Merge pull request #4977 from rlibouba/update_slides_intro_genome_ann…

…otation

Add new informations: Helixer, compleasm and OMArk

topics/genome-annotation/tutorials/introduction/slides.html

@@ -154,14 +154,14 @@
 
 ---
 
-### Data Reconcilliation
+### Data Reconciliation
 
 .pull-left[
 
 - Integration of evidence and *ab initio* predictions
 - "Consensus" of multiple sources
 - Automated pipelines
-  - [**Maker**]({% link topics/genome-annotation/tutorials/annotation-with-maker-short/tutorial.md %}), **Braker**, [**Funannotate**]({% link topics/genome-annotation/tutorials/funannotate/tutorial.md %}), **Pasa**, **Prokka**, ...
+  - [**Maker**]({% link topics/genome-annotation/tutorials/annotation-with-maker-short/tutorial.md %}), **Braker**, **Braker3**, [**Funannotate**]({% link topics/genome-annotation/tutorials/funannotate/tutorial.md %}), **Pasa**, **Prokka**, ...
   - Align evidences (or use pre-aligned)
   - Run *ab initio* predictors
   - Reconciliate gene models
@@ -203,6 +203,25 @@
 
 ---
 
+### Evaluation of annotation: Compleasm
+* "A faster and more accurate reimplementation of BUSCO" 
+* Similar results as BUSCO:
+  * Found genes
+  * Fragmented genes
+  * Duplicated genes
+
+---
+
+### Evaluation of annotation: OMArk
+
+* Assign proteins to HOGs using k-mer composition
+* HOG = Hierarchical Orthologous Groups (gene families from OMA db)
+* Differences vs BUSCO:
+  * Completeness: also considers genes conserved in multiple copies
+  * Consistency: checks if (all) proteins matches the auto-detected lineage or not
+
+---
+
 ### Visualisation of Results
 
 Genome Browsers (JBrowse, UCSC, ...)
@@ -223,6 +242,7 @@
   - [RepeatMasker]({% link topics/genome-annotation/tutorials/repeatmasker/tutorial.md %})
   - RepeatModeler
   - REPET
+  - Red
 - Databases of repeated elements
   - Can be used by pipelines
   - Dfam
@@ -252,6 +272,16 @@
 
 ---
 
+### Helixer: a new and different approach
+
+#### Why is this approach so different? 
+
+- Ab-initio annotation of genes in large eukaryotic genomes
+- Based on a cross-species deep learning model
+- No need for any evidences (RNASeq, aligments, etc)
+- Uses GPUs, fast runtime (few hours max)
+---
+
 ## Manual Annotation
 
 - Recruit experts of some gene families