BOL: Related items

BRIG

Jit — Thu, 16 Feb 2017 13:14:25 -0600

BRIG is a free cross-platform (Windows/Mac/Unix) application that can display circular comparisons between a large number of genomes, with a focus on handling genome assembly data. The application is available at:http://sourceforge.net/projects/brig

If you have any questions or comments, post them on one of the trackers on BRIG’s SourceForge page:http://sourceforge.net/tracker/?group_id=328245.

Features:

Images show similarity between a central reference sequence and other sequences as concentric rings.
BRIG will perform all BLAST comparisons and file parsing automatically via a simple GUI.
Contig boundaries and read coverage can be displayed for draft genomes; customized graphs and annotations can be displayed.
Using a user-defined set of genes as input, BRIG can display gene presence, absence, truncation or sequence variation in a set of complete genomes, draft genomes or even raw, unassembled sequence data.
BRIG also accepts SAM-formatted read-mapping files enabling genomic regions present in unassembled sequence data from multiple samples to be compared simultaneously

Address of the bookmark: http://brig.sourceforge.net/

J-Circos

Shruti Paniwala — Fri, 17 Feb 2017 09:06:54 -0600

Circos plot tool (J-Circos) that is an interactive visualization tool that can plot Circos figures, as well as being able to dynamically add data to the figure, and providing information for specific data points using mouse hover display and zoom in/out functions. J-Circos uses the Java computer language to enable it to be used on most operating systems (Windows, MacOS, Linux). Users can input data into J-Circos using flat data formats, as well as from the GUI. J-Circos will enable biologists to better study more complex chromosomal interactions and fusion transcripts that are otherwise difficult to visualize from next-generation sequencing data.

Address of the bookmark: http://www.australianprostatecentre.org/research/software/jcircos

bedtools

Jit — Fri, 24 Feb 2017 04:50:44 -0600

Collectively, the bedtools utilities are a swiss-army knife of tools for a wide-range of genomics analysis tasks. The most widely-used tools enable genome arithmetic: that is, set theory on the genome. For example, bedtools allows one tointersect, merge, count, complement, and shuffle genomic intervals from multiple files in widely-used genomic file formats such as BAM, BED, GFF/GTF, VCF. While each individual tool is designed to do a relatively simple task (e.g., intersect two interval files), quite sophisticated analyses can be conducted by combining multiple bedtools operations on the UNIX command line.

bedtools is developed in the Quinlan laboratory at the University of Utah and benefits from fantastic contributions made by scientists worldwide.

Address of the bookmark: http://bedtools.readthedocs.io/en/latest/index.html

FinisherSC: a repeat-aware and scalable tool for upgrading de novo assembly using long reads

Jit — Mon, 27 Feb 2017 09:49:45 -0600

FinisherSC, a repeat-aware and scalable tool for upgrading de novo assembly using long reads. Experiments with real data suggest that FinisherSC can provide longer and higher quality contigs than existing tools while maintaining high concordance.

Address of the bookmark: http://kakitone.github.io/finishingTool/

MyCC: Accurate binning of metagenomic contigs via automated clustering sequences using information of genomic signatures and marker genes

Jit — Fri, 03 Mar 2017 08:34:23 -0600

MyCC, an automated binning tool that combines genomic signatures, marker genes and optional contig coverages within one or multiple samples, in order to visualize the metagenomes and to identify the reconstructed genomic fragments.

More at http://www.nature.com/articles/srep24175

Address of the bookmark: https://sourceforge.net/projects/sb2nhri/files/MyCC/

Bioinformatician - Purdue Cancer Center

Wed, 03 Feb 2021 22:54:14 -0600

The Center for Cancer Research is an NCI-designated cancer center. The center is a catalyst for collaborative cancer research around Purdue University. In this role, the selected individual will have the opportunity to cooperate with Purdue faculty and students in performing cutting-edge research and analyses, with opportunities for professional development, and the possibility of co-authorship in faculty research publications.
Projects will be challenging, including various model organisms, and we are looking for an individual who is excited about interacting with multi-disciplinary cancer research groups and the development of new tools, techniques, and workflows. Independently perform both routine and project-specific analyses, advise faculty on the design of experiments, writing manuscripts for publication, and writing grant proposals. Interact and collaborate with bioinformatics services (i.e. Statistical Consulting Center to provide relevant services to the campus research community), where applicable. Support all of the bioinformatics activities of the Center for Cancer Research at Purdue University
Required:

