BOL: Related items

Genome assembly forensics: finding the elusive mis-assembly

Jit — Sat, 26 Jan 2019 18:02:01 -0600

We present the first collection of tools aimed at automated genome assembly validation. This work formalizes several mechanisms for detecting mis-assemblies, and describes their implementation in our automated validation pipeline, called amosvalidate. We demonstrate the application of our pipeline in both bacterial and eukaryotic genome assemblies, and highlight several assembly errors in both draft and finished genomes. The software described is compatible with common assembly formats and is released, open-source, at http://amos.sourceforge.net.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2397507/

http://amos.sourceforge.net/wiki/index.php/AMOS

Address of the bookmark: http://amos.sourceforge.net/wiki/index.php/AMOS

GMASS: a novel measure for genomeassembly structural similarity

Abhimanyu Singh — Sun, 14 Apr 2019 20:35:40 -0500

The GMASS score is a novel measure for representing structural similarity between two assemblies. It will contribute to the understanding of assembly output and developing de novo assemblers.

https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-2710-z

Address of the bookmark: http://bioinfo.konkuk.ac.kr/GMASS/htdocs/syncircos.php

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

MEC: Contig Misassembly Correction

BioStar — Tue, 04 Feb 2020 23:40:49 -0600

MEC, to identify and correct misassemblies in contigs. Firstly, MEC takes fragment coverage as the feature to detect the candidate misassemblies. Then, it can distinguish a large number of false positives from the candidate misassemblies based on the distribution of paired-end reads and the statistical analysis of GC-contents. We apply MEC to four real contig datasets, and carry out experiments to analyze the influence of MEC on scaffolding results, which shows that MEC can reduce misassemblies effectively and result in quantitative improvements in scaffolding quality. MEC is publicly available for download at https://github.com/bioinfomaticsCSU/MEC.

Address of the bookmark: https://github.com/bioinfomaticsCSU/MEC

SvABA: Structural variation and indel detection by local assembly

Jit — Tue, 10 Mar 2020 07:52:15 -0500

SvABA is a method for detecting structural variants in sequencing data using genome-wide local assembly. Under the hood, SvABA uses a custom implementation of SGA (String Graph Assembler) by Jared Simpson, and BWA-MEM by Heng Li. Contigs are assembled for every 25kb window (with some small overlap) for every region in the genome. The default is to use only clipped, discordant, unmapped and indel reads, although this can be customized to any set of reads at the command line using VariantBam rules. These contigs are then immediately aligned to the reference with BWA-MEM and parsed to identify variants. Sequencing reads are then realigned to the contigs with BWA-MEM, and variants are scored by their read support.

Address of the bookmark: https://github.com/walaj/svaba

Software for genome assembly !

LEGE — Sun, 30 Aug 2020 09:51:38 -0500

List of bioinformatics tools/Software Website References for genome assembly:

1 Falcon https://github.com/PacificBiosciences/pb-assembly

2 Canu assembler http://canu.readthedocs.io/en/latest/index.html

3 Miniasm assembler https://github.com/lh3/miniasm

4 PBJelly scaffolding tool https://sourceforge.net/projects/pb-jelly/

5 ARCS scaffolding tool https://github.com/bcgsc/arcs

6 Redundans reduction and scaffolding tool https://github.com/Gabaldonlab/redundans

7 Arrow error correction https://github.com/PacificBiosciences/ GenomicConsensus

8 PILON error correction https://github.com/broadinstitute/pilon/wiki

9 BUSCO single copy gene markers http://busco.ezlab.org/

10 Bandage graph assembly viewer https://rrwick.github.io/Bandage/

11 Gepard dotter http://cube.univie.ac.at/gepard

12 MUMmer aligner and plotter http://mummer.sourceforge.net/

CSA: A high-throughput chromosome-scale assembly pipeline for vertebrate genomes

Jit — Wed, 10 Mar 2021 06:13:49 -0600

The pipeline can use information from scaffolded assemblies (for example from HiC or 10X Genomics), or even from diverged (~65-100 Mya) reference genomes for ordering the contigs and thus support the assembly process. This typically results in improved contig N50 when compared to current state of the art methods.

For smaller vertebrate genomes (~1 Gbp) chromosome scale assemblies can be achieved within 12h on high-end Desktop computers (Intel i7, 12 CPU threads, 128 GB RAM). Larger mammalian genomes (~3Gbp) can be processed within 15-18 h on server equipment (Xeon, 96 CPU threads, 1TB RAM).

Address of the bookmark: https://github.com/HMPNK/CSA2.6

Illumina based assembly pipeline steps !

Surabhi Chaudhary — Fri, 10 Dec 2021 06:22:54 -0600

Illumina

Merge re-sequenced FastQ files (cat)
Read QC (FastQC)
Adapter trimming (fastp)
Removal of host reads (Kraken 2; optional)
Variant calling
1. Read alignment (Bowtie 2)
2. Sort and index alignments (SAMtools)
3. Primer sequence removal (iVar; amplicon data only)
4. Duplicate read marking (picard; optional)
5. Alignment-level QC (picard, SAMtools)
6. Genome-wide and amplicon coverage QC plots (mosdepth)
7. Choice of multiple variant calling and consensus sequence generation routes (iVar variants and consensus; default for amplicon data || BCFTools, BEDTools; default for metagenomics data)
  - Variant annotation (SnpEff, SnpSift)
  - Consensus assessment report (QUAST)
  - Lineage analysis (Pangolin)
  - Clade assignment, mutation calling and sequence quality checks (Nextclade)
  - Individual variant screenshots with annotation tracks (ASCIIGenome)
8. Intersect variants across callers (BCFTools)
De novo assembly
1. Primer trimming (Cutadapt; amplicon data only)
2. Choice of multiple assembly tools (SPAdes || Unicycler || minia)
  - Blast to reference genome (blastn)
  - Contiguate assembly (ABACAS)
  - Assembly report (PlasmidID)
  - Assembly assessment report (QUAST)
Present QC and visualisation for raw read, alignment, assembly and variant calling results (MultiQC)

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

Abhi — Tue, 05 Sep 2023 07:31:35 -0500

MitoHiFi v3.2 is a python pipeline distributed under MIT License !

MitoHiFi was first developed to assemble the mitogenomes for a wide range of species in the Darwin Tree of Life Project (DToL)

https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-023-05385-y

Address of the bookmark: https://github.com/marcelauliano/MitoHiFi

TRITEX, a computational pipeline for chromosome-scale assembly of plant genomes

LEGE — Fri, 14 Feb 2025 10:53:48 -0600

This is the documentation of TRITEX, a computational pipeline for chromosome-scale assembly of plant genomes. It was developed in the research group Domestication Genomics at the Leibniz Institute of Plant Genetics and Crop Research (IPK) Gatersleben.

Address of the bookmark: https://tritexassembly.bitbucket.io/