Presenting Results Laura Biggins v1.0 1

2 I have my results in a table… what next? Plot everything?

Artefacts 3 Artefacts in the data can be caused by a whole myriad of reasons during any stage from library preparation to the final step of the analysis where the gene lists are produced. RNA-seq – transcript length, expression level Ribosomal, cytoskeleton, extracellular, secreted multi-mapping reads – multi vs single ribosomal, translation Bisulphite – CpG density GC content – low and high GC fragments are underrepresented in libraries Location, average copy number Starting population of cells – remember to include background Completely random genes….

Differential power RNA-seq – transcript length, expression level Bisulphite – CpG density Non-random distribution – CpG density 4

Mapping – multi-mapping – genome Splice variants – Analysis at transcript vs gene level 5

Copy number variation 6

Categories to be wary of ribosomal cytoskeleton extracellular secreted translation glycoprotein 7

Beware… 8 GC < 0.35

9 GC > 0.6

10 All genes on chr 2, 8, 13

11 No of transcripts > 4 Random sets of 1000 genes put through DAVID

Artefacts – checking your gene list 12 Make sure background is appropriate Be suspicious of some ontology categories – Ribosomal, cytoskeleton, extracellular, secreted, translation gene_screen – Shiny app to check for obvious differences in target genes compared to background population

What next? 13

Figure examples 14

Figure examples 15

GO graph 16 Genes are often annotated with many functions

Displaying Results Interpreting and exploring results How can the results be displayed so that I can interpret and explore them most easily? – Understanding the functional terms (incl GO hierarchy) – Finding relevant information amongst the masses ( GOslim, redundant terms, clustering) Presenting results How should I present my results? What information should I include? 17

Interpreting and Exploring Results How can the results be displayed so that I can interpret them most easily? Understanding the functional categories – GOrilla – hierarchical map – Panther - interactive pie charts Reducing redundancy – DAVID – clusters of similar functions – REVIGO - semantic similarity – GOslims 18

GOrilla 19 cbl-gorilla.cs.technion.ac.il/

Panther 20

GOrilla 21 cbl-gorilla.cs.technion.ac.il/

Exploring Results How can the results be displayed so that I can interpret them most easily? Understanding the functional categories – Gorilla – hierarchical map – Panther - interactive pie charts Reducing redundancy – DAVID – clusters of similar functions – REVIGO - semantic similarity – GOslims 22

GOrilla 23 cbl-gorilla.cs.technion.ac.il/

Exploring results 24

Reducing redundancy 25

Reducing redundancy 26

Reducing redundancy 27

Reducing redundancy Use a clustering tool Use a GOslim – various versions available, may lose the interesting detail Select non-redundant terms yourself – be consistent – P-value filter, top x number of categories, largest categories, most enriched 28

What information should be included? 29

Figure examples 30

Figure examples 31

Figure examples 32

Summary Beware of artefacts – if something looks too good to be true it probably is…. Remember your background population Do not try and plot absolutely everything Choose a method to deal with redundant terms Think about what you’re plotting and whether it makes sense Do not be afraid of including tables 33

Exercise 2 34

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Panther plots 37