Exogean: an expert gene annotation framework based on directed acyclic coloured multigraphs

 

ENCODE Gene Prediction Workshop - EGASP/2005

Sarah Djebali, Franck Delaplace, Hugues Roest Crollius

• Human experts generate reference gene annotations automating human expertise could provide highly specific gene models

• What do human experts do? Human experts combine biological objects using heuristic rules Both biological objects and heuristic rules evolve with time

Human experts generate high quality gene annotations

• Exogean is a generic framework based on directed acyclic coloured multigraphs (DACMs) made to allow the integration of any set of heuristic rules to any set of resources

• In Exogean DACMs: Nodes are biological objects (protein or mRNA alignments, …etc) Multiple edges between nodes are relations between objects

• In terms of DACMs the human expert annotation protocolcorresponds to building, reading and reducing DACMs

Exogean: a highly flexible method that automates human expertise

Exogean main steps

Filter

CDS Identification Filter output

InformationCollection

- Blat- Spidey- Blast… etc

SingleMolecule Clustering

Single Type Multi Molecule Clustering

Multi Type Multi Molecule Clustering

Exogean core: DACM expert annotation

Protein and mRNA alignments called HSPs

Final gene models with multiple transcripts

Reduction Reduction Reduction

DACM1 DACM2 DACM3

h1 h2 h3 h4rm1

h5 h6rm2

h7 h8 h9rm3

h10 h11 h12 h13pm1

h14 h15 h16pm2

h17 h18pm3

Example: several mRNAs and proteins have been aligned to a specific locus

• rmi = mRNA molecule• pmj= proteinmolecule• hk= mRNA or protein HSP

Building and reducing DACM1 = the Single Molecule Clustering

mRNA,protein HSPs

DACM1building +reduction

Level3 transcript models

DACM2building +reduction

DACM3building +reduction

Level2 transcript models

Level1 transcript models

DACM expert annotation

Each DACM reduction producesmore complexe transcript models

M2

M1

DACM3 reduction produces final transcript models

Mi = final multi type multi molecule transcript model in which Exogean searches for a CDS

1 3

1

1

1 223

223 2

Evaluation method

Method_X

HAVANA

FNTPTP

FNFN

FP FP

%504

2

FPTP

TPSp

%405

2

FNTP

TPSn

3

2

2

FN

FP

TP

Specificity on the 44 ENCODE regions

0

10

20

30

40

50

60

70

80

90

100

Exogean Aceview Augustus Ensembl Paraigon+n-scan

Exonhunter

Sp

ecif

icit

y exon overlap

exon exact

CDS overlap

CDS exact

Sensitivity on the 44 ENCODE regions

0

10

20

30

40

50

60

70

80

90

100

Aceview Exogean Augustus Ensembl Exonhunter Paraigon+n-scan

Sen

siti

vity

exon overlap

exon exact

CDS overlap

CDS exact

Evaluation method

TP = True Positive : each HAVANA CDS matched exactly by at least one CDS from method_X is counted as TP

FP = False Positive : a virtual HAVANA CDS is defined as a method_XCDS that does not match exactly a HAVANA CDS and is counted as FP

FN = False Negative : each HAVANA CDS that is not matched exactly by at least one method_X CDS is counted as FN

FPTP

TPSp

FNTP

TPSn

h1 h2 h3 h4r1

h5 h6r2

h7 h8 h9r3

h10 h11p1h12 h13p2

h14h15 h16p3

h17 h18p4

DACM1 reduction produces level1 transcript models

• ri = mRNA level1 transcript model• pj= protein level1 transcript model

Building and reducing DACM2 = the Single Type Multi Molecule Clustering

DACM2 reduction produces level2 transcript models

• Ri = mRNA level2 transcript model• Pj = protein level2 transcript model

R1

(r1,r3)2 21 1 1

R2

(r2,r3)21 1 1

P2

(p2)1 1

P3

(p4)1 1

P1

(p1,p3)21 1 1

Building and reducing DACM3 = the Multi Type Multi Molecule Clustering