology, including the evolution of sex, genome maintenance,
recombination and extreme stress resistance on different eukaryotic systems,
including rotifers, amoeba and Corbicula clams. We are employing different tools
(including experimental ecology, population genetics, phylogeny, comparative
genomics, transcriptomics, bioinformatics, molecular and cellular biology) to study
evolutionary processes at the level of populations, both experimental and natural, and
genomes.

Offer
We offer a full-time contract for two years. The contract starts between October 2021
and December 2021. The position involves no or extremely light teaching load, if the
candidate is interested. Salaries are competitive at the European level. The recruited
person will benefit from the Belgian social insurance scheme (health care, etc.) without
additional expenses.

Profile
Applicants are expected to show outstanding commitment to research and must have
obtained a PhD by the start of the position. A strong expertise in genomics is required.
More specifically, solid competences in bioinformatics (e.g. scripting pipelines) and in
genome evolution are needed. Knowledge or interest regarding recombination,
metazoan evolution, phylogenomics and population genomics is an added-value.

Application
Applications should be submitted via email to karine.van.doninck@ulb.be. The
application package should contain the following documents:
- A curriculum vitae with the complete list of publications
- A cover letter mentioning why the candidate is interested in the position
- Minimum 2 recommendation letters
Interviews: Interviews will be conducted with the selected candidates. Selected
candidates could also be invited to give a seminar to MBE ULB.
For any additional information, please contact karine.van.doninck@ulb.be

The MARVEL assembler

Jit — Fri, 04 May 2018 19:18:41 -0500

MARVEL consists of a set of tools that facilitate the overlapping, patching, correction and assembly of noisy (not so noisy ones as well) long reads.

The assembly process can be summarized as follows:

overlap
patch reads
overlap (again)
scrubbing
assembly graph construction and touring
optional read correction
fasta file creation

Address of the bookmark: https://github.com/schloi/MARVEL

BAUM – Improving Genome Assembly by Adaptive Unique Mapping and Local Overlap-Layout-Consensus

Jit — Wed, 24 Oct 2018 23:35:09 -0500

BAUM, breaks the whole genome into regions by adaptive unique mapping; then the local OLC is used to assemble each region in parallel. BAUM can: (1) perform reference-assisted assembly based on the genome of a close species; (2) or improve the results of existing assemblies that are obtained based on short or long sequencing reads.

Address of the bookmark: http://www.zhanyuwang.xin/wordpress/index.php/2017/07/21/baum-improving-genome-assembly-by-adaptive-unique-mapping-and-local-overlap-layout-consensus/

RaGOO: Fast Reference-Guided Scaffolding of Genome Assembly Contigs

Jit — Sun, 27 Oct 2019 00:57:23 -0500

Alonge M, Soyk S, Ramakrishnan S, Wang X, Goodwin S, Sedlazeck FJ, Lippman ZB, Schatz MC: Fast and accurate reference-guided scaffolding of draft genomes. bioRxiv 2019.

RaGOO is a tool for coalescing genome assembly contigs into pseudochromosomes via minimap2 alignments to a closely related reference genome. The focus of this tool is on practicality and therefore has the following features:

Good performance. On a MacBook Pro using Arabidopsis data, pseudochromosome construction takes less than a minute and the whole pipeline with SV calling takes ~2 minutes.
Intact ordering and orienting of contigs.
Misassembly correction
GFF lift-over
Structural variant calling with and integrated version of Assemblytics
Confidence scores associated with the grouping, localization, and orientation for each contig.

Address of the bookmark: https://github.com/malonge/RaGOO

Genobuntu: Package for Next Generation Sequencing and Genome Assembly

BioStar — Mon, 18 May 2020 16:47:56 -0500

Genobuntu is a software package containing more than 70 software and packages oriented towards NGS. In its current version, Genobuntu supports pre assembly tools, genome assemblers as well as post assembly tools.

Commonly used biological software and example script files for different assembly pipelines have also been provided, where the example script files can be updated to suit one’s experimental needs. Genobuntu attempts to reduce the amount of time and energy needed to build software workstations and it can also act as a good teaching source for a class room setting.

Therefore, Genobuntu offers a well-tailored environment for both novices and experts working in the field of genome assembly.

Features

Velvet
MiB
SSAKE
EULER
VCAKE
ABySS
ALLPATHS
Celera
SHARCGS
Allpaths
IDBA
TAIPAN
Edena
SOAPdenovo
Maq
IDBA-UD
No. of Reads present in the Ref. Seq.
ART NGS Reads Simulator
HiTEC, FASTQC
Minimum Description Length
SOAPaligner
Sequencing Read Archive Toolkit

Address of the bookmark: https://sourceforge.net/projects/genobuntu/

QuasiModo - Quasispecies Metric Determination on Omics

Neel — Sat, 26 Jun 2021 15:22:56 -0500

This repository contains the scripts and pipeline that reproduces the results of the HCMV benchmarking study. In this study we evaluated genome assemblers and variant callers on 10 in vitro generated, mixed strain HCMV sequence samples, each consisting of two lab strains in different abundance ratios. This tool can also be used to evaluate assemblies and variant calling results on other similar datasets.

https://academic.oup.com/bib/article/22/3/bbaa123/5868070

Address of the bookmark: https://github.com/hzi-bifo/Quasimodo