BOL: Related items

Getting Started with Nextflow

LEGE — Sat, 18 Sep 2021 01:28:41 -0500

Introduction to Bioinformatics workflows with Nextflow and nf-core

Getting Started with Nextflow

Objectives Understand

What a workflow management system is.

Understand the benefits of using a workflow management system.

Explain the benefits of using Nextflow as part of your bioinformatics workflow.

Explain the components of a Nextflow script.

Run a Nextflow script.

Introduction to Bioinformatics workflows with Nextflow and nf-core

Getting Started with Nextflow

Address of the bookmark: https://carpentries-incubator.github.io/workflows-nextflow/aio/index.html

Flye: Fast and accurate de novo assembler for single molecule sequencing reads

Jit — Fri, 04 May 2018 19:16:22 -0500

Flye is a de novo assembler for long and noisy reads, such as those produced by PacBio and Oxford Nanopore Technologies. The algorithm uses an A-Bruijn graph to find the overlaps between reads and does not require them to be error-corrected. After the initial assembly, Flye performs an extra repeat classification and analysis step to improve the structural accuracy of the resulting sequence. The package also includes a polisher module, which produces the final assembly of high nucleotide-level quality.

Address of the bookmark: https://github.com/fenderglass/Flye

Bioinformatics Training Collections !

BioStar — Sun, 05 Mar 2023 23:01:26 -0600

Useful list of bioinformatics training collections @ https://github.com/sib-swiss/training-collection

Address of the bookmark: https://github.com/sib-swiss/training-collection

Ranbow: a haplotype assembler for polyploid genomes

Jit — Fri, 01 Jun 2018 07:21:54 -0500

Ranbow is a haplotype assembler for polyploid genomes. It has been developed for the haplotype assembly of the hexaploid sweet potato genome, which is highly heterozygous. Ranbow can also be applied to other polyploid genomes. After a first phasing, Ranbow utilizes the assembled haplotypes to improve the accuracy of variant calling results and to infer the evolutionary history of the organism´s genome. Ranbow has three main modes of function: ranbow hap: for haplotyping ranbow eval: for evaluating of the assemble haplotypes by gold standard (long) reads ranbow phylo: for the phylogenetic analysis

Address of the bookmark: https://www.molgen.mpg.de/ranbow

Bioinformatics Opening at NIBMG, India

Sun, 03 Dec 2023 00:16:59 -0600

NIBMG is looking for motivated and bright individuals interested to explore career
opportunities for the position of Research Associate (Project Linked Person) for extramural
project funded by ICMR as per details given below.
Project Name: Fast detection of driver mutations and genes from cancer genomics data using
an integrative machine learning-based approach.

More at https://www.nibmg.ac.in/uploads/3c5d4da3fb31bef490a218805408c858.pdf

Postdoc at UBasel Comparative Single Cell Genomics

Fri, 13 Dec 2024 12:46:19 -0600

A fully funded 4-year Postdoc position is available in the lab of Patrick
Tschopp at the University of Basel, Switzerland, study the molecular and
tissue-scale dynamics during the embryonic formation of the vertebrate
skeleton and compare it across different vertebrate species with distinct
habitats.

We are looking for a highly motivated candidate with a PhD degree in
Bioinformatics or a related field. Candidates are expected to have a
strong background in evolutionary biology and/or comparative functional
genomics. Additional experiences in single cell functional genomics
analyses, statistics and computational data analyses are a plus, as is
an interest in comparative developmental (EvoDevo) questions.

We offer a dynamic and interactive research environment with state-of-the
art research facilities, good research funding and internationally
competitive salaries.

The Tschopp lab (www.evolution.unibas.ch/tschopp/research/)
studies the gene regulatory mechanisms of cell type
specification and evolution in vertebrates. See also our
preprints at https://doi.org/10.1101/2024.03.26.586769 and
https://doi.org/10.1101/2024.11.28.625862 Applications should include
a motivation letter, a CV, a list of publications, a statement about
research interests, as well as the names and contact details of at
least two referees. Applications (in the form of a single .pdf file)
should be sent to Patrick Tschopp (patrick.tschopp@unibas.ch); review
of applications will begin on January 1st 2025, and will continue until
the position is filled.

