BOL: Related items

CLAW: Chloroplast Long-read Assembly Workflow

LEGE — Wed, 21 Feb 2024 12:37:46 -0600

CLAW (Chloroplast Long-read Assembly Workflow) is an mostly-automated Snakemake-based workflow for the assembly of chloroplast genomes. CLAW uses chloroplast long-reads, which are baited out of larger read libraries (e.g., an Oxford Nanopore Technologies MinION read library derived from photosynthetic tissue), for assembly with Flye and/or Unicycler. CLAW was designed with the novice bioinformatician in mind - it is easy to install and easy to use, requiring only minimal user input.

Address of the bookmark: https://github.com/aaronphillips7493/CLAW

GToTree: a user-friendly workflow for phylogenomics

Neel — Wed, 23 Feb 2022 08:18:58 -0600

GToTree is a user-friendly workflow for phylogenomics intended to give more researchers the capability to create phylogenomic trees. The open-access Bioinformatics Journal publication is available here, and documentation and examples can be found at the wiki here.

Address of the bookmark: https://github.com/AstrobioMike/GToTree

Katuali is a flexible consensus pipeline implemented in Snakemake to basecall, assemble, and polish Oxford Nanopore Technologies' sequencing data

Jit — Tue, 22 Jan 2019 06:26:55 -0600

Run a pipeline processing fast5s to a consensus in a single command.
Recommended fixed "standard" and "fast" pipelines.
Interchange basecaller, assembler, and consensus components of the pipelines simply by changing the target filepath.
Seemless distribution of tasks over local or distributed compute.
Highly configurable.
Open source (Mozilla Public License 2.0).

Documentation can be found at https://nanoporetech.github.io/katuali/.

Address of the bookmark: https://github.com/nanoporetech/katuali

Executing Snakemake

Abhi — Sun, 25 Sep 2022 18:34:30 -0500

This part of the documentation describes the snakemake executable. Snakemake is primarily a command-line tool, so the snakemake executable is the primary way to execute, debug, and visualize workflows.

https://github.com/snakemake/snakemake/blob/main/docs/tutorial/basics.rst

Address of the bookmark: https://snakemake.readthedocs.io/en/v4.5.1/executable.html

Bioinformatics approach to Boar Taint

Rahul Agarwal — Wed, 17 Jul 2013 15:50:37 -0500

Meat products obtained from intact male pigs often produce offensive smell or odour which is recognized as a complex genetic trait called boar taint.Androstenone and Skatole in the fat primarily cause boar taint. Metabolism of androstenone and sex steroids share a common pathway which makes removal of boar taint a very challenging task. Castration is a traditional solution to remove boar taint but it also results in bad quality of meat due to low level of steroids which is objectionable to many consumers. Detected functional variant(s) underlying boar taint compounds can be used as genetic markers in selection of male pigs with reduced boar taint levels. Resequencing of a total of 47 samples belong to Norwegian Landrace (NL) and Duroc (D) pigs with varied boar taint levels were done in Illumina HiSeq2000 to >10X average coverage. Short reads generated from these samples mapped to Sus Scrofa version 10.2 reference assembly using Bowtie2. Alignment file then used for calling SNPs and InDels inside previousy identified QTL regions on SSC5,13, and 7 with the aid of FreeBayes , a variant caller tool. A final list of SNPs was prepared after filtering SNPs on the basis of SNP quality, coverage of SNP allele, functional and structural annotation, and repeats, etc. Selected SNPs will be genotyped in sample population for validation and then used for constructing SNPs haplotypes in close linkage disequilibrium with QTLs and fine mapping of QTLs through association mapping of genotyped SNPs.

