BOL: Related items

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

Genome assembly stats plotting

Jit — Wed, 28 Feb 2018 03:45:39 -0600

A de novo genome assembly can be summarised b

y a number of metrics, including:

Overall assembly length
Number of scaffolds/contigs
Length of longest scaffold/contig
Scaffold/contig N50 and N90Assembly base composition, in particular percentage GC and percentage Ns
CEGMA completeness
Scaffold/contig length/count distribution

assembly-stats supports two widely used presentations of these values, tabular and cumulative length plots, and introduces an additional circular plot that summarises most commonly used assembly metrics in a single visualisation. Each of these presentations is generated using javascript from a common (JSON) data structure, allowing toggling between alternative views, and each can be applied to a single or multiple assemblies to allow direct comparison of alternate assemblies.

Tabular presentation allows direct comparison of exact values between assemblies, the limitations of this approach lie in the necessary omission of distributions and the challenge of interpreting ratios of values that may vary by several orders of magnitude.

Address of the bookmark: https://github.com/rjchallis/assembly-stats

Earth BioGenome Project

Jit — Wed, 25 Apr 2018 07:48:56 -0500

The central goal of the Earth BioGenome Project is to understand the evolution and organization of life on our planet by sequencing and functionally annotating the genomes of 1.5 million known species of eukaryotes, a massive group that includes plants, animals, fungi and other organisms whose cells have a nucleus that houses their chromosomal DNA. To date, the genomes of less than 0.2 percent of eukaryotic species have been sequenced.

More at https://www.ucdavis.edu/news/earth-biogenome-project-aims-sequence-dna-all-complex-life

GMcloser: closing gaps in assemblies accurately with a likelihood-based selection of contig or long-read alignments

Shruti Paniwala — Mon, 11 Jun 2018 05:43:44 -0500

GMcloser uses likelihood-based classifiers calculated from the alignment statistics between scaffolds, contigs and paired-end reads to correctly assign contigs or long reads to gap regions of scaffolds, thereby achieving accurate and efficient gap closure. We demonstrate with sequencing data from various organisms that the gap-closing accuracy of GMcloser is 3–100-fold higher than those of other available tools, with similar efficiency. https://academic.oup.com/bioinformatics/article/31/23/3733/209212

Address of the bookmark: https://academic.oup.com/bioinformatics/article/31/23/3733/209212

Roary: the Pan Genome Pipeline

Jit — Tue, 22 Jan 2019 05:52:07 -0600

Roary is a high speed stand alone pan genome pipeline, which takes annotated assemblies in GFF3 format (produced by Prokka (Seemann, 2014)) and calculates the pan genome. Using a standard desktop PC, it can analyse datasets with thousands of samples, something which is computationally infeasible with existing methods, without compromising the quality of the results. 128 samples can be analysed in under 1 hour using 1 GB of RAM and a single processor. To perform this analysis using existing methods would take weeks and hundreds of GB of RAM. Roary is not intended for meta-genomics or for comparing extremely diverse sets of genomes.

Address of the bookmark: https://sanger-pathogens.github.io/Roary/

RaGOO: Fast Reference-Guided Scaffolding of Genome Assembly Contigs

BioJoker — Wed, 17 Apr 2019 19:45:22 -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.
Chimeric contig 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

MGSE: Mapping-based Genome Size Estimation

Shruti Paniwala — Fri, 17 Jan 2020 02:11:43 -0600

MGSE can harness the power of files generated in genome sequencing projects to predict the genome size. Required are the FASTA file containing a high continuity assembly and a BAM file with all available reads mapped to this assembly. The script construct_cov_file.py (https://doi.org/10.1186/s12864-018-5360-z) allows the generation of a COV file based on the (sorted) BAM file (also possible via MGSE directly). Next, this COV file can be used by MGSE to calculate the coverage in provided reference regions and to calculate the total number of mapped bases. Both values are subjected to the genome size estimation. Providing accurate reference regions is crucial for this genome size estimation.

Address of the bookmark: https://github.com/bpucker/MGSE

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

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

OGDRAW - Draw Organelle Genome Maps

Abhi — Tue, 05 Oct 2021 03:34:35 -0500

OrganellarGenomeDRAW converts annotations in the GenBank or EMBL/ENA format into graphical maps. The input has to be a GenBank or EMBL/ENA flat file wherase the output can vary among several types of files. The application is optimized to create detailed high-quality maps of organellar genomes (plastid and mitochondria). Nevertheless, you can upload most database entries.

Please take a look at our FAQ section and do not hesitate to report bugs or suggestions for improvements by email.

Address of the bookmark: https://chlorobox.mpimp-golm.mpg.de/OGDraw.html