RNA sequencing (RNA-Seq) is a powerful tool that captures information about how organisms respond to stimuli in their environment at the molecular level. A common RNA-Seq approach involves isolating and sequencing all of the messenger RNA (mRNA) in a tissue sample taken from an organism. Researchers can compare patterns observed in RNA-Seq data to understand how individuals respond to the environment over minutes, hours, or days and how populations evolve in response to the environment over millions of years. The materials in this repository will guide users through an analysis of RNA-Seq data collected from two California populations of a copepod crustacean, Tigriopus californicus, that were exposed to different levels of salinity. Users will examine the contents of a fastq file that contains raw RNA-Seq data, determine the quality of the RNA-Seq data using a web-server, and test for significant differences in gene expression between the copepod populations using the R packages DE...

Bioinformatics workshop and conferences organized in Pakistan.

Post-processed FreeBayes variant calls for use in the 2020 bioinformatics workshop for unit CEA301.

These are derived from data published previously in Training material for the course "Exome analysis with GALAXY". Credit for uploading the original data goes to Paolo Uva and Gianmauro Cuccuru!

This record includes training materials associated with the Australian BioCommons workshop ‘Introduction to Machine Learning in R - from data to knowledge’. This workshop took place over one, 4 hour sessions on 09 December 2024. Event description With the rise in high-throughput sequencing technologies, the volume of omics data has grown exponentially. A major issue is to mine useful knowledge from these heterogeneous collections of data. The analysis of complex high-volume data is not trivial and classical tools cannot be used to explore their full potential. Machine Learning (ML), a discipline in which computers perform automated learning without being programmed explicitly and assist humans to make sense of large and complex data sets, can thus be very useful in mining large omics datasets to uncover new insights that can advance the field of bioinformatics. This hands-on workshop will introduce participants to the ML taxonomy and the applications of common ML algorithms to health data. The workshop will cover the foundational concepts and common methods being used to analyse omics data sets by providing a practical context through the use of basic but widely used R libraries. Participants will acquire an understanding of the standard ML processes, as well as the practical skills in applying them on familiar problems and publicly available real-world data sets. Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event. Lead trainers: Dr Fotis Psomopoulos, Senior Researcher, Institute of Applied Biosciences (INAB), Center for Research and Technology Hellas (CERTH) Facilitators: Dr Giorgia Mori, Australian BioCommons Dr Eden Zhang, Sydney Informatics Hub Dr Erin Graham, Queensland Cyber Infrastructure Foundation (QCIF) Infrastructure provision: Uwe Winter, Australian BioCommons Host: Dr. Giorgia Mori, Australian BioCommons Training materials Files and materials included in this record: Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. Training materials webpage Data and documentation

Advances in high-throughput techniques have resulted in a rising demand for scientists with basic bioinformatics skills as well as workshops and curricula that teach students bioinformatics concepts. DNA Detective is a workshop we designed to introduce students to big data and bioinformatics using CyVerse and the Dolan DNA Learning Center's online DNA Subway platform. DNA Subway is a user-friendly workspace for genome analysis and uses the metaphor of a network of subway lines to familiarize users with the steps involved in annotating and comparing DNA sequences. For DNA Detective, we use the DNA Subway Red Line to guide students through analyzing a "mystery" DNA sequence to distinguish its gene structure and name. During the workshop, students are assigned a unique Arabidopsis thaliana DNA sequence. Students "travel" the Red Line to computationally find and remove sequence repeats, use gene prediction software to identify structural elements of the sequence, search databases of known genes to determine the identity of their mystery sequence, and synthesize these results into a model of their gene. Next, students use The Arabidopsis Information Resource (TAIR) to identify their gene's function so they can hypothesize what a mutant plant lacking that gene might look like (its phenotype). Then, from a group of plants in the room, students select the plant they think is most likely defective for their gene. Through this workshop, students are acquainted to the flow of genetic information from genotype to phenotype and tackle complex genomics analyses in hopes of inspiring and empowering them towards continued science education.

Four PBMC scRNA-seq datasets (~1,000 cells each) for analysis with CBW_CAN_SingleCell_*R scripts

MTX files were downloaded from 10X publicly available datasets.

This record includes training materials associated with the Australian BioCommons workshop ‘Make your bioinformatics workflows findable and citable’. This workshop took place on 21 March 2023. Event description Computational workflows are invaluable resources for research communities. They help us standardise common analyses, collaborate with other researchers, and support reproducibility. Bioinformatics workflow developers invest significant time and expertise to create, share, and maintain these resources for the benefit of the wider community and being able to easily find and access workflows is an essential factor in their uptake by the community. Increasingly, the research community is turning to workflow registries to find and access public workflows that can be applied to their research. Workflow registries support workflow findability and citation by providing a central repository and allowing users to search for and discover them easily. This workshop will introduce you to workflow registries and support attendees to register their workflows on the popular workflow registry, WorkflowHub. We’ll kick off the workshop with an introduction to the concepts underlying workflow findability, how it can benefit workflow developers, and how you can make the most of workflow registries to share your computational workflows with the research community. You will then have the opportunity to register your own workflows in WorkflowHub with support from our trainers. Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event. Files and materials included in this record: Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. Index of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file. 2023-03-21_Workflows_slides (PDF): A copy of the slides presented during the workshop Materials shared elsewhere: A recording of the first part of this workshop is available on the Australian BioCommons YouTube Channel: https://youtu.be/2kGKxaPuQN8

