BOL: Related items

E-MEM: Efficient computation of Maximal Exact Matches

Jit — Thu, 15 Dec 2016 09:30:43 -0600

E-MEM is a C++/OpenMP program designed to efficiently compute MEMs between large genomes. See the README file for instructions on how to use E-MEM.

E-MEM source code

The source code can be downloaded here.

If you use E-MEM, please cite:

N. Khiste, L. Ilie, E-MEM: Efficient computation of Maximal Exact Matches for very large genomes, Bioinformatics 31(4) (2015) 509 -- 514.

For any questions, please contact Lucian Ilie: ilie@uwo.ca

Address of the bookmark: http://www.csd.uwo.ca/~ilie/E-MEM/

Progressive Cactus

Jit — Tue, 17 Jan 2017 03:40:06 -0600

v0.0 by Glenn Hickey (hickey@soe.ucsc.edu)

Progressive Cactus is a whole-genome alignment package.

Requirements

git
gcc 4.2 or newer
python 2.7
wget
64bit processor and build environment
150GB+ of memory on at least one machine when aligning mammal-sized genomes; less memory is needed for smaller genomes.
Parasol or SGE for cluster support.
750M disk space

Instructions

IMPORTANT NOTE: Progressive Cactus does not presently support installation into paths that contain spaces. Until this is resolved, you can use a softlink as a workaround: ln -s "path with spaces" "installation path without spaces"

In the parent directory of where you want Progressive Cactus installed:

git clone git://github.com/glennhickey/progressiveCactus.git
cd progressiveCactus
git pull
git submodule update --init
make

It is also convenient to add the location of progressiveCactus/bin to your PATH environment variable. In order to run the included tools (ex hal2maf) in the submodules/ directory structure, first source progressiveCactus/environment to load the installed environment.

If any errors occur during the build process, you are unlikely to be able to use the tool. Please submit a GitHub issue so we can help out: not only will you help yourself, but others who wish to use the tool as well.

Note that all dependencies are also built and included in the submodules/ directory. This increases the size and build time but greatly simplifies installation and version management. The installation does not create or modify any files outside the progressiveCactus/ directory.

Address of the bookmark: https://github.com/glennhickey/progressiveCactus

sockeye

Jit — Fri, 17 Feb 2017 08:51:16 -0600

This sockeye software uses the Ensembl database project to import sequence and annotation information from several eukaryotic species. A user can additionally import their own custom sequence and annotation data. Individual annotation objects are displayed in Sockeye by using custom 3D models. Ensembl-derived and imported sequences can be analyzed by using a suite of multiple and pair-wise alignment algorithms. The results of these comparative analyses are also displayed in the 3D environment of Sockeye. By using the Java3D API to visualize genomic data in a 3D environment, we are able to compactly display cross-sequence comparisons. This provides the user with a novel platform for visualizing and comparing genomic feature organization.

Address of the bookmark: http://www.bcgsc.ca/platform/bioinfo/software/sockeye/releases/1.3

Pacbio Long Reads Compatible Software and Tools

Archana Malhotra — Wed, 15 Mar 2017 14:19:01 -0500

The following software packages are known to be compatible with PacBio® data, in addition to PacBio's own SMRT® Analysis suite. All packages are believed to be open source or freely available for non-commercial use. See the individual project sites for up-to-date license information. A separate page lists commercial software.

Know of any other open source software for PacBio data? Email us.

Software categories:

Address of the bookmark: https://github.com/PacificBiosciences/DevNet/wiki/Compatible-Software

SSPACE

Jit — Fri, 05 May 2017 05:42:15 -0500

SSPACE standard is a stand-alone program for scaffolding pre-assembled contigs using NGS paired-read data. It is unique in offering the possibility to manually control the scaffolding process. By using the distance information of paired-end and/or matepair data, SSPACE is able to assess the order, distance and orientation of your contigs and combine them into scaffolds. Currently we offer this as a command-line tool in Perl. The input data is given by pre-assembled contig sequences (FASTA) and NGS paired-read data (Illumina/454/Solid FASTA or FASTQ). The final scaffolds are provided in FASTA format.

Address of the bookmark: https://www.baseclear.com/genomics/bioinformatics/basetools/SSPACE

List of genome announcement, notes and reporting journals

Jit — Wed, 26 Jul 2017 08:01:38 -0500

Faced with an increasing number of articles describing DNA data and a need for more appropriate venues to present these data, some publishers and journals have responded by changing the structure and format of genome papers. Specifically, certain journals have started accepting very short manuscripts (500–1500 words) that present a new chromosome sequence, its GenBank accession number and little else. These pint-sized articles go by various names, such as genome reports, genome announcements, genome notes or genome letters, but will be referred to here broadly as genome reports. Their short length and minimal number (or complete absence) of figures, tables and article subheadings are a significant departure from long-form genome papers, which typically span 8–10 journal pages, contain many supporting items and have formal introduction, methods, results and discussion sections.

Following are the list of journals publishing pint-sized articles go by various names, such as genome reports, genome announcements, genome notes or genome letters, but will be referred to here broadly as genome reports.

1. Genome Announcements, American Society for Microbiology, Genome announcement, Impact factor 1.3, A 500-word report stating that the genome of a particular organism (prokaryote, eukaryote or virus) has been sequenced and providing a citable record of the corresponding GenBank submission. Must include abstract but no text headings can be used except for ‘Acknowledgments’ and ‘References’. Cannot include figures, tables or supplemental material to present data or analysis.

Link: https://mra.asm.org/

2. Genome Biology and Evolution, Oxford University Press, Genome report, Impact factor 4.2, Focused 1500-word papers (up to six tables or figures) that publish the main evolutionary message of new genome sequences as they become submitted to GenBank. May also contain specifically focused comparative analyses of previously published genomes that contain a substantial and novel insight of broadest evolutionary significance.

Link: https://academic.oup.com/gbe

3. Journal of Biotechnology, Elsevier, Genome announcement, Impact factor 2.9, A 500-word report announcing the availability of the completely annotated genome sequence of a biotechnologically relevant organism in the corresponding database (for eukaryotes, advanced draft genomes will also be considered). Articles can contain an Abstract, a brief report on the organism and its biotechnological relevance, a table summarizing the genome features, References and an Acknowledgement. Figures are generally not allowed.

Link: https://www.journals.elsevier.com/journal-of-biotechnology

4. Journal of Genomics, Ivyspring, Genome note, Impact factor N/A, A 1000-word report (10 reference limit; conclusions not permitted) describing novel data sets from high-throughput analysis of genotypes, phenotypes, gene expression, metabolomes, proteomes or genome assemblies.Standard metrics for data quality and the experimental design must be clearly reported.

Link: http://www.jgenomics.com/

5. Memórias do Instituto, Oswaldo Cruz Oswaldo Cruz Foundation, Genome announcement and highlight, Impact factor 1.6, Dedicated to publishing new genome information from eukaryote parasites, virus, bacteria and their respective vectors, as well as re-sequencing or comparative genome analyses. Should occupy no more than three printed pages including figures and/or tables.

Link: http://memorias.ioc.fiocruz.br/

6. Molecular Ecology Resources, Wiley, Genomic resources note, Impact factor 3.7, Short notes on newly assembled and annotated transcriptomes, genome fractions or whole genomes, and/or a library of SNP/SSR markers.Authors submit a short manuscript describing how the resource was developed and where the data can be accessed. Do not appear in journal as individual papers but are instead published as part of a summary article.

Link: https://onlinelibrary.wiley.com/journal/17550998

7. Standards in Genomic Science, BioMed Central (Springer), Short genome report, Impact factor 3.2, Short (∼500-word) article on newly sequenced genome. Article format must follow guidelines and template (available from journal Web site) put forward by the SGS. Any manuscripts not using template or that are missing key figures, tables and/or references (as per the guidelines) will be returned to authors. Rationale of the content model is to provide information that is consistently and uniformly presented for rapid and easy consumption by both human and machine readers.

Link: https://standardsingenomics.biomedcentral.com/

8. 3biotech, Springer, Short genome report, Impact factor 1.3, Short (∼500-word) article on newly sequenced genome. Article format must follow guidelines (available from journal Web site). Genome of a particular organism (prokaryote, eukaryote or virus) has been sequenced and providing a citable record of the corresponding GenBank submission.

Link: https://link.springer.com/journal/13205

SciLifeLab tutorial for bioinformatics analysis !

Jit — Tue, 17 Apr 2018 04:33:00 -0500

SciLifeLab is a national center for molecular biosciences with focus on health and environmental research.

Courses

Old courses (2012-2014)

ASAR: Advanced metagenomic Sequence Analysis in R

Jit — Mon, 09 Jul 2018 05:20:50 -0500

An interactive data analysis tool for selection, aggregation and visualization of metagenomic data is presented. Functional analysis with a SEED hierarchy and pathway diagram based on KEGG orthology based upon MG-RAST annotation results is available.

To read the manual, please click the link https://askarbek-orakov.github.io/ASAR/

Address of the bookmark: https://github.com/Askarbek-orakov/ASAR

pWhatsHap: a parallel, high-performance version of WhatsHap

Jit — Wed, 14 Nov 2018 08:20:27 -0600

Given the potential relevance of efficient haplotyping in several analysis pipelines, we have designed and engineered pWhatsHap, a parallel, high-performance version of WhatsHap. pWhatsHap is embedded in a toolkit developed in Python and supports genomics datasets in standard file formats. Building on WhatsHap, pWhatsHap exhibits the same complexity exploring a number of possible solutions which is exponential in the coverage of the dataset. The parallel implementation on multi-core architectures allows for a relevant reduction of the execution time for haplotyping, while the provided results enjoy the same high accuracy as that provided by WhatsHap, which increases with coverage.

https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1170-y

Address of the bookmark: https://bitbucket.org/whatshap/whatshap

gVolante: Completeness Assessment of Genome/Transcriptome Sequences

Neel — Sun, 13 Jan 2019 07:03:25 -0600

A brand-new web server, gVolante, which provides an online tool for (i) on-demand completeness assessment of sequence sets by means of the previously developed pipelines CEGMA and BUSCO and (ii) browsing pre-computed completeness scores for publicly available data in its database section

Address of the bookmark: https://gvolante.riken.jp/analysis.html

BOL: Related items

E-MEM: Efficient computation of Maximal Exact Matches

Progressive Cactus

v0.0 by Glenn Hickey (hickey@soe.ucsc.edu)

Requirements

Instructions

sockeye

Pacbio Long Reads Compatible Software and Tools

SSPACE

List of genome announcement, notes and reporting journals

SciLifeLab tutorial for bioinformatics analysis !

Courses

Metagenomics Workshop

Introduction to Bioinformatics Using NGS Data

Introduction to Genome Annotation

De Novo Genome Assembly

RNA-seq course

R Programming Foundations for Life Scientists

Single cell RNA sequencing analysis

ASAR: Advanced metagenomic Sequence Analysis in R

pWhatsHap: a parallel, high-performance version of WhatsHap

gVolante: Completeness Assessment of Genome/Transcriptome Sequences