Projets autour de l'Hi-C

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Kfé SaAB du 7 avril 2023 INRAE Centre Occitanie Toulouse

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Projets autour de l’Hi-C
Nathalie Vialaneix
nathalie.vialaneix@inrae.fr
http://www.nathalievialaneix.eu
Réunion SaAB
7 avril 2023

3D organization of the chromatine (taken from SF’s slides)
Réunion SAaB : stratégie à 2/3 ans
7 avril 2023 / Nathalie Vialaneix
p. 2

Context: from 3D to function (taken from SF’s slides)
Réunion SAaB : stratégie à 2/3 ans
7 avril 2023 / Nathalie Vialaneix
p. 3

The Hi-C experiment (taken from SF’s slides)
Réunion SAaB : stratégie à 2/3 ans
7 avril 2023 / Nathalie Vialaneix
p. 4

The Hi-C matrix (taken from SF’s slides)
Réunion SAaB : stratégie à 2/3 ans
7 avril 2023 / Nathalie Vialaneix
p. 5

Outline
Clustering based on Hi-C matrices
Differential analysis of Hi-C matrices
Work in progress
Réunion SAaB : stratégie à 2/3 ans
7 avril 2023 / Nathalie Vialaneix
p. 6

Clustering based on Hi-C matrices
Are we able to partition a chromosome into densely connected contiguous
elements? ⇔ clustering of the chromosome based on Hi-C matrix similarity
Réunion SAaB : stratégie à 2/3 ans
7 avril 2023 / Nathalie Vialaneix
p. 7

Pig3D genome project (taken from SF’s slides)
[Marti-Marimon et al., 2018]
Réunion SAaB : stratégie à 2/3 ans
7 avril 2023 / Nathalie Vialaneix
p. 10

Problem of Hi-C differential analysis approaches
Problem of Hi-C differential analysis approaches:
Réunion SAaB : stratégie à 2/3 ans
7 avril 2023 / Nathalie Vialaneix
p. 11

A new differential analysis method: treediff (taken from SF’s
slides)
Réunion SAaB : stratégie à 2/3 ans
7 avril 2023 / Nathalie Vialaneix
p. 12

A new differential analysis method: treediff
τ1 τ2
dwPD(τ1, τ2) = 2 ×









.
.
.
x1,9(τ1)
.
.
.
x3,8(τ1)
.
.
.









−









.
.
.
x1,9(τ2)
.
.
.
x3,8(τ2)
.
.
.









2
Réunion SAaB : stratégie à 2/3 ans
7 avril 2023 / Nathalie Vialaneix
p. 13

A new differential analysis method: treediff
▶ Article issu de la thèse Nathanaël [Neuvial et al., 2022] (en révision)
▶ R package treediff (stage Gwendaëlle)
Réunion SAaB : stratégie à 2/3 ans
7 avril 2023 / Nathalie Vialaneix
p. 14

Current and future work on Hi-C and Hi-C differential analysis
▶ Chrocodiff: review of the different methods/tools for the differential analysis of
Hi-C data
▶ DG PhD thesis: minimum and maximum differential subtrees (challenges: multiple
testing control in a hierarchical setting, very large computational problems, ...)
▶ ChrocoNet: network DigitBio
Réunion SAaB : stratégie à 2/3 ans
7 avril 2023 / Nathalie Vialaneix
p. 16

References
Ambroise, C., Dehman, A., Neuvial, P., Rigaill, G., and Vialaneix, N. (2019).
Adjacency-constrained hierarchical clustering of a band similarity matrix with application to genomics.
Algorithms for Molecular Biology, 14:22.
Marti-Marimon, M., Vialaneix, N., Voillet, V., Yerle-Bouissou, M., Lahbib-Mansais, Y., and Liaubet, L. (2018).
A new approach of gene co-expression network inference reveals significant biological processes involved in porcine muscle development in late
gestation.
Scientific Report, 8:10150.
Neuvial, P., Randriamihamison, N., Chavent, M., Foissac, S., and Vialaneix, N. (2022).
Testing differences in structure between families of trees.
Preprint submitted for publication.
Randriamihamison, N., Vialaneix, N., and Neuvial, P. (2021).
Applicability and interpretability of Ward’s hierarchical agglomerative clustering with or without contiguity constraints.
Journal of Classification, 38:363–389.
Réunion SAaB : stratégie à 2/3 ans
7 avril 2023 / Nathalie Vialaneix
p. 16