This record includes training materials associated with the Australian BioCommons workshop ‘Genetic Outlier Analysis’. These workshops took place on: 27 - 28 February 2024: Online via Zoom 10 - 11 April 2024: In person in Melbourne 4 - 5 July 2024: In person in Sydney Event description There are many interesting patterns that you can extract from genetic variant data. This can include patterns of linkage, balancing selection, or even inbreeding signals. One of the most common approaches is to find sites on the genome that are under selection. This workshop introduces the basics of genetic selection analysis. It will step you through the process of identifying signals of selection using your own data (or an example genomic dataset) using the outlier analysis method. Materials are shared under a Creative Commons Attribution 4.0 International agreement unless otherwise specified and were current at the time of the event. This workshop is presented by the Australian BioCommons and the Genetics Society of AustralAsia Lead trainer: Dr Katarina Stuart, Research Fellow, University of Auckland. Facilitators: Adele Barugahare, Monash Genomics and Bioinformatics Platform Dr Georgina Samaha, Sydney Informatics Hub, University of Sydney Dr Ching-Yu Lu, Sydney Informatics Hub, University of Sydney Soleille Miller, University of NSW Dr Nandan Deshpande, Sydney Informatics Hub, University of Sydney Infrastructure provision: Audrey Stott, Pawsey Supercomputing Research Centre Host: Dr Melissa Burke, Australian BioCommons Training materials Files and materials included in this record: Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. Schedules describing the timing of sessions for the in person and online events Materials shared elsewhere: These workshops followed the materials developed by Dr Katarina Stuart https://github.com/katarinastuart/Ev1_SelectionMetaAnalysis

These are the course materials for the Intro to R workshop taught by Ibraheem for the Collaboratory Workshop series as part of Applied Bioinformatics M275A and Molecular, Cellular and Developmental Biology MCDB199.

Bioinformatics.ca has been hosting continuing education programs in introductory and advanced bioinformatics topics in Canada since 1999 and has trained more than 2,000 participants to date. These workshops have been adapted over the years to keep pace with advances in both science and technology as well as the changing landscape in available learning modalities and the bioinformatics training needs of our audience. Post-workshop surveys have been a mandatory component of each workshop and are used to ensure appropriate adjustments are made to workshops to maximize learning. However, neither bioinformatics.ca nor others offering similar training programs have explored the long-term impact of bioinformatics continuing education training. Bioinformatics.ca recently initiated a look back on the impact its workshops have had on the career trajectories, research outcomes, publications, and collaborations of its participants. Using an anonymous online survey, bioinformatics.ca analyzed responses from those surveyed and discovered its workshops have had a positive impact on collaborations, research, publications, and career progression.

Metadata of the study entitled: Drought influences the fungal community structure, diversity, and functionality inhabiting the grapevine xylem and enhances the abundance of Phaeomoniella chlamydospora

Research story artefact of the Bioplatforms Australia - CSIRO NGS Workshop (July 9-10 2012) on the Monash Research Cloud (R@CMon).

The dataset consists of whole genome DNA sequences, generated from invertebrate species from the Gulf of Mexico during the Benthic Invertebrate Taxonomy, Metagenomics, and Bioinformatics Workshop (BITMaB) in 2017 in Corpus Christi, Texas, USA. All genomic data sets were deposited in and distributed by GenBank (NCBI), the European Nucleotide Archive (ENA)- European Bioinformatics Institute (EMBL-EBI), DNA Data Bank of Japan, NemATOL, the Global Genome Initiative, and Ocean Genome Legacy.

The Genome Solver was an NSF-funded project developed as a way to train undergraduate life science faculty in basic web-based tools for bioinformatics. As part of the project we developed a one-day workshop consisting of bioinformatics modules on the theme of bacterial genomics, which we delivered to faculty at colleges and universities around the country. All of our workshop material can be accessed on the QUBESHub website: https://qubeshub.org/community/groups/genomesolver/

This record includes training materials associated with the Australian BioCommons workshop ���Online data analysis for biologists���. This workshop took place on 9 September 2021. Workshop description Galaxy is an online platform for biological research that allows people to use computational data analysis tools and workflows without the need for programming experience. It is an open source, web-based platform for accessible, reproducible, and transparent computational biomedical research. It also captures run information so that workflows can be saved, repeated and shared efficiently via the web. This interactive beginners workshop will provide an introduction to the Galaxy interface, histories and available tools. The material covered in this workshop is freely available through the Galaxy Training Network. The workshop will be held via Zoom and involves a combination of presentations by the lead trainer and smaller breakout groups supported by experienced facilitators. The materials are shared under a Creative Commons 4.0 International agreement unless otherwise specified and were current at the time of the event. Files and materials included in this record: Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc. Index of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file. Schedule (PDF): schedule for the workshop Online_data_analysis_for_biologists_extraslides (PPTX and PDF): Slides used to introduce the data set and emphasise the importance of workflows. These slides were developed by Ms Grace Hall. Materials shared elsewhere: The tutorial used in this workshop is available via the Galaxy Training Network. Anne Fouilloux, Nadia Gou��, Christopher Barnett, Michele Maroni, Olha Nahorna, Dave Clements, Saskia Hiltemann, 2021 Galaxy 101 for everyone (Galaxy Training Materials). https://training.galaxyproject.org/training-material/topics/introduction/tutorials/galaxy-intro-101-everyone/tutorial.html Online; accessed Fri Dec 10 2021