Master's degree in bioinformatics, computer science, molecular biology, or related field
One year of experience in analyzing RNA-Seq data
In lieu of a degree, consideration will be given to an equivalent combination of related education and required work experience.
Understanding of molecular biology, biochemistry, and genetics
Proficiency in writing scripts using Perl, Python, Java, or equivalent languages
Proficiency in R and UNIX/LINUX
Knowledge of genomics, alignment, annotation, bioinformatics, concepts of sequence assembly
Highly motivated and detail-oriented
Ability, interest, and curiosity to learn new skills
Must possess strong communication skills to work effectively with users across disciplines
Ability to work independently and as part of a multi-disciplinary team
Strong visual, verbal, and written communication skills
Excellent time organizational skills
Preferred:

Experience writing software or building software pipelines
Experience with oncology-specific public databases including TCGA
Experience with deploying and/or running software on high-performance computational systems
Statistical and experimental design knowledge
Additional Information:

This position is contingent on the availability of funding
Purdue will not sponsor employment authorization for this position
A background check will be required for employment in this position
FLSA: Exempt (Not Eligible For Overtime)
Retirement Eligibility: Defined Contribution Waiting Period
Purdue University is an EOE/AA employer. All individuals, including minorities, women, individuals with disabilities, and veterans are encouraged to apply

More at https://careers.purdue.edu/job/West-Lafayette-Bioinformatician-Purdue-Cancer-Center-IN-47906/686617600/

Prokka: tool for the rapid annotation of prokaryotic genomes

Jit — Mon, 06 Mar 2017 03:49:57 -0600

Prokka is a software tool for the rapid annotation of prokaryotic genomes. A typical 4 Mbp genome can be fully annotated in less than 10 minutes on a quad-core computer, and scales well to 32 core SMP systems. It produces GFF3, GBK and SQN files that are ready for editing in Sequin and ultimately submitted to Genbank/DDJB/ENA.

Address of the bookmark: http://www.vicbioinformatics.com/software.prokka.shtml

A computational postdoc position and a bioinformatician position

Thu, 18 Jan 2018 16:29:42 -0600

A computational postdoc position and a bioinformatician position are available in Alessandro Romanel's Lab recently established at the Centre for Integrative Biology (CIBIO) in Trento, Italy. The positions are in the context of an AIRC grant and are immediately available.

Successful candidates will be involved in the design and implementation of strategies to study the role of inherited polymorphisms in combination with timedependent variables and somatic events on cancer genesis, progression and resistance.
The ideal postdoc candidate will have a PhD in Computer Science, Bioinformatics, Computational Biology or equivalent, experience in the analysis of next generation sequencing and high-density array data from human cells, strong analytical and quantitative background and programming skills. Background in cancer genomics is recommended.
The ideal bioinformatician candidate will have a four or five years degree in Computer Science, Bioinformatics or equivalent, experience in the management of large datasets, implementation of processing pipelines and strong programming skills. Background in biology/genomics is a plus.
Highly motivated individuals are invited to send a detailed CV, a cover letter describing research interests and experience, and contact information for two references to Alessandro Romanel (alessandro.romanel@unitn.it).

COCACOLA (binning metagenomic contigs using sequence COmposition, read CoverAge, CO-alignment, and paired-end read LinkAge)

Jit — Tue, 07 Mar 2017 08:50:57 -0600

COCACOLA is a general framework that combines different types of information: sequence COmposition, CoverAge across multiple samples, CO-alignment to reference genomes and paired-end reads LinkAge to automatically bin contigs into OTUs. Furthermore, COCACOLA seamlessly embraces customized prior knowledge to facilitate binning accuracy.

News: Python version of COCACOLA is available now!

Address of the bookmark: https://github.com/younglululu/COCACOLA

Genomic Impact

Jitendra Narayan — Wed, 10 Jul 2013 01:33:50 -0500

The ongoing genomic research in USA contributed $31 billion to the U.S. gross national product and helped support 152,000 jobs.

Reference: http://www.unitedformedicalresearch.com/wp-content/uploads/2013/06/The-Impact-of-Genomics-on-the-US-Economy.pdf