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Projets autour de l'Hi-C

1. Projets autour de l’Hi-C Nathalie Vialaneix nathalie.vialaneix@inrae.fr http://www.nathalievialaneix.eu Réunion SaAB 7 avril 2023

2. 3D organization of the chromatine (taken from SF’s slides) Réunion SAaB : stratégie à 2/3 ans 7 avril 2023 / Nathalie Vialaneix p. 2

3. Context: from 3D to function (taken from SF’s slides) Réunion SAaB : stratégie à 2/3 ans 7 avril 2023 / Nathalie Vialaneix p. 3

4. The Hi-C experiment (taken from SF’s slides) Réunion SAaB : stratégie à 2/3 ans 7 avril 2023 / Nathalie Vialaneix p. 4

5. The Hi-C matrix (taken from SF’s slides) Réunion SAaB : stratégie à 2/3 ans 7 avril 2023 / Nathalie Vialaneix p. 5

6. Outline Clustering based on Hi-C matrices Differential analysis of Hi-C matrices Work in progress Réunion SAaB : stratégie à 2/3 ans 7 avril 2023 / Nathalie Vialaneix p. 6

7. Clustering based on Hi-C matrices Are we able to partition a chromosome into densely connected contiguous elements? ⇔ clustering of the chromosome based on Hi-C matrix similarity Réunion SAaB : stratégie à 2/3 ans 7 avril 2023 / Nathalie Vialaneix p. 7

8. Clustering based on Hi-C matrices Are we able to partition a chromosome into densely connected contiguous elements? ⇔ clustering of the chromosome based on Hi-C matrix similarity ▶ Projet CNRS SCALES (with P. Neuvial & S. Foissac). Thèse INRAE/Inria Nathanaël Randriamihamison (also with M. Chavent) ▶ Developped a constrained HC method based on similarity / kernel with improved efficiency for genomic data [Ambroise et al., 2019] (band sparsity assumption, min-heap, linear in p) ▶ Study statistical properties of the method [Randriamihamison et al., 2021] (reversals) Réunion SAaB : stratégie à 2/3 ans 7 avril 2023 / Nathalie Vialaneix p. 7

9. Clustering based on Hi-C matrices Are we able to partition a chromosome into densely connected contiguous elements? ⇔ clustering of the chromosome based on Hi-C matrix similarity R package adjclust Réunion SAaB : stratégie à 2/3 ans 7 avril 2023 / Nathalie Vialaneix p. 8

10. Outline Clustering based on Hi-C matrices Differential analysis of Hi-C matrices Work in progress Réunion SAaB : stratégie à 2/3 ans 7 avril 2023 / Nathalie Vialaneix p. 9

11. Pig3D genome project (taken from SF’s slides) [Marti-Marimon et al., 2018] Réunion SAaB : stratégie à 2/3 ans 7 avril 2023 / Nathalie Vialaneix p. 10

12. Problem of Hi-C differential analysis approaches Problem of Hi-C differential analysis approaches: Réunion SAaB : stratégie à 2/3 ans 7 avril 2023 / Nathalie Vialaneix p. 11

13. A new differential analysis method: treediff (taken from SF’s slides) Réunion SAaB : stratégie à 2/3 ans 7 avril 2023 / Nathalie Vialaneix p. 12

14. A new differential analysis method: treediff τ1 τ2 dwPD(τ1, τ2) = 2 ×          . . . x1,9(τ1) . . . x3,8(τ1) . . .          −          . . . x1,9(τ2) . . . x3,8(τ2) . . .          2 Réunion SAaB : stratégie à 2/3 ans 7 avril 2023 / Nathalie Vialaneix p. 13

15. A new differential analysis method: treediff ▶ Article issu de la thèse Nathanaël [Neuvial et al., 2022] (en révision) ▶ R package treediff (stage Gwendaëlle) Réunion SAaB : