BOL: Related items

JCVI:Python utility libraries on genome assembly, annotation and comparative genomics

Jit — Tue, 17 Mar 2020 06:19:06 -0500

Collection of Python libraries to parse bioinformatics files, or perform computation related to assembly, annotation, and comparative genomics.

https://github.com/tanghaibao/jcvi

More at https://github.com/tanghaibao/jcvi/wiki

Address of the bookmark: https://github.com/tanghaibao/jcvi

HASLR: a hybrid assembler which uses both second and third generation sequencing reads

BioStar — Mon, 04 May 2020 02:04:03 -0500

HASLR, a hybrid assembler which uses both second and third generation sequencing reads to efficiently generate accurate genome assemblies. Our experiments show that HASLR is not only the fastest assembler but also the one with the lowest number of misassemblies on all the samples compared to other tested assemblers. Furthermore, the generated assemblies in terms of contiguity and accuracy are on par with the other tools on most of the samples. Availability. HASLR is an open source tool available at https://github.com/vpc-ccg/haslr.

Address of the bookmark: https://github.com/vpc-ccg/haslr

HapSolo: An optimization approach for removing secondary haplotigs during diploid genome assembly and scaffolding.

Jit — Mon, 26 Oct 2020 21:23:36 -0500

Despite marked recent improvements in long-read sequencing technology, the assembly of diploid genomes remains a difficult task. A major obstacle is distinguishing between alternative contigs that represent highly heterozygous regions. If primary and secondary contigs are not properly identified, the primary assembly will overrepresent both the size and complexity of the genome, which complicates downstream analysis such as scaffolding.

More at https://github.com/esolares/HapSolo

Address of the bookmark: https://github.com/esolares/HapSolo

HapSolo: An optimization approach for removing secondary haplotigs during diploid genome assembly and scaffolding

Jit — Sat, 08 May 2021 21:25:00 -0500

HapSolo, that identifies secondary contigs and defines a primary assembly based on multiple pairwise contig alignment metrics. HapSolo evaluates candidate primary assemblies using BUSCO scores and then distinguishes among candidate assemblies using a cost function. The cost function can be defined by the user but by default considers the number of missing, duplicated and single BUSCO genes within the assembly. HapSolo performs hill climbing to minimize cost over thousands of candidate assemblies.

Address of the bookmark: https://github.com/esolares/HapSolo

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

BUSCO

Jitendra Narayan — Sun, 07 Feb 2016 16:02:39 -0600

Assessing genome assembly and annotation completeness with Benchmarking Universal Single-Copy Orthologs

More at http://busco.ezlab.org/

Address of the bookmark: http://busco.ezlab.org/

CISA: Contig Integrator for Sequence Assembly

Neel — Thu, 15 Dec 2016 05:42:21 -0600

A plethora of algorithmic assemblers have been proposed for the de novo assembly of genomes, however, no individual assembler guarantees the optimal assembly for diverse species. Optimizing various parameters in an assembler is often performed in order to generate the most optimal assembly. However, few efforts have been pursued to take advantage of multiple assemblies to yield an assembly of high accuracy. In this study, we employ various state-of-the-art assemblers to generate different sets of contigs for bacterial genomes. A tool, named CISA, has been developed to integrate the assemblies into a hybrid set of contigs, resulting in assemblies of superior contiguity and accuracy, compared with the assemblies generated by the state-of-the-art assemblers and the hybrid assemblies merged by existing tools. This tool is implemented in Python and requires MUMmer and BLAST+ to be installed on the local machine. The source code of CISA and examples of its use are available at http://sb.nhri.org.tw/CISA/.

Address of the bookmark: http://sb.nhri.org.tw/CISA/en/CISA

Oxford Nanopore Sequencing, Hybrid Error Correction, and de novo Assembly of a Eukaryotic Genome

Jit — Wed, 29 Nov 2017 05:08:53 -0600

Monitoring the progress of DNA molecules through a membrane pore has been postulated as a method for sequencing DNA for several decades. Recently, a nanopore-based sequencing instrument, the Oxford Nanopore MinION, has become available that we used for sequencing the S. cerevisiae genome. To make use of these data, we developed a novel open-source hybrid error correction algorithm Nanocorr (https://github.com/jgurtowski/nanocorr) specifically for Oxford Nanopore reads, as existing packages were incapable of assembling the long read lengths (5-50kbp) at such high error rate (between ~5 and 40% error). With this new method we were able to perform a hybrid error correction of the nanopore reads using complementary MiSeq data and produce a de novo assembly that is highly contiguous and accurate: the contig N50 length is more than ten-times greater than an Illumina-only assembly (678kb versus 59.9kbp), and has greater than 99.88% consensus identity when compared to the reference. Furthermore, the assembly with the long nanopore reads presents a much more complete representation of the features of the genome and correctly assembles gene cassettes, rRNAs, transposable elements, and other genomic features that were almost entirely absent in the Illumina-only assembly.

Address of the bookmark: http://schatzlab.cshl.edu/data/nanocorr/

MeDuSa: a multi-draft based scaffolder

Abhimanyu Singh — Wed, 14 Feb 2018 02:49:00 -0600

MeDuSa (Multi-Draft based Scaffolder), an algorithm for genome scaffolding. MeDuSa exploits information obtained from a set of (draft or closed) genomes from related organisms to determine the correct order and orientation of the contigs. MeDuSa formalises the scaffolding problem by means of a combinatorial optimisation formulation on graphs and implements an efficient constant factor approximation algorithm to solve it. In contrast to currently used scaffolders, it does not require either prior knowledge on the microrganisms dataset under analysis (e.g. their phylogenetic relationships) or the availability of paired end read libraries.

Address of the bookmark: https://github.com/combogenomics/medusa