Training eSupport System
  • Log In
    • Log in with LS Login
    • Login
    • Register
  • About
  • Events
  • Materials
  • e-Learning
  • Workflows
  • Collections
  • Learning paths
  • Directory
    • Providers
    • Nodes
    • Spaces

TeSS makes use of some necessary cookies to provide its core functionality. Additionally, we make use of Google Analytics to discover how people are using TeSS in order to help us improve the service. To opt out of this, choose the "Allow necessary cookies" option.

See our Privacy Policy for more information.

You can modify your cookie preferences at any time here, or from the link in the footer.

Allow necessary cookies Allow all cookies
  1. Home
  2. Materials

Filter

  • Sort

  • Filter Clear filters

    • Date added
    • In the last 24 hours
    • In the last 1 week
    • In the last 1 month
    • Scientific topic
    • Bayesian methods
    • R89
    • R program89
    • R script89
    • Biostatistics29
    • Descriptive statistics29
    • Gaussian processes29
    • Inferential statistics29
    • Markov processes29
    • Multivariate statistics29
    • Probabilistic graphical model29
    • Probability29
    • Statistics29
    • Statistics and probability29
    • Data rendering21
    • Data visualisation21
    • Comparative transcriptomics20
    • Transcriptome20
    • Transcriptomics20
    • MicroRNA sequencing16
    • RNA sequencing16
    • RNA-Seq16
    • RNA-Seq analysis16
    • Small RNA sequencing16
    • Small RNA-Seq16
    • Small-Seq16
    • Transcriptome profiling16
    • WTSS16
    • Whole transcriptome shotgun sequencing16
    • miRNA-seq16
    • Genome annotation15
    • Exomes13
    • Genomes13
    • Genomics13
    • Personal genomics13
    • Synthetic genomics13
    • Viral genomics13
    • Whole genomes13
    • Active learning11
    • Ensembl learning11
    • Kernel methods11
    • Knowledge representation11
    • Machine learning11
    • Neural networks11
    • Recommender system11
    • Reinforcement learning11
    • Supervised learning11
    • Unsupervised learning11
    • Single-cell genomics10
    • Single-cell sequencing10
    • Chromosome walking8
    • Clone verification8
    • DNA-Seq8
    • DNase-Seq8
    • High throughput sequencing8
    • High-throughput sequencing8
    • NGS8
    • NGS data analysis8
    • Next gen sequencing8
    • Next generation sequencing8
    • Panels8
    • Primer walking8
    • R markdown8
    • Sanger sequencing8
    • Sequencing8
    • Targeted next-generation sequencing panels8
    • Bottom-up proteomics4
    • Discovery proteomics4
    • Integrative omics4
    • MS-based targeted proteomics4
    • MS-based untargeted proteomics4
    • Metaproteomics4
    • Multi-omics4
    • Multiomics4
    • Pan-omics4
    • Panomics4
    • Peptide identification4
    • Protein and peptide identification4
    • Proteomics4
    • Quantitative proteomics4
    • Targeted proteomics4
    • Top-down proteomics4
    • Pipelines3
    • Python3
    • Python program3
    • Python script3
    • Software integration3
    • Tool integration3
    • Tool interoperability3
    • Variant pattern analysis3
    • Workflows3
    • py3
    • Antimicrobial stewardship2
    • CWL2
    • Common Workflow Language2
    • CommonWL2
    • Data management2
    • Enrichment2
    • Enrichment analysis2
    • Functional enrichment2
    • Show N_FILTERS more
    • Content provider
    • Glittr.org27
    • European Bioinformatics Institute (EBI)1
    • GOBLET1
    • Show N_FILTERS more
    • Keyword
    • R
    • Statistics45
    • Data science9
    • Machine learning9
    • RNA-seq6
    • Data visualization4
    • General4
    • Transcriptomics4
    • Genomics3
    • Single-cell sequencing3
    • Biostatistics2
    • Next generation sequencing2
    • Python2
    • Version control2
    • ATAC-seq1
    • Data management1
    • Multiomics1
    • Open access1
    • Pathways and Networks1
    • Rmarkdown1
    • Spatial transcriptomics1
    • Unix/Linux1
    • Workflows1
    • microbial ecosystems1
    • microbiome1
    • Show N_FILTERS more
    • Competency level
    • Not specified29
    • Show N_FILTERS more
    • Licence
    • License Not Specified
    • MIT License8
    • Creative Commons Zero v1.0 Universal3
    • GNU General Public License v3.0 only1
    • Show N_FILTERS more
    • Target audience
    • Clinicians1
    • PhD students1
    • Show N_FILTERS more
    • Author
    • SIB Swiss Institute of Bioinformatics2
    • The Gulbenkian Training Programme in Bioinformatics2
    • András Aszódi1
    • CRUK CI Bioinformatics Core1
    • Causal Inference in R1
    • Computational Biology and Bioinformatics at UCLouvain1
    • Daniel Kaplan1
    • Danielle Navarro1
    • David Dalpiaz1
    • Emil Hvitfeldt1
    • Jacques van Helden1
    • Matthew B. Jané1
    • ModernDive1
    • Monash Data Fluency1
    • Måns Thulin1
    • OpenIntro1
    • Oscar Baruffa1
    • Paul Roback1
    • RStudio Education1
    • Stephen Turner1
    • Surgical Informatics1
    • The Carpentries Incubator1
    • bioinformatics.ca1
    • gladstone-institutes1
    • posit-conf-20231
    • robinsonlabuzh1
    • Show N_FILTERS more
    • Contributor
    • Adejumo Ridwan Suleiman2
    • Emil Hvitfeldt2
    • Metehan GÜNGÖR2
    • Mine Cetinkaya-Rundel2
    • Måns Thulin2
    • The Gulbenkian Training Programme in Bioinformatics2
    • e-linc2
    • Adam Fleischhacker1
    • Ailith Ewing1
    • Alan O'Callaghan1
    • Alan T. Arnholt1
    • Albert Y. Kim1
    • Alexander Pico1
    • Alison Presmanes Hill1
    • Allison Theobold1
    • Ana B1
    • Anders Riutta1
    • Andrew Bray1
    • Andrew Heiss1
    • Andrzej Romaniuk1
    • Annajiat Alim Rasel1
    • Antoine Bichat1
    • AshKernow1
    • Ashish Kumar1
    • Ayushi Agrawal1
    • Becki R1
    • Ben Baumer1
    • Binxiang Ni1
    • Bjørn Peare Bartholdy1
    • Bryan Shalloway1
    • CATALYST-project1
    • Caitlin Eger1
    • Canadian Bioinformatics Workshops1
    • Carina Silva1
    • Carlos Paniagua1
    • Catalina Vallejos1
    • Christophe Dervieux1
    • Clayton Hughes1
    • Colin Fay1
    • Colin Rundel1
    • Craig Bonsignore1
    • Dale Maschette1
    • Damien Ready1
    • Daniel Kaplan1
    • Danielle Navarro1
    • David A. Parry1
    • David Dalpiaz1
    • David Kane1
    • David Solito1
    • Debbie Yuster1
    • Dorothy Bishop1
    • Dr. Chester Ismay1
    • Dr. Saurav Singla1
    • Emily Kothe1
    • Eric Leung1
    • Erik Erhardt1
    • Erin LaBrecque1
    • Ezekiel Adebayo Ogundepo1
    • Gail Robertson1
    • GaryBikini1
    • Giuseppe Burtini1
    • Grace Lawley1
    • Guy Incognito1
    • Hannes Becher1
    • Hernando Cortina1
    • Hugo Varet1
    • Hywel Dunn-Davies1
    • Isabella Velásquez1
    • Izaskun Mallona1
    • Jack M Wolf1
    • Jacob Bien1
    • Jacques van Helden1
    • Jakob Schumacher1
    • James J Balamuta1
    • Jamie Lendrum1
    • Jannik Buhr1
    • Javier Orraca-Deatcu1
    • Jean-Marie Pivette1
    • Jennifer (Jenny) Bryan1
    • Jo Hardin1
    • Joel Ostblom1
    • John Coene1
    • Jon Calder1
    • Julia Silge1
    • Kelly N. Bodwin1
    • Ken Taylor1
    • Kenny Armstrong1
    • Krishna Choudhary1
    • Kristian Lundby Gjerde1
    • Kristina Hanspers1
    • LaurenCCH1
    • Laurent Gatto1
    • Leandro Lima1
    • Legana Fingerhut1
    • Little Miss Data1
    • Lluís Revilla1
    • Louis Aslett1
    • Lucy D'Agostino McGowan1
    • MMJansen1
    • Malcolm Barrett1
    • Show N_FILTERS more
    • Resource type
    • e-learning1
    • Show N_FILTERS more
    • Node
    • Switzerland27
    • EMBL-EBI1
    • Show N_FILTERS more
  • Show materials from all spaces
  • Show disabled materials
  • Show materials with broken links
  • Show archived materials

Training materials

  • Subscribe via email

Email Subscription

Register training material

Scientific topics: Bayesian methods

and Keywords: R

and Licence: License Not Specified

29 materials found
  • bioinformaticsdotca/STAT_2024

    ELIXIR node event
    Statistics and probability Statistics R
  • robinsonlabuzh/pasta

    ELIXIR node event
    Statistics and probability Statistics R Spatial transcriptomics
  • EmilHvitfeldt/feature-engineering-az

    ELIXIR node event
    Machine learning Statistics and probability Machine learning Statistics Data science Python R
  • gladstone-institutes/Bioinformatics-Workshops

    ELIXIR node event
    Genomics Transcriptomics Machine learning Statistics and probability Single-cell sequencing RNA-Seq Pathway or network Data visualisation General R …
  • stephenturner/workshops

    ELIXIR node event
    Genomics Statistics and probability Data visualisation R markdown RNA-Seq R Data visualization Rmarkdown RNA-seq Genomics …
  • dtkaplan/Lessons-in-statistical-thinking

    ELIXIR node event
    Statistics and probability Statistics R
  • mthulin/mswr-book

    ELIXIR node event
    Statistics and probability Statistics R
  • OpenIntroStat/ims

    ELIXIR node event
    Statistics and probability Statistics R Data science
  • GTPB/ABSTAT18

    ELIXIR node event
    Statistics and probability R Statistics
  • sib-swiss/multiomics-data-analysis-and-integration-training

    ELIXIR node event
    Multiomics Statistics and probability Multiomics R Statistics
  • 1
  • 2
  • 3
Training eSupport System
[email protected]
Contribute
About TeSS
Browse Spaces
Funding & acknowledgements
Privacy
Cookie preferences
Version: 1.5.1
Source code
API documentation
Bioschemas testing tool

TeSS has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 676559.