BOL: Related items

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

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/

Merfin: improved variant filtering, assembly evaluation and polishing via k-mer validation

Neel — Sun, 03 Apr 2022 20:35:19 -0500

Merfin, a k-mer based variant-filtering algorithm for improved accuracy in genotyping and genome assembly polishing. Merfin evaluates each variant based on the expected k-mer multiplicity in the reads, independently of the quality of the read alignment and variant caller’s internal score. Merfin increased the precision of genotyped calls in several benchmarks, improved consensus accuracy and reduced frameshift errors when applied to human and nonhuman assemblies built from Pacific Biosciences HiFi and continuous long reads or Oxford Nanopore reads, including the first complete human genome. Moreover, we introduce assembly quality and completeness metrics that account for the expected genomic copy numbers.

More at https://www.nature.com/articles/s41592-022-01445-y

Address of the bookmark: https://github.com/arangrhie/merfin

liftover

Jitendra Narayan — Mon, 08 Feb 2016 15:45:03 -0600

Convenient conversions between genome assemblie. The liftover package makes it easy to remap genomic coordinates to a different genome assembly.

More at https://github.com/aaronwolen/liftover

https://www.bioconductor.org/help/workflows/liftOver/

Address of the bookmark: https://github.com/aaronwolen/liftover

RNA-Seq De novo Assembly Using Trinity

Surabhi Chaudhary — Wed, 23 Mar 2016 05:53:46 -0500

Trinity, developed at the Broad Institute and the Hebrew University of Jerusalem, represents a novel method for the efficient and robust de novo reconstruction of transcriptomes from RNA-seq data. Trinity combines three independent software modules: Inchworm, Chrysalis, and Butterfly, applied sequentially to process large volumes of RNA-seq reads. Trinity partitions the sequence data into many individual de Bruijn graphs, each representing the transcriptional complexity at at a given gene or locus, and then processes each graph independently to extract full-length splicing isoforms and to tease apart transcripts derived from paralogous genes. Briefly, the process works like so:

Inchworm assembles the RNA-seq data into the unique sequences of transcripts, often generating full-length transcripts for a dominant isoform, but then reports just the unique portions of alternatively spliced transcripts.
Chrysalis clusters the Inchworm contigs into clusters and constructs complete de Bruijn graphs for each cluster. Each cluster represents the full transcriptonal complexity for a given gene (or sets of genes that share sequences in common). Chrysalis then partitions the full read set among these disjoint graphs.
Butterfly then processes the individual graphs in parallel, tracing the paths that reads and pairs of reads take within the graph, ultimately reporting full-length transcripts for alternatively spliced isoforms, and teasing apart transcripts that corresponds to paralogous genes.

More at https://github.com/trinityrnaseq/trinityrnaseq/wiki

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Download Trinity here.

Build Trinity by typing 'make' in the base installation directory.

Assemble RNA-Seq data like so:

 Trinity --seqType fq --left reads_1.fq --right reads_2.fq --CPU 6 --max_memory 20G

Find assembled transcripts as: 'trinity_out_dir/Trinity.fasta'

Address of the bookmark: https://github.com/trinityrnaseq/trinityrnaseq/wiki

RACA: Reference-Assisted Chromosome Assembly

Priya Singh — Wed, 06 Apr 2016 09:29:50 -0500

Rreference-Assisted Chromosome Assembly (RACA), an algorithm to reliably order and orient sequence scaffolds generated by NGS and assemblers into longer chromosomal fragments using comparative genome information and paired-end reads.

http://www.ncbi.nlm.nih.gov/pubmed/23307812

http://bioen-compbio.bioen.illinois.edu/RACA/

Address of the bookmark: http://bioen-compbio.bioen.illinois.edu/RACA/

DISCOVAR

Abhimanyu Singh — Mon, 18 Apr 2016 11:59:16 -0500

DISCOVAR is a new variant caller and DISCOVAR de novo a new genome assembler, both designed for state-of-the-art data. Their inputs are chosen to optimize quality while keeping costs low. Currently it takes as input Illumina reads of length 250 or longer — produced on MiSeq or HiSeq 2500 — and from a single PCR-free library. These data enable a level of completeness and continuity that was not previously possible.

DISCOVAR can call variants on a region by region basis, potentially tiling an entire large genome. DISCOVAR variant calling is under active development and transitioning to VCF.

DISCOVAR de novo can generate de novo assemblies for both large and small genomes. It currently does not call variants.

More at https://www.broadinstitute.org/software/discovar/blog/?page_id=14

Address of the bookmark: https://www.broadinstitute.org/software/discovar/blog/

CANU: Assembling Large Genomes with Single-Molecule Sequencing and Locality Sensitive Hashing.

Jit — Tue, 26 Apr 2016 11:38:10 -0500

Canu is a fork of the Celera Assembler designed for high-noise single-molecule sequencing (such as the PacBio RSII or Oxford Nanopore MinION). The software is currently alpha level, feel free to use and report issues encountered.

Canu is a hierachical assembly pipeline which runs in four steps:

Detect overlaps in high-noise sequences using MHAP
Generate corrected sequence consensus
Trim corrected sequences
Assemble trimmed corrected sequences

Read the documentation

New release https://github.com/marbl/canu/releases

Address of the bookmark: https://github.com/marbl/canu

Blobology

Jit — Mon, 13 Jun 2016 10:18:33 -0500

Tools for making blobplots or Taxon-Annotated-GC-Coverage plots (TAGC plots) to visualise the contents of genome assembly data sets as a QC step

Blaxter Lab, Institute of Evolutionary Biology, University of Edinburgh

Goal: To create blobplots or Taxon-Annotated-GC-Coverage plots (TAGC plots) to visualise the contents of genome assembly data sets as a QC step.

This repository accompanies the paper:
Blobology: exploring raw genome data for contaminants, symbionts and parasites using taxon-annotated GC-coverage plots. Sujai Kumar, Martin Jones, Georgios Koutsovoulos, Michael Clarke, Mark Blaxter
(submitted 2013-10-01 to Frontiers in Bioinformatics and Computational Biology special issue : Quality assessment and control of high-throughput sequencing data).

It contains bash/perl/R scripts for running the analysis presented in the paper to create a preliminary assembly, and to create and collate GC content, read coverage and taxon annotation for the preliminary assembly, which can be visualised, such as Figure 2a from the paper showing TAGC plots/blobplots for Caenorhabditis sp. 5:

Address of the bookmark: https://github.com/blaxterlab/blobology

Redundans

Jit — Thu, 01 Sep 2016 08:28:11 -0500

Redundans pipeline assists an assembly of heterozygous genomes.
Program takes as input assembled contigs, paired-end and/or mate pairs sequencing libraries and returns scaffolded homozygous genome assembly, that should be less fragmented and with total size smaller than the input contigs. In addition, Redundans will automatically close the gaps resulting from genome assembly or scaffolding more details.

The pipeline consists of three steps/modules:

redundancy reduction: detection and selectively removal of redundant contigs from an initial de novo assembly
scaffolding: joining of genome fragments using paired-end and/or mate-pairs reads
gap closing

Redundans is:

fast & lightweight, multi-core support and memory-optimised, so it can be run even on the laptop for small-to-medium size genomes
flexible toward many sequencing technologies (Illumina, 454 or Sanger) and library types (paired-end, mate pairs, fosmids)
modular: every step can be ommited or replaced by another tools

Address of the bookmark: https://github.com/Gabaldonlab/redundans