BOL: Related items

JBrowse: Embeddable genome browser built completely with JavaScript and HTML5

Jit — Fri, 29 Jun 2018 09:19:56 -0500

JBrowse is a fast, embeddable genome browser built completely with JavaScript and HTML5, with optional run-once data formatting tools written in Perl. Headline Features: Fast, smooth scrolling and zooming. Explore your genome with unparalleled speed. Scales easily to multi-gigabase genomes and deep-coverage sequencing. Quickly open and view data files on your computer without uploading them to any server. Supports GFF3, BED, FASTA, Wiggle, BigWig, BAM, VCF (with either .tbi or .idx index), REST, and more. BAM, BigBed, BigWig, and VCF data are displayed directly from chunks of the compressed binary files, no conversion needed. Includes an optional “faceted” track selector (see demo) suitable for large installations with thousands of tracks. Very light server resource requirements. In fact, JBrowse has no back-end server code, just tools for formatting data files to be read directly over HTTP. Serve huge datasets from a single low-cost cloud instance. Can run as a stand-alone app on OSX and Windows using the Electron platform Highly extensible plugin architecture, with a large plugin registry of existing examples here https://gmod.github.io/jbrowse-registry https://jbrowse.org/

Address of the bookmark: https://github.com/GMOD/jbrowse

PANDASEQ is a program to align Illumina reads, optionally with PCR primers embedded in the sequence, and reconstruct an overlapping sequence.

BioStar — Fri, 21 Sep 2018 10:19:52 -0500

Development packages for zlib and libbz2 are needed, as well as a standard compiler environment. On Ubuntu, this can be installed via:

sudo apt-get install build-essential libtool automake zlib1g-dev libbz2-dev pkg-config

On MacOS, the Apple Developer tools and Fink (or MacPorts or Brew) must be installed, then:

sudo fink install bzip2-dev pkgconfig

Address of the bookmark: https://github.com/neufeld/pandaseq

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

SLR-superscaffolder: A scaffold assemble pipeline for stLFR reads.

Jit — Fri, 14 Feb 2020 14:23:30 -0600

This is a scaffold assembler designed for stLFR reads[1]. It uses the link-reads information from stLFR reads to assemble contigs to scaffolds.

Here is an illustration of this pipeline:

Address of the bookmark: https://github.com/BGI-Qingdao/SLR-superscaffolder

Bioinformatics tools for telomere to telomere assembly !

BioStar — Tue, 17 Aug 2021 13:17:09 -0500

● Merfin – k-mer-based assembly and variant calling evaluation for improved consensus accuracy (Arang Rhie)
● PanGenie – algorithm that leverages a pangenome reference built from haplotype-resolved genome assemblies in conjunction with k-mer count information from raw, short-read sequencing data to genotype a wide spectrum of genetic variation (Tobias Marschall)
● SQANTI3 – an automated pipeline for the classification of long-read transcripts that can assess the quality of data and the preprocessing pipeline (Rocío Amorín de Hegedüs @rocioadh)
● tama (Transcriptome Annotation by Modular Algorithms) – software designed for processing Iso-Seq data and other long-read transcriptome data (Richard Kuo @GenomeRIK)
● pbaa (PacBio Amplicon Analysis) – separates complex mixtures of amplicon targets from genomic samples to cluster and generate high-quality consensus sequences from HiFi reads (Zev Kronenberg @zevkronenberg)
● bellerophon – analyzes MHC typing and other low-complexity gene amplicon data; performs allele calling while detecting polymorphic sites within the sequences and removing potential chimeric sequence variants (Yuanyuan Cheng @Yuanyuan929)
● svpack – tools for filtering, comparing, and annotating structural variant (SV) calls in VCF format (Aaron Wenger)
● JumboDB – tool for de Bruijn graph construction (Anton Bankevich @AntonBankevich)
● uLTRA – tool for splice alignment of long transcriptomic reads to a genome, guided by a database of exon annotations. (Kristoffer Sahlin @krsahlin)
● LeafGo – workflow to rapidly produce high-quality de novo plant genomes (Luca Ermini @ermini_luca)