Database of curated links to molecular resources, tools and databases selected on the basis of recommendations from bioinformatics experts in the field. This resource relies on input from its community of bioinformatics users for suggestions. Starting in 2003, it has also started listing all links contained in the NAR Webserver issue. The different types of information available in this portal: * Computer Related: This category contains links to resources relating to programming languages often used in bioinformatics. Other tools of the trade, such as web development and database resources, are also included here. * Sequence Comparison: Tools and resources for the comparison of sequences including sequence similarity searching, alignment tools, and general comparative genomics resources. * DNA: This category contains links to useful resources for DNA sequence analyses such as tools for comparative sequence analysis and sequence assembly. Links to programs for sequence manipulation, primer design, and sequence retrieval and submission are also listed here. * Education: Links to information about the techniques, materials, people, places, and events of the greater bioinformatics community. Included are current news headlines, literature sources, educational material and links to bioinformatics courses and workshops. * Expression: Links to tools for predicting the expression, alternative splicing, and regulation of a gene sequence are found here. This section also contains links to databases, methods, and analysis tools for protein expression, SAGE, EST, and microarray data. * Human Genome: This section contains links to draft annotations of the human genome in addition to resources for sequence polymorphisms and genomics. Also included are links related to ethical discussions surrounding the study of the human genome. * Literature: Links to resources related to published literature, including tools to search for articles and through literature abstracts. Additional text mining resources, open access resources, and literature goldmines are also listed. * Model Organisms: Included in this category are links to resources for various model organisms ranging from mammals to microbes. These include databases and tools for genome scale analyses. * Other Molecules: Bioinformatics tools related to molecules other than DNA, RNA, and protein. This category will include resources for the bioinformatics of small molecules as well as for other biopolymers including carbohydrates and metabolites. * Protein: This category contains links to useful resources for protein sequence and structure analyses. Resources for phylogenetic analyses, prediction of protein features, and analyses of interactions are also found here. * RNA: Resources include links to sequence retrieval programs, structure prediction and visualization tools, motif search programs, and information on various functional RNAs.

Handout and figure from a workshop on processing data from The Cancer Genome Atlas project. Uses the RTCGAToolbox to access Broad Institute Firehose data, examine the data and produce plots. The workshop was given in San Juan, PR, at the University of Puerto Rico Medical School, on Friday, April 17, 2015. The workshop was sponsored by the UPR/MDACC Parnership for Excellence in Cancer Research and the Puerto Rico Clinical and Translational Research Consortium.

In Brazil, training capable bioinformaticians is done, mostly, in graduate programs, sometimes with experiences during the undergraduate period. However, this formation tends to be inefficient in attracting students to the area and mainly in attracting professionals to support research projects in research groups. To solve these issues, participation in short courses is important for training students and professionals in the usage of tools for specific areas that use bioinformatics, as well as in ways to develop solutions tailored to the local needs of academic institutions or research groups. In this aim, the project “Bioinformática na Estrada” (Bioinformatics on the Road) proposed improving bioinformaticians’ skills in undergraduate and graduate courses, primarily in the countryside of the State of Pará, in the Amazon region of Brazil. The project scope is practical courses focused on the areas of interest of the place where the courses are occurring to train and encourage students and researchers to work in this field, reducing the existing gap due to the lack of qualified bioinformatics professionals. Theoretical and practical workshops took place, such as Introduction to Bioinformatics, Computer Science Basics, Applications of Computational Intelligence applied to Bioinformatics and Biotechnology, Computational Tools for Bioinformatics, Soil Genomics and Research Perspectives and Horizons in the Amazon Region. In the end, 444 undergraduate and graduate students from higher education institutions in the state of Pará and other Brazilian states attended the events of the Bioinformatics on the Road project.

Presentation on computational biology in undergraduate education at the 2019 Great Lakes Bioinformatics Conference

This archive contains supplementary material used in the workshop "Introduction to single cell RNAseq analysis" taught by the Danish National Sandbox for Health Data Science. The course repo can be found on Github. Data.zip contains 6 10x runs on Spermatogonia development. 3 from healthy individuals and 3 from azoospermic individuals. Data has been already preprocessed using cellranger and can be loaded using Seurat (R) or scanpy (python). Slides.zip contains slides explaning theory regarding single cell RNAseq data analysis Notebooks.zip contains Rmarkdown files to follow the course in using R in Rstudio. Updated version of the notebooks.