Exploring Bioinformatics Job Websites: Your Gateway to a Thriving Career

BioStar — Sat, 19 Oct 2024 13:43:06 -0500

Bioinformatics is a rapidly growing field at the intersection of biology, computer science, and data analytics, with applications in healthcare, genomics, drug discovery, and more. As demand increases for skilled professionals who can manage, analyze, and interpret biological data, finding the right job opportunities can be challenging. Fortunately, numerous online platforms cater specifically to bioinformatics professionals, from academia to industry positions.

Here’s a curated list of the top websites offering bioinformatics job opportunities and postdoctoral fellowships worldwide.

1. General Bioinformatics Job Portals

These platforms are ideal for bioinformaticians seeking jobs in diverse sectors:

Nature Careers: A trusted resource for job seekers in the sciences, Nature Careers offers bioinformatics roles globally. Their specialized search function allows you to filter jobs by keyword, location, and more.
- Explore Bioinformatics Jobs on Nature Careers
Science Careers: A job board from the AAAS, this site focuses on STEM jobs, including numerous bioinformatics opportunities in academia and industry.
Euraxess: Euraxess is the go-to platform for researchers looking for jobs, fellowships, and funding across Europe and beyond. It lists both bioinformatics roles and research grants.
- Search Bioinformatics Jobs on Euraxess
ResearchGate Jobs: ResearchGate is widely known as a platform for researchers to share publications, but it also has a robust job board featuring bioinformatics positions globally.
FindAPostDoc: This site is dedicated to helping postdoctoral researchers find positions, with bioinformatics being a popular category.
Academic Positions: Targeting academic roles worldwide, Academic Positions lists bioinformatics jobs at universities and research institutions.
PostdocJobs.com: Specializing in postdoctoral roles, this platform is a great resource for early-career researchers looking for bioinformatics-related positions.
Scholarship Positions: In addition to jobs, Scholarship Positions provides information on scholarships, fellowships, and grants related to bioinformatics.

2. Fellowship and Training Opportunities in Bioinformatics

For those seeking fellowships or specialized training, these organizations offer postdoctoral programs, grants, and research opportunities:

NIH Office of Intramural Training and Education: The National Institutes of Health offer extensive research training programs for postdocs, including those in bioinformatics.
NSF Research Opportunity Awards: The National Science Foundation funds bioinformatics research at predominantly undergraduate institutions, providing fellowships and grants.
Top U.S. Universities: Many prestigious U.S. institutions, including Harvard, Berkeley, Yale, MIT, Johns Hopkins, UCSD, and Cornell, offer postdoctoral opportunities in bioinformatics.

3. Country-Specific Job and Fellowship Resources

If you're targeting a specific region, these platforms offer bioinformatics opportunities tailored to their respective countries:

Canada

CAPS/ACPP: The Canadian Association of Postdoctoral Scholars provides a job board, including bioinformatics roles in academia.
Banting Postdoctoral Fellowships: A prestigious fellowship program for postdocs in bioinformatics and related fields.
Mitacs Elevate: A Canadian initiative offering fellowships to connect postdoctoral researchers with industry partners.

United Kingdom

UKRI: The UK Research and Innovation body funds bioinformatics research and offers various grants.
The Royal Society: Provides funding schemes for researchers in bioinformatics.
Marie Skłodowska-Curie Actions: The MSCA funds fellowships and doctoral programs across Europe, including bioinformatics-related projects.
Wellcome Trust: Offers research funding and career development opportunities in health-related fields, including bioinformatics.

Europe

EMBO Fellowships: The European Molecular Biology Organization supports bioinformaticians through fellowships and career grants.
Max Planck Society: A leading research organization offering bioinformatics positions and fellowships across Europe.
Helmholtz Association: A major research organization in Germany offering bioinformatics roles in various disciplines.
Leibniz Association: Offers research opportunities, including bioinformatics, across its numerous institutes.

Australia and New Zealand

Australian Research Council: Offers funding and research schemes, including in bioinformatics.
Top Universities: Universities like Sydney, Melbourne, and Queensland have research programs in bioinformatics.

Asia

Japan Society for the Promotion of Science (JSPS): Offers fellowships for international researchers in bioinformatics.
Top Institutions: Universities like NUS, CAS, and IISc are leading hubs for bioinformatics research.

