# Functional Analysis Training

### 2024

- AI use to interprete images ?
- How we do?
- What can we do?
- How accurate ?
- https://www.nature.com/articles/s41698-024-00576-z

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### Contribuitors
- Bruna Piereck
- Janick Mathys
- Mainak

### About the Course
- Title suggestion: Gene annotation and the biology behind genes
- 2 full days
- Anyone working with nucleotide (DNA,RNA) and proteine sequencing
- Beginner
-

### To be approched

#### Introduction
- OMICS
- What is gene annotation
- - How this helps understanding the biology behind the genes
- What is functional and motif analysis
- What and When we do Funct. analysis
- Diff. levels of annotations

#### Hands on activities and topics
- - Overrepresentation analysis
- GO enrichment
- What is gene ontology?
- Gprofiler (Human, mouse, rat)
- WEbgeshallt (Human, mouse, rat)
- EnrichR (Humna, mouse, rat)
- toppgene (Human, mouse, rat)
- Gene ontology (All)
- How to make it visual?
- PLAZA (For plants)
- Gene enrichment
- background (full set) vs Genes set (selected group)
- statical comparison

- Network analysis
- analysis
- vizualization
- From genes to pathways
- map genes to pathways
- topology stucture of pathway
- String
- KeGG
- Reactome
- PESCADOR
- IPA (mentioning)
- Human, Mouse, rt
- Payed (VIB4free)
- More info: Stephane Plaisance
- Expression
- DESeq2
- EdgeR
- Quantifications
- Abundance
- Quality control

- Motifs (?)
> the last might too complex for this session

- Examples
- Human/Animal example
- Plants example
- Bac. example
- Non-model organism example
- Diff conditions

> Activities online and ofline
> No command line for this training (For advanced connected with Python)

### General thoughts

- [MaxQuant](https://www.maxquant.org/)
- list of peptides
- Raw data (csv, txt)

## Functional annotation Resources

- DESeq2
- EdgeR
- Annotation
- Abundances
- Enrichment vs topology
- Enrichment Bags of genes
- Gene ontology annotation
- GO-slims
- Subset of GO (more useful information less general, less specific)
- Not everything is maintened
- REViGO
- Non redundant GO terms
- http://revigo.irb.hr/
- http://geneontology.org/

### Data that can be used
- [Previous Course e-leanring](https://elearning.bits.vib.be/courses/ngs-analysis/)
- Previous Course live sessions
- [youtube fastQC](https://youtu.be/6wADdc6IQ8o)
- [youtube galaxy filtering and trimming]( https://youtu.be/ExZY9ZxIfUc)
- [youtube mapping DNA](https://youtu.be/F4IhjKv35Mk)
- [youtube mapping RNAseq](https://youtu.be/9sM6JgBbIiE)
- bulk RNAseq training dataset
- Slides in the e-mail
- Table sheets in the e-mail
- [NCBI](https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM1275864)
- [EBI](https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-GEOD-52778#Protocols)
- [Single cell dataset markers gene symbol](https://pubmed.ncbi.nlm.nih.gov/33782623/)
- [bulk RNAseq slides](https://elearning.bits.vib.be/courses/bulk-rnaseq-analysis/)
- [wiki RNAseq analysis]( https://wiki.bits.vib.be/index.php/NGS_data_analysis#Training_3:_RNA-Seq_analysis)
- [interesting tool for cancer research](https://f1000research.com/articles/10-416)
- [Functional analysis slides](http://data.bits.vib.be/pub/trainingen/Functional/Functional.pptx )
> No longer pub, needs to log in to find it. Check later with Alex.
- [e-learning (work in progress)](https://elearning.bits.vib.be/courses/functional-analysis/)
- [wiki enrichement analysis](https://wiki.bits.vib.be/index.php/Functional_annotation_and_enrichment_analysis)

### Papers and websites consulted

- A Literature Review of Gene Function Prediction by Modeling Gene Ontology
https://www.frontiersin.org/articles/10.3389/fgene.2020.00400/full
https://doi.org/10.3389/fgene.2020.00400
- Gene Ontology knowledgebase
http://geneontology.org/ (accessed in june 2023)
- Gene enrichemnt and over-representation
- https://learn.gencore.bio.nyu.edu/rna-seq-analysis/over-representation-analysis/
- https://alexslemonade.github.io/refinebio-examples/03-rnaseq/pathway-analysis_rnaseq_01_ora.html
- http://revigo.irb.hr/
Paramtric vs non-parametric test
- https://www.ibm.com/docs/en/db2woc?topic=procedures-statistics-parametric-nonparametric

- Gene Ontology
- Searching GO
- Overrepresentation analysis
- Gene enrichment
- Pathways (Network) information
- Differences between Organism with and without reference