BOL: Related items

MECAT: fast mapping, error correction, and de novo assembly for single-molecule sequencing reads

Rahul Nayak — Fri, 11 May 2018 05:07:45 -0500

MECAT is an ultra-fast Mapping, Error Correction and de novo Assembly Tools for single molecula sequencing (SMRT) reads. MECAT employs novel alignment and error correction algorithms that are much more efficient than the state of art of aligners and error correction tools. MECAT can be used for effectively de novo assemblying large genomes. For example, on a 32-thread computer with 2.0 GHz CPU , MECAT takes 9.5 days to assemble a human genome based on 54x SMRT data, which is 40 times faster than the current PBcR-Mhap pipeline. MECAT performance were compared with PBcR-Mhap pipeline, FALCON and Canu(v1.3) in five real datasets. The quality of assembled contigs produced by MECAT is the same or better than that of the PBcR-Mhap pipeline and FALCON.

https://www.nature.com/articles/nmeth.4432

Address of the bookmark: https://github.com/xiaochuanle/MECAT

minialign: fast and accurate alignment tool for PacBio and Nanopore long reads

Jit — Thu, 24 May 2018 08:33:26 -0500

Minialign is a little bit fast and moderately accurate nucleotide sequence alignment tool designed for PacBio and Nanopore long reads. It is built on three key algorithms, minimizer-based index of the minimap overlapper, array-based seed chaining, and SIMD-parallel Smith-Waterman-Gotoh extension.

Address of the bookmark: https://github.com/ocxtal/minialign

EAGLER: a scaffolding tool for long reads.

Jit — Mon, 04 Jun 2018 05:26:03 -0500

EAGLER is a scaffolding tool for long reads. The scaffolder takes as input a draft genome created by any NGS assembler and a set of long reads. The long reads are used to extend the contigs present in the NGS draft and possibly join overlapping contigs. EAGLER supports both PacBio and Oxford Nanopore reads.

The tool should be compatible with most UNIX flavors and has been successfully tested on the following operating systems:

Mac OS X 10.11.1
Mac OS X 10.10.3
Ubuntu 14.04 LTS

https://bib.irb.hr/datoteka/844447.Diplomski_2015_Luka_terbi.pdf

Address of the bookmark: https://github.com/mculinovic/EAGLER

ReMILO: reference assisted misassembly detection algorithm using short and long reads.

Jit — Fri, 06 Jul 2018 04:27:49 -0500

ReMILO, a reference assisted misassembly detection algorithm that uses both short reads and PacBio SMRT long reads. ReMILO aligns the initial short reads to both the contigs and reference genome, and then constructs a novel data structure called red-black multipositional de Bruijn graph to detect misassemblies. In addition, ReMILO also aligns the contigs to long reads and find their differences from the long reads to detect more misassemblies.

Address of the bookmark: https://github.com/songc001/remilo

Hercules: a profile HMM-based hybrid error correction algorithm for long reads

Jit — Mon, 20 Aug 2018 14:14:11 -0500

Choosing whether to use second or third generation sequencing platforms can lead to trade-offs between accuracy and read length. Several studies require long and accurate reads including de novo assembly, fusion and structural variation detection. In such cases researchers often combine both technologies and the more erroneous long reads are corrected using the short reads. Current approaches rely on various graph based alignment techniques and do not take the error profile of the underlying technology into account. Memory- and time- efficient machine learning algorithms that address these shortcomings have the potential to achieve better and more accurate integration of these two technologies. Results: We designed and developed Hercules, the first machine learning-based long read error correction algorithm. The algorithm models every long read as a profile Hidden Markov Model with respect to the underlying platformtextquoterights error profile. The algorithm learns a posterior transition/emission probability distribution for each long read and uses this to correct errors in these reads. Using datasets from two DNA-seq BAC clones (CH17-157L1 and CH17-227A2), and human brain cerebellum polyA RNA-seq, we show that Hercules-corrected reads have the highest mapping rate among all competing algorithms and highest accuracy when most of the basepairs of a long read are covered with short reads. Availability:

Hercules source code is available at https://github.com/BilkentCompGen/Hercules

Address of the bookmark: https://github.com/BilkentCompGen/Hercules

Rebaler: program for conducting reference-based assemblies using long reads.

Jit — Tue, 18 Sep 2018 07:52:41 -0500

Rebaler is a program for conducting reference-based assemblies using long reads. It relies mainly on minimap2 for alignment and Racon for making consensus sequences.

I made Rebaler for bacterial genomes (specifically for the task of testing basecallers). It should in principle work for non-bacterial genomes as well, but I haven't tested it.

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

Rainbow: an integrated tool for efficient clustering and assembling RAD-seq reads

Rahul Nayak — Fri, 19 Oct 2018 08:23:42 -0500

Rainbow is developed to provide an ultra-fast and memory-efficient solution to clustering and assembling short reads produced by RAD-seq. First, Rainbow clusters reads using a spaced seed method. Then, Rainbow implements a heterozygote calling like strategy to divide potential groups into haplotypes in a top–down manner. And along a guided tree, it iteratively merges sibling leaves in a bottom–up manner if they are similar enough. Here, the similarity is defined by comparing the 2nd reads of a RAD segment. This approach tries to collapse heterozygote while discriminate repetitive sequences. At last, Rainbow uses a greedy algorithm to locally assemble merged reads into contigs. Rainbow not only outputs the optimal but also suboptimal assembly results. Based on simulation and a real guppy RAD-seq data, we show that Rainbow is more competent than the other tools in dealing with RAD-seq data

Address of the bookmark: https://sourceforge.net/projects/bio-rainbow/files/

ARCS: scaffolding genome drafts with linked reads

Jit — Mon, 17 Dec 2018 17:40:28 -0600

ARCS requires two input files:

Draft assembly fasta file
Interleaved linked reads file (Barcode sequence expected in the BX tag of the read header or in the form "@readname_barcode" ; Run Long Ranger basic on raw chromium reads to produce this interleaved file)

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

Flye: Fast and accurate de novo assembler for single molecule sequencing reads

BioJoker — Tue, 02 Apr 2019 21:54:55 -0500

Flye is a de novo assembler for single molecule sequencing reads, such as those produced by PacBio and Oxford Nanopore Technologies. It is designed for a wide range of datasets, from small bacterial projects to large mammalian-scale assemblies. The package represents a complete pipeline: it takes raw PB / ONT reads as input and outputs polished contigs. Flye also includes a special mode for metagenome assembly.

Address of the bookmark: https://github.com/fenderglass/Flye

FastGT: an alignment-free method for calling common SNVs directly from raw sequencing reads

Jit — Tue, 28 Jan 2020 03:27:33 -0600

FastGT is a program package for whole-genome genotyping of genome variants directly from raw sequencing reads. It is written in C and runs in Linux. FastGT uses a list of variant-specific k-mer pairs that are unique in human genome, counts the frequency of k-mers in sequencing data and predicts the genotype. All this takes less than 1 hour on average low-cost Linux server.

http://bioinfo.ut.ee/FastGT/

https://github.com/bioinfo-ut/GenomeTester4/

Address of the bookmark: http://bioinfo.ut.ee/FastGT/