Middle East

Qatar Research, Development, and Innovation (QRDI): Offers research opportunities in bioinformatics.
KAUST: A leading university in Saudi Arabia offering bioinformatics research positions.

Africa

African Academy of Sciences: Provides career opportunities and research funding in bioinformatics across Africa.

Conclusion

The field of bioinformatics is full of exciting opportunities for those with the right skills. Whether you are looking for a postdoc position, research funding, or a long-term job in industry, these platforms are an excellent starting point. Explore, apply, and take the next step in your bioinformatics career!

Apollo: A Sequencing-Technology-Independent, Scalable, and Accurate Assembly Polishing Algorithm

BioStar — Mon, 16 Mar 2020 10:09:26 -0500

Apollo is an assembly polishing algorithm that attempts to correct the errors in an assembly. It can take multiple set of reads in a single run and polish the assemblies of genomes of any size. Described by Firtina et al. (preliminary version at https://arxiv.org/pdf/1902.04341.pdf

More at https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btaa179/5804978?rss=1

Address of the bookmark: https://github.com/CMU-SAFARI/Apollo

A Beginner's Guide to Using Kraken for Taxonomic Classification

Neel — Fri, 13 Dec 2024 11:29:03 -0600

Kraken is a popular bioinformatics tool designed for fast and accurate taxonomic classification of metagenomic sequences. Its efficiency and precision make it a go-to resource for analyzing microbial communities, including bacteria, viruses, archaea, and fungi. Whether you're new to bioinformatics or experienced in the field, Kraken is an indispensable tool for taxonomic analysis.

In this blog, we’ll walk through the basics of Kraken, from installation to running an analysis, and highlight its key features and applications.

What is Kraken?

Kraken is a sequence classification tool that assigns taxonomic labels to DNA sequences using exact k-mer matching. It uses a reference database of genomes, dividing sequences into k-mers and identifying matches in a computationally efficient way.

Key Features of Kraken

Speed: Kraken processes data much faster than alignment-based methods.
Accuracy: It uses a precise k-mer matching algorithm for high-resolution taxonomic assignments.
Scalability: It can handle large metagenomic datasets.
Custom Databases: You can build and use custom databases tailored to your research needs.

Installing Kraken

System Requirements
- A Unix-based operating system (Linux/macOS).
- Sufficient computational resources for database building (RAM and disk space).
Installation Steps
- Clone the Kraken repository from GitHub:
  
  git clone https://github.com/DerrickWood/kraken.git cd kraken
- Compile the Kraken binaries:
  
  make
- Add Kraken to your PATH for easy access:
  
  export PATH=$PATH:/path/to/kraken

Preparing a Database

Kraken requires a database of reference genomes. You can use a pre-built database or create a custom one.

Downloading a Pre-built Database
Kraken offers pre-built databases, such as the MiniKraken database, which is lightweight and suitable for smaller datasets. Download it using:

kraken-build --download-library minikraken
Building a Custom Database
To include specific genomes, download FASTA files and build the database:

kraken-build --download-library bacteria --threads 4 --db my_database kraken-build --build --db my_database

This process may take considerable time and resources, depending on the size of the database.

Running Kraken

Once the database is ready, you can classify sequences.

Basic Usage
Use the following command to classify sequences:

kraken --db my_database --threads 4 --fastq-input input_sequences.fastq --output kraken_output.txt

Key options:
- --db: Specifies the database.
- --threads: Number of threads for parallel processing.
- --fastq-input: Indicates input file format (FASTQ/FASTA).
Interpreting Results
Kraken generates an output file with columns for sequence IDs, taxonomic classifications, and the confidence score.

Visualizing Kraken Results

Kraken results can be visualized using tools like Krona or converted to human-readable reports using kraken-report.

Generate a Report

kraken-report --db my_database kraken_output.txt > kraken_report.txt
Krona Visualization
Install Krona and convert Kraken output for visualization:

cut -f2,3 kraken_output.txt | ktImportTaxonomy -o krona_output.html

Open the HTML file in your browser to interactively explore the taxonomic classifications.

