6th Version bioinformatics course: intensive in R/Bioconducor and Cytoscape

6th Version bioinformatics course: intensive in R/Bioconducor and Cytoscape

"The overall objective of this intensive is to empower its participants in the understanding of omics technologies and different methods of analysis that represents this type of data, using free software such as"R/Bioconductor"alternatives 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 with meaning and allows correct decision making.

Session 1: Thursday, June 13. Fundamentals of statistics for bioinformatics.

  • Classical statistics: null hypothesis, alternative hypothesis, p-values.
  • Correction for multiple comparisons: adjusted p-values.
  • Bayesian statistics: a posteriori probability and decision theory.

Session 2: Tuesday, June 18. R for Bioinformatics programming.

  • Introduction to programming in R and use RStudio.
  • Types of variables: vectors, matrices, factors, data frames, ready.
  • Control flow and conditionals, loops, functions, family apply.
  • Management of FASTA files, FASTQ, BAM, BED, csv, txt.

Session 3: Thursday, June 20. Massive sequencing and Machine Learning in Bioinformatics.

  • Massive sequencing and single molecule technologies.
  • Machine Learning using omics data. Unsupervised methods; PCA, t-SNE, NMDS, PCoA, Clustering. Supervised methods; L/hdc, KNN, SVM, CART and Random Forest.
  • Practical in R/Bioconductor.

Session 4: Tuesday, June 25. Analysis of Microbiota by amplification of 16/18S.

  • Applications of molecular markers: 16/18S using Illumina.
  • Operational Taxonomic Unit (OTU) versus Amplicon Sequence Variant (ASV).
  • Workflow: Experimental design, trimming and filtering of files FASTQ, mapping species, phylogenetic tree construction, statistical analysis of alpha diversity, beta, range and composition of communities.
  • Practical in R/Bioconductor: workflow using public FASTQ.

Session 5: Thursday, June 27. Introduction to Transcriptomics.

  • Transcriptomics: Microarrays, RNA-seq Bulk and single-cell RNA-seq.
  • Analysis of differential expression: comparison of frequentist and Bayesian statistical methods.
  • Practical in R/Bioconductor: statistical analysis of differential expression of RNA-seq and microarray data.

Session 6: Tuesday, July 2. Statistical analysis of results differential post-expression part I.

  • Statistical analysis of biological pathways.
  • Use of functional annotation databases: Gene Ontology (GO), KEGG.
  • Practical in R/Bioconductor: analysis of enrichment of biological processes, molecular function, cellular components (GO) and biological pathways (KEGG). Graphic dbuilder-evente enrichments.
  • Practical in Cytoscape: introduction to Cytoscape. Analysis of enrichment. Views and customization of graphics.

Session 7: Thursday, July 4. Statistical analysis of results differential post-expression part II.

  • Statistical analysis of biological networks.
  • Gene co-expression networks. Protein-protein interaction networks.
  • Practical in R/Bioconductor and Cytoscape. Transcriptomic will be calculated from data: networks of co-expression of interaction protein-protein.

Session 8: Tuesday, July 11. Statistical analysis of results differential post-expression part III.

  • Gene regulatory networks.
  • Search in silico and microRNAs and transcription factor binding sites in vivo.
  • Immunoprecipitation of chromatin followed by sequencing: ChIP-seq.
  • Practical in R/Bioconductor and Cytoscape.

Registration cost: $150,000.

Total cost for the 8 session of 19 to 22 hours (24 hours altogether).

Invoice is delivered if it is required.

More information and registration: https://bit.ly/2Vvx1ov