Reference:

https://www.pacb.com/blog/young-investigators-share-stellar-science-career-advice-and-bioinformatics-tools-at-smrt-leiden-2021/

Stacks

Jitendra Narayan — Wed, 24 Feb 2016 15:52:30 -0600

Stacks is a software pipeline for building loci from short-read sequences, such as those generated on the Illumina platform. Stacks was developed to work with restriction enzyme-based data, such as RAD-seq, for the purpose of building genetic maps and conducting population genomics and phylogeography.

More at http://catchenlab.life.illinois.edu/stacks/

Address of the bookmark: http://catchenlab.life.illinois.edu/stacks/

cutadapt

Radha Agarkar — Fri, 13 May 2016 04:54:50 -0500

Cutadapt finds and removes adapter sequences, primers, poly-A tails and other types of unwanted sequence from your high-throughput sequencing reads.

Cleaning your data in this way is often required: Reads from small-RNA sequencing contain the 3’ sequencing adapter because the read is longer than the molecule that is sequenced. Amplicon reads start with a primer sequence. Poly-A tails are useful for pulling out RNA from your sample, but often you don’t want them to be in your reads.

Cutadapt helps with these trimming tasks by finding the adapter or primer sequences in an error-tolerant way. It can also modify and filter reads in various ways. Adapter sequences can contain IUPAC wildcard characters. Also, paired-end reads and even colorspace data is supported. If you want, you can also just demultiplex your input data, without removing adapter sequences at all.

Cutadapt comes with an extensive suite of automated tests and is available under the terms of the MIT license.

If you use cutadapt, please cite DOI:10.14806/ej.17.1.200 .

Address of the bookmark: https://cutadapt.readthedocs.io/en/stable/installation.html#quickstart

WgSim

Jit — Thu, 23 Jun 2016 07:26:49 -0500

Reads simulator

Wgsim is a small tool for simulating sequence reads from a reference genome. It is able to simulate diploid genomes with SNPs and insertion/deletion (INDEL) polymorphisms, and simulate reads with uniform substitution sequencing errors. It does not generate INDEL sequencing errors, but this can be partly compensated by simulating INDEL polymorphisms.

Wgsim outputs the simulated polymorphisms, and writes the true read coordinates as well as the number of polymorphisms and sequencing errors in read names. One can evaluate the accuracy of a mapper or a SNP caller with wgsim_eval.pl that comes with the package.

Address of the bookmark: https://github.com/lh3/wgsim

BIMA V3: an aligner customized for mate pair library sequencing

Abhimanyu Singh — Wed, 14 Dec 2016 15:20:00 -0600

Summary: Mate pair library sequencing is an effective and economical method for detecting genomic structural variants and chromosomal abnormalities. Unfortunately, the mapping and alignment of mate pair read pairs to a reference genome is a challenging and
time consuming process for most NGS alignment programs. Large insert sizes, introduction of library preparation protocol artifacts (biotin junction reads, paired-end read contamination, chimeras, etc.), and presence of structural variant breakpoints within reads increases mapping and alignment complexity. We describe an algorithm that is up to 20 times faster and 25% more accurate than popular NGS alignment programs when processing mate pair sequencing.
Availability: http://bioinformaticstools.mayo.edu/research/bima/
Contact: vasmatzis.george@mayo.edu

Address of the bookmark: http://bioinformatics.oxfordjournals.org/content/early/2014/02/12/bioinformatics.btu078.full.pdf

Krona

Jit — Wed, 22 Mar 2017 04:47:35 -0500

Krona allows hierarchical data to be explored with zooming, multi-layered pie charts. Krona charts can be created using an Excel template or KronaTools, which includes support for several bioinformatics tools and raw data formats. The interactive charts are self-contained and can be viewed with any modern web browser (see Browser support).

Address of the bookmark: https://github.com/marbl/Krona/wiki