BOL: Related items

COPE: an accurate k-mer-based pair-end reads connection tool to facilitate genome assembly

Jit — Wed, 06 Dec 2017 02:08:14 -0600

An efficient tool called Connecting Overlapped Pair-End (COPE) reads, to connect overlapping pair-end reads using k-mer frequencies. We evaluated our tool on 30× simulated pair-end reads from Arabidopsis thaliana with 1% base error. COPE connected over 99% of reads with 98.8% accuracy, which is, respectively, 10 and 2% higher than the recently published tool FLASH. When COPE is applied to real reads for genome assembly, the resulting contigs are found to have fewer errors and give a 14-fold improvement in the N50 measurement when compared with the contigs produced using unconnected reads.

Address of the bookmark: ftp://ftp.genomics.org.cn/pub/cope

ALPACA: A hybrid strategy for assembly of genomic DNA shotgun sequencing reads.

Seema Singh — Mon, 30 Apr 2018 04:38:40 -0500

ALPACA requires Celera Assembler 8.3 or later. It is recommended to build Celera Assembler from source. (Why? The pre-built binaries CA_8.3rc1 and CA8.3rc2 will work for any large data set.

Detail paper at https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-017-3927-8

Address of the bookmark: https://github.com/VicugnaPacos/ALPACA

NxRepair: error correction in de novo assemblies using Nextera Mate Pair Reads

BioStar — Thu, 24 Jan 2019 10:35:12 -0600

NxRepair is a python module that automatically detects large structural errors in de novo assemblies using Nextera mate pair reads. The decector will break a contig at the site of an identified misassembly and will generate a new fasta file containing both the corrected contigs and the correct, unaffected contigs.

https://nxrepair.readthedocs.io/en/latest/tutorial.html

nxrepair aligned_matepairs.bam assemblyfasta.fasta error_locations.csv new_fasta.fasta

Address of the bookmark: https://github.com/rebeccaroisin/nxrepair

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

HiCanu: accurate assembly of segmental duplications, satellites, and allelic variants from high-fidelity long reads

BioStar — Fri, 27 Mar 2020 22:49:31 -0500

HiCanu, a significant modification of the Canu assembler designed to leverage the full potential of HiFi reads via homopolymer compression, overlap-based error correction, and aggressive false overlap filtering.

More at https://www.biorxiv.org/content/10.1101/2020.03.14.992248v3

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

Short-read assembly using Spades !

Abhimanyu Singh — Mon, 31 Jan 2022 07:18:16 -0600

If we only had Illumina reads, we could also assemble these using the tool Spades.

You can try this here, or try it later on your own data.

Get data

We will use the same Illumina data as we used above:

illumina_R1.fastq.gz: the Illumina forward reads
illumina_R2.fastq.gz: the Illumina reverse reads

Assemble

Run Spades:

spades.py -1 illumina_R1.fastq.gz -2 illumina_R2.fastq.gz --careful --cov-cutoff auto -o spades_assembly_all_illumina

-1 is input file of forward reads
-2 is input file of reverse reads
--careful minimizes mismatches and short indels
--cov-cutoff auto computes the coverage threshold (rather than the default setting, “off”)
-o is the output directory

Results

Move into the output directory and look at the contigs:

infoseq contigs.fasta

Understanding PacBio

Jitendra Narayan — Fri, 24 Feb 2017 10:17:36 -0600

This tutorial includes resources for learning more about PacBio data and bioinformatics analysis, and includes content suitable for both beginners and experts. Below are links to training modules (webinars and PowerPoint presentations) to help you get started with your data processing, as well as information for specialized applications.

Training Resources:

Specialized Applications:

Address of the bookmark: https://github.com/PacificBiosciences/Bioinformatics-Training/wiki

Multi-metagenome assembly

Radha Agarkar — Fri, 03 Mar 2017 10:14:18 -0600

This project contains scripts and tutorials on how to assemble individual microbial genomes from metagenomes, as described in:

Genome sequences of rare, uncultured bacteria obtained by differential coverage binning of multiple metagenomes

Mads Albertsen, Philip Hugenholtz, Adam Skarshewski, Gene W. Tyson, Kåre L. Nielsen and Per .H. Nielsen

Nature Biotechnology 2013, doi: 10.1038/nbt.2579

Address of the bookmark: https://github.com/MadsAlbertsen/multi-metagenome

Meraculous: De Novo Genome Assembly with Short Paired-End Reads

Jit — Tue, 07 Nov 2017 04:36:10 -0600

We describe a new algorithm, meraculous, for whole genome assembly of deep paired-end short reads, and apply it to the assembly of a dataset of paired 75-bp Illumina reads derived from the 15.4 megabase genome of the haploid yeast Pichia stipitis. More than 95% of the genome is recovered, with no errors; half the assembled sequence is in contigs longer than 101 kilobases and in scaffolds longer than 269 kilobases. Incorporating fosmid ends recovers entire chromosomes. Meraculous relies on an efficient and conservative traversal of the subgraph of the k-mer (deBruijn) graph of oligonucleotides with unique high quality extensions in the dataset, avoiding an explicit error correction step as used in other short-read assemblers. A novel memory-efficient hashing scheme is introduced. The resulting contigs are ordered and oriented using paired reads separated by ∼280 bp or ∼3.2 kbp, and many gaps between contigs can be closed using paired-end placements. Practical issues with the dataset are described, and prospects for assembling larger genomes are discussed.

Address of the bookmark: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3158087/

GAPPadder: A Sensitive Approach for Closing Gaps on Draft Genomes with Short Sequence Reads

Jit — Mon, 14 May 2018 05:25:48 -0500

This software is provided ``as is” without warranty of any kind. In no event shall the author be held responsible for any damage resulting from the use of this software. The program package, including source codes, executables, and this documentation, is distributed free of charge. If you use this program in a publication, please cite the following reference:
Chong Chu, Xin Li, and Yufeng Wu. "GAPPadder: A Sensitive Approach for Closing Gaps on Draft Genomes with Short Sequence Reads." bioRxiv (2017): 125534.

Address of the bookmark: https://github.com/Reedwarbler/GAPPadder