Latest paper on comparison of mapping tools

Rahul Agarwal — Tue, 03 Sep 2013 18:00:38 -0500

A. Hatem, D. Bozdag, A. E. Toland, U. V. Catalyurek "Benchmarking short sequence mapping tools" BMC Bioinformatics, 14(1):184, 2013.

http://bmi.osu.edu/hpc/software/benchmark/

http://bmi.osu.edu/hpc/software/pmap/pmap.html

Other similiar papers:

http://online.liebertpub.com/doi/pdf/10.1089/cmb.2012.0022

http://bioinformatics.oxfordjournals.org/content/28/24/3169

Some new Mapping tool links:

GSNAP

http://research-pub.gene.com/gmap/

RMAP

http://rulai.cshl.edu/rmap/

mrsFAST

http://mrsfast.sourceforge.net/Home

http://sourceforge.net/projects/mrsfast/files/mrsfast-ultra-3.1.0/

BFAST

http://sourceforge.net/apps/mediawiki/bfast/index.php?title=Main_Page

SHRiMP (for AB SOLiD color-space reads)

http://compbio.cs.toronto.edu/shrimp/

RazerA 3

http://www.seqan.de/projects/razers/

Address of the bookmark: http://www.biomedcentral.com/1471-2105/14/184

Summer 2016

Sun, 21 Feb 2016 06:17:55 -0600

REU at Fordham University- Summer 2016

An NSF-funded REU to study Y-chromosome diversity and sex-biased dispersal in wild brown rats (Rattus norvegicus) is available in the Munshi-South Lab at Fordham University. Our lab is currently investigating rat evolution at scales ranging from landscape genetics of individual cities to global patterns of diversity. Development of resources for investigating Y-chromosome diversity will support many of these studies. The REU student will work with the lab to bioinformatically identify Y-chromosome SNPs, design SNPtype assays,
extract DNA, genotype samples, and analyze data.

We seek applicants interested in bioinformatics, evolutionary biology, and related disciplines. Applicants must have taken a college-level genetics course. This REU will require attention to detail, reliability, independence, and critical thinking.

This position is based at Fordham University's field station, the Louis Calder Center, in Armonk, NY. The Calder Center is located approximately 25 miles north of New York City in a protected woodland area. Housing
will be provided at the Calder Center for the duration of the REU (May 23 to Aug 12, 2016). Additionally, the student will receive a $6,000 stipend. The selected student will participate in professional development activities through the Calder Centers REU program, including presentation of results at a research colloquium at the end of the summer.

To apply, please send a one page personal statement about your scientific interests and how this REU will support your professional goals, unofficial transcripts including a list of Spring 2016 courses, and names of two professional references (including title, address, phone number, and email address) as a single pdf (with your last name in the file name) to Dr. Jason Munshi-South (jmunshisouth@fordham.edu).

Applications are due March 4th, 2016.

Jason Munshi-South

Snippy: Rapid haploid variant calling and core SNP phylogeny

Neel — Sat, 11 Aug 2018 11:06:56 -0500

Snippy finds SNPs between a haploid reference genome and your NGS sequence reads. It will find both substitutions (snps) and insertions/deletions (indels). It will use as many CPUs as you can give it on a single computer (tested to 64 cores). It is designed with speed in mind, and produces a consistent set of output files in a single folder. It can then take a set of Snippy results using the same reference and generate a core SNP alignment (and ultimately a phylogenomic tree).

snippy --cpus 16 --outdir mysnps --ref Listeria.gbk --R1 FDA_R1.fastq.gz --R2 FDA_R2.fastq.gz

Address of the bookmark: https://github.com/tseemann/snippy

QuasiModo - Quasispecies Metric Determination on Omics

Neel — Sat, 26 Jun 2021 15:22:56 -0500

This repository contains the scripts and pipeline that reproduces the results of the HCMV benchmarking study. In this study we evaluated genome assemblers and variant callers on 10 in vitro generated, mixed strain HCMV sequence samples, each consisting of two lab strains in different abundance ratios. This tool can also be used to evaluate assemblies and variant calling results on other similar datasets.

https://academic.oup.com/bib/article/22/3/bbaa123/5868070

Address of the bookmark: https://github.com/hzi-bifo/Quasimodo

Kevler: Reference-free variant discovery in large eukaryotic genomes

Jit — Tue, 28 Jan 2020 03:21:53 -0600

Welcome to kevlar, software for predicting de novo genetic variants without mapping reads to a reference genome! kevlar's k-mer abundance based method calls single nucleotide variants (SNVs), multinucleotide variants (MNVs), insertion/deletion variants (indels), and structural variants (SVs) simultaneously with a single simple model.

More at https://kevlar.readthedocs.io/en/latest/

https://www.cell.com/iscience/pdf/S2589-0042(19)30259-7.pdf

Address of the bookmark: https://github.com/kevlar-dev/kevlar