BOL: Related items

GraphMap - A highly sensitive and accurate mapper for long, error-prone reads

Jit — Wed, 07 Jun 2017 04:18:16 -0500

GraphMap - A highly sensitive and accurate mapper for long, error-prone reads http://www.nature.com/ncomms/2016/160415/ncomms11307/full/ncomms11307.html

Features

    Mapping position agnostic to alignment parameters.
    Consistently very high sensitivity and precision across different error profiles, rates and sequencing technologies even with default parameters.
    Circular genome handling to resolve coverage drops near ends of the genome.
    E-value.
    Meaningful mapping quality.
    Various alignment strategies (semiglobal bit-vector and Gotoh, anchored).
    Overlapping of reads for de novo assembly.
    Transcriptome mapping through internal construction of a transcriptome from a given genomic reference and a GTF file.
    ...and much more.

GraphMap is also used as an overlapper in a new de novo genome assembly project called Ra (https://github.com/mariokostelac/ra-integrate).
Ra attempts to create de novo assemblies from raw nanopore and PacBio reads without requiring error correction, for which a highly sensitive overlapper is required.

Currently, development of a new spliced-alignment mode for mapping RNA-seq reads is under way.
Description of the current effort as well as how to reach the experimental implementation can be found here: doc/rnaseq.md.

Address of the bookmark: https://github.com/isovic/graphmap

LRCstats: a tool for evaluating long reads correction methods

Aaryan Lokwani — Wed, 22 Aug 2018 11:05:04 -0500

LRCstats is an open-source pipeline for benchmarking DNA long read correction algorithms for long reads outputted by third generation sequencing technology such as machines produced by Pacific Biosciences. The reads produced by third generation sequencing technology, as the name suggests, are longer in length than reads produced by next generation sequencing technologies, such as those produced by Illumina. However, long reads are plagued by high error rates, which can cause issues in downstream analysis. Long read correction algorithms reduce the error rate of long reads either through self-correcting methods or using accurate, short reads outputted by next generation sequencing technologies to correct long reads.

Address of the bookmark: https://github.com/cchauve/lrcstats

Evaluation of genome assembly software based on long reads

BioStar — Fri, 01 Feb 2019 11:55:54 -0600

TGS technologies have been used to produce highly accurate de novo assemblies of hundreds of microbial genomes and highly contiguous reconstructions of many dozens of plant and animal genomes, enabling new insights into evolution and sequence diversity. They have also been applied to resequencing analyses, to create detailed maps of structural variations in many species. Also, these new technologies have been used to fill in many of the gaps in the human reference genome.

In this report, we compare and evaluate several genome assembly software based on TSG technology. The experimentation has been performed on 4 reference genomes and the results evaluated with the QUAST software. The 11 software that have been evaluated are: Celera Assembler , Falcon , Miniasm, Newbler , SGA Assembler, Smartdenovo, Abruijn, Ra, DBG2OLC, Spades and Cerulean. The first 8 software use only long reads, while the 3 last software can merge long and short reads

HASLR: a tool for rapid genome assembly of long sequencing reads

LEGE — Fri, 31 Jan 2020 05:50:15 -0600

HASLR is a tool for rapid genome assembly of long sequencing reads. HASLR is a hybrid tool which means it requires long reads generated by Third Generation Sequencing technologies (such as PacBio or Oxford Nanopore) together with Next Generation Sequencing reads (such as Illumina) from the same sample.

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

LncPipe:A Nextflow-based pipeline for comprehensive analyses of long non-coding RNAs from RNA-seq datasets

LEGE — Fri, 17 Sep 2021 01:57:02 -0500

The pipeline was developed based on a popular workflow framework Nextflow, composed of four core procedures including reads alignment, assembly, identification and quantification. It contains various unique features such as well-designed lncRNAs annotation strategy, optimized calculating efficiency, diversified classification and interactive analysis report. LncPipe allows users additional control in interuppting the pipeline, resetting parameters from command line, modifying main script directly and resume analysis from previous checkpoint.

Ref https://www.lncrnablog.com/lncpipe-a-nextflow-based-pipeline-for-identification-and-analysis-of-long-non-coding-rnas-from-rna-seq-data/

Address of the bookmark: https://github.com/likelet/LncPipe

Jabba: Hybrid Error Correction for Long Sequencing Reads

Jit — Fri, 05 Jan 2018 03:58:14 -0600

Jabba is a hybrid error correction tool to correct third generation (PacBio / ONT) sequencing data, using second generation (Illumina) data.

Input

Jabba takes as input a concatenated de Bruijn graph and a set of sequences:

the de Bruijn graph should appear in fasta format with 1 entry per node, the meta information should be in the format:
>NODE
the set of sequences should be in fasta or fastq format. These sequences will be corrected (e.g. PacBio reads). The corrections will be written to a file Jabba fasta.
The output is a file in fasta format with corrections of the long reads, and additionally a file in the input format containing uncorrected reads.

https://github.com/biointec/jabba/wiki

https://almob.biomedcentral.com/articles/10.1186/s13015-016-0075-7

Address of the bookmark: https://github.com/biointec/jabba

Porechop: tool for finding and removing adapters from Oxford Nanopore reads

Rahul Nayak — Tue, 29 May 2018 07:33:44 -0500

Porechop is a tool for finding and removing adapters from Oxford Nanopore reads. Adapters on the ends of reads are trimmed off, and when a read has an adapter in its middle, it is treated as chimeric and chopped into separate reads. Porechop performs thorough alignments to effectively find adapters, even at low sequence identity.

Porechop also supports demultiplexing of Nanopore reads that were barcoded with the Native Barcoding Kit, PCR Barcoding Kit or Rapid Barcoding Kit.

Address of the bookmark: https://github.com/rrwick/Porechop

npScarf: Scaffolding and Completing Assemblies in Real-time Fashion

Jit — Tue, 23 May 2017 04:53:29 -0500

npScarf (jsa.np.npscarf) is a program that scaffolds and completes draft genomes assemblies in real-time with Oxford Nanopore sequencing. The pipeline can run on a computing cluster as well as on a laptop computer for microbial datasets. It also facilitates the real-time analysis of positional information such as gene ordering and the detection of genes from mobile elements (plasmids and genomic islands).

Complete paper at https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5321748/

Address of the bookmark: https://github.com/mdcao/npScarf

The MARVEL assembler

Jit — Fri, 04 May 2018 19:18:41 -0500

MARVEL consists of a set of tools that facilitate the overlapping, patching, correction and assembly of noisy (not so noisy ones as well) long reads.

The assembly process can be summarized as follows:

overlap
patch reads
overlap (again)
scrubbing
assembly graph construction and touring
optional read correction
fasta file creation

Address of the bookmark: https://github.com/schloi/MARVEL

SViper: Swipe your Structural Variants called on long (ONT/PacBio) reads with short exact (Illumina) reads.

Neel — Sun, 22 Dec 2019 03:48:28 -0600

Call sviper

~$ ./sviper -s short-reads.bam -l long-reads.bam -r ref.fa -c variants.vcf -o polished_variants

This will output a polished_variants.vcf file, that contains all the refined variants.

Sometimes it is helpful to look at the polished sequence, e.g. with the IGV browser. In that case you want SViper to output the polished and aligned sequences in a bam file via the option --output-polished-bam:

~$ ./sviper -s short-reads.bam -l long-reads.bam -r ref.fa -c variants.vcf -o polished_variants --output-polished-bam

Address of the bookmark: https://github.com/smehringer/SViper