Advanced Usage

Confidence Thresholds
Adjust the confidence threshold for classification using the --confidence option. Higher values reduce false positives but may miss some true positives:

kraken --db my_database --confidence 0.1 --fastq-input input.fastq
Paired-End Reads
For paired-end sequencing data, use:

kraken --db my_database --paired reads_1.fastq reads_2.fastq
Customizing K-mers
Kraken allows you to set custom k-mer lengths during database building for specific applications.

Applications of Kraken

Microbial Ecology: Characterizing microbial communities in soil, water, and the human microbiome.
Pathogen Detection: Identifying pathogens in clinical samples.
Fungal Research: Analyzing fungal diversity in metagenomic datasets.
Environmental Monitoring: Tracking microbial populations in diverse habitats.

Conclusion

Kraken is a versatile and efficient tool for taxonomic classification in metagenomics. Its speed, accuracy, and flexibility make it a favorite among bioinformaticians. By following this guide, you can set up and use Kraken to unlock insights into microbial and fungal communities, paving the way for discoveries in ecology, medicine, and biotechnology.

The Future of Bioinformatics: Innovations and Opportunities

BioStar — Mon, 20 Jan 2025 12:44:53 -0600

Bioinformatics, the interdisciplinary field that merges biology, computer science, and statistics, has transformed the way we understand biological systems. As we stand at the cusp of a new era in scientific discovery, the future of bioinformatics promises even greater advancements, powered by cutting-edge technologies and a growing understanding of life’s complexities.

1. Big Data and Bioinformatics

The exponential growth in biological data, driven by advancements in sequencing technologies and high-throughput experiments, has made bioinformatics an indispensable tool. By 2030, we anticipate:

Petabyte-Scale Data Management: Enhanced storage solutions and cloud computing platforms will allow researchers to handle the vast amounts of data generated from omics studies, including genomics, transcriptomics, and proteomics.
AI and Machine Learning Integration: Sophisticated algorithms will uncover patterns and relationships in large datasets, enabling predictions about gene function, disease susceptibility, and therapeutic outcomes.

2. Personalized Medicine and Genomics

Bioinformatics will play a pivotal role in tailoring healthcare to individual patients. Key developments include:

Whole-Genome Sequencing in Clinics: The decreasing cost of sequencing will make it routine in medical diagnostics, enabling personalized treatment plans based on an individual’s genetic makeup.
Drug Repurposing and Development: Computational tools will identify potential new uses for existing drugs, accelerating the development of targeted therapies.

3. Advancing Computational Tools

The future will see the development of more user-friendly and powerful bioinformatics tools:

Graph-Based Approaches: Enhanced algorithms for analyzing complex biological networks, such as protein-protein interaction maps.
Visualization Tools: Intuitive software for visualizing multi-dimensional data, enabling researchers to interpret findings more effectively.

4. Synthetic Biology and Systems Biology

Bioinformatics will continue to drive progress in synthetic and systems biology by:

Gene Circuit Design: Leveraging computational models to design and simulate synthetic biological systems.
Understanding Cellular Pathways: Integrating multi-omics data to model cellular processes with unprecedented accuracy.

5. Bioinformatics in Agriculture and Environmental Science

Beyond healthcare, bioinformatics will revolutionize agriculture and environmental conservation:

Crop Improvement: Genomic studies will help develop high-yield, disease-resistant, and climate-resilient crops.
Microbial Ecology: Metagenomics will enhance our understanding of microbial communities, aiding in bioremediation and ecosystem management.

6. Democratization of Bioinformatics

Open-source software and accessible education will broaden participation in bioinformatics research:

Community-Driven Projects: Collaborative platforms like GitHub will continue to foster innovation in tool development.
Education and Training: Online courses and workshops will bridge skill gaps, enabling researchers from diverse backgrounds to contribute.

Challenges and Ethical Considerations

While the future is bright, challenges remain. Data privacy and ethical concerns surrounding genetic information require careful navigation. Furthermore, addressing the digital divide is critical to ensuring equitable access to bioinformatics resources globally.

Conclusion

The future of bioinformatics is boundless, with opportunities to revolutionize our understanding of life and improve human health. As technologies evolve and collaborations flourish, bioinformatics will undoubtedly remain at the forefront of scientific discovery, unlocking the secrets of life one dataset at a time.