BOL: Related items

Jaeger : an accurate and fast deep-learning tool to detect bacteriophage sequences

LEGE — Sun, 31 Aug 2025 06:30:16 -0500

Jaeger is a tool that utilizes homology-free machine learning to identify phage genome sequences that are hidden within metagenomes. It is capable of detecting both phages and prophages within metagenomic assemblies.

Address of the bookmark: https://github.com/MGXlab/Jaeger

Omega2: metagenome assembly pipeline

Jit — Mon, 10 Jul 2017 05:56:07 -0500

Omega found overlaps between reads using a prefix/suffix hash table. The overlap graph of reads was simplified by removing transitive edges and trimming short branches. Unitigs were generated based on minimum cost flow analysis of the overlap graph and then merged to contigs and scaffolds using mate-pair information. In comparison with three de Bruijn graph assemblers (SOAPdenovo, IDBA-UD and MetaVelvet), Omega provided comparable overall performance on a HiSeq 100-bp dataset and superior performance on a MiSeq 300-bp dataset. In comparison with Celera on the MiSeq dataset, Omega provided more continuous assemblies overall using a fraction of the computing time of existing overlap-layout-consensus assemblers. This indicates Omega can more efficiently assemble longer Illumina reads, and at deeper coverage, for metagenomic datasets.

Address of the bookmark: http://omega.omicsbio.org/

RGFA: powerful and convenient handling of assembly graphs

Rahul Nayak — Thu, 25 Jan 2018 05:47:53 -0600

RGFA, an implementation of the proposed GFA specification in Ruby. It allows the user to conveniently parse, edit and write GFA files. Complex operations such as the separation of the implicit instances of repeats and the merging of linear paths can be performed. A typical application of RGFA is the editing of a graph, to finish the assembly of a sequence, using information not available to the assembler. We illustrate a use case, in which the assembly of a repetitive metagenomic fosmid insert was completed using a script based on RGFA.

https://github.com/ggonnella/rgfa

Address of the bookmark: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5103826/

ChopStitch: exon annotation and splice graph construction using transcriptome assembly and whole genome sequencing data

Rahul Nayak — Tue, 03 Jul 2018 04:14:52 -0500

ChopStitch is a new method for finding putative exons and constructing splice graphs using an assembled transcriptome and whole genome shotgun sequencing (WGSS) data. ChopStitch identifies exon-exon boundaries in de novo assembled RNA-seq data with the help of a Bloom filter that represents the k-mer spectrum of WGSS reads. The algorithm also detects base substitutions in transcript sequences corresponding to sequencing or assembly errors, haplotype variations, or putative RNA editing events. The primary output of our tool is a FASTA file containing putative exons. Further, exon edges are interrogated for alternative exon-exon boundaries to detect transcript isoforms, which are reported as splice graphs in dot output format.

Address of the bookmark: https://github.com/bcgsc/ChopStitch

HaploMerger2: rebuilding both haploid sub-assemblies from high-heterozygosity diploid genome assembly

BioStar — Thu, 27 Sep 2018 07:08:47 -0500

HM2 can process any diploid assemblies, but it is especially suitable for diploid assemblies with high heterozygosity (≥3%), which can be difficult for other tools. This pipeline also implements flexible and sensitive assembly error detection, a hierarchical scaffolding procedure and a reliable gap-closing method for haploid sub-assemblies.

Source code, executables and the testing dataset are freely available at https://github.com/mapleforest/HaploMerger2/releases/.

Address of the bookmark: https://github.com/mapleforest/HaploMerger2/releases/

Referee: Genome assembly quality scores

Jit — Sun, 04 Nov 2018 16:44:30 -0600

Modern genome sequencing technologies provide a succint measure of quality at each position in every read, however all of this information is lost in the assembly process. Referee summarizes the quality information from the reads that map to a site in an assembled genome to calculate a quality score for each position in the genome assembly.

We accomplish this by first calculating genotype likelihoods for every site. For a given site in a diploid genome, there are 10 possible genotypes (AA, AC, AG, AT, CC, CG, CT, GG, GT, TT). Referee takes as input the genotype likelihoods calculated for all 10 genotypes given the called reference base at each position.

Referee is a program to calculate a quality score for every position in a genome assembly. This allows for easy filtering of low quality sites for any downstream analysis.

https://github.com/gwct/referee

Address of the bookmark: https://gwct.github.io/referee/#

ALLHiC: Phasing and scaffolding polyploid genomes based on Hi-C data

BioStar — Thu, 20 Dec 2018 12:03:32 -0600

The major problem of scaffolding polyploid genome is that Hi-C signals are frequently detected between allelic haplotypes and any existing stat of art Hi-C scaffolding program links the allelic haplotypes together. To solve the problem, we developed a new Hi-C scaffolding pipeline, called ALLHIC, specifically tailored to the polyploid genomes. ALLHIC pipeline contains a total of 5 steps: prune, partition, rescue, optimize and build.

Address of the bookmark: https://github.com/tangerzhang/ALLHiC/wiki

SvABA: Genome-wide detection of structural variants and indels by local assembly

Abhimanyu Singh — Mon, 21 Jan 2019 17:58:56 -0600

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

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

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