3rd Version bioinformatics workshop

3rd Version bioinformatics workshop

3rd Version bioinformatics workshop. Intensive in R/Bioconducor and Cytoscape.

The overall objective of this workshop is to empower his assistants in the understanding of omics technologies and different methods of analysis that represents this type of data, using alternatives of softwares free as "R/Bioconductor" and "Cytoscape". This will be achieved through understanding fully of the workflow involved in each technology, to finally get results whose biological interpretation is charged meaning and allows correct decision making.

Session 1: Wednesday, November 14

  1. Statistics for Bioinformatics basics:
  • Classical statistics: null hypothesis, alternative hypothesis, p-values.
  • Bayesian statistics: a posteriori probability and decision theory.
  • Machine Learning in Bioinformatics: Clustering, Heatmaps, PCA, t-SNE.
  • Introduction to R/Bioconductor

Session 2: Wednesday, November 28

  1. Massive sequencing and Transcriptomics:
  • Massive sequencing and single molecule technologies.
  • Transcriptomics: Microarrays, RNA-seq and single-cell sequencing.
  • Practical in R/Bioconductor: statistical analysis of differential expression from RNA-seq data. PCA, Clustering, Heatmaps, and graphics of differentially expressed genes.

Session 3: Wednesday 05 of December

  1. Statistical analysis of results differential post-expression part I:
  • Statistical analysis of biological pathways.
  • Use of functional annotation databases: GeneOntology (GO), KEGG.
  • Practical in R/Bioconductor: analysis of enrichment of biological processes, molecular function, cellular components (GO) and biological pathways (KEGG). Graphics of enrichments.
  • Practical in Cytoscape: introduction to Cytoscape. Analysis of enrichment. Views and customization of graphics.

Session 4: Wednesday December 12

  1. Statistical analysis of results differential post-expression part II:
  • Statistical analysis of biological networks.
  • Coexpression of networks. Protein-protein interaction networks.
  • Search in silico e Vivo (ChIP-seq) sites of transcription factors. Gene regulatory networks.
  • Practical in R/Bioconductor and Cytoscape. Transcriptomic will be calculated from data: networks of coexpression, protein-protein interaction, Clustering and subnets. Search for microRNAs and transcription factors binding sites.

Session 5: Wednesday, December 19

  1. Introduction to the Microbiota statistical analysis:
  • Applications of molecular markers: 16/18S.
  • Operational Taxonomic Unit (OTU) versus Amplicon Sequence Variant (ASV).
  • Workflow: Experimental Design trimming and filtering of FASTQ file, mapping species, building phylogenetic tree, statistical analysis of diversity and composition of communities.
  • Practical in R/Bioconductor, Cytoscape: using files FASTQ public will take place the complete analysis workflow.

Registration cost: $100,000. Total cost for 5 sessions (15 hours).

Registration and further information: Goo.GL/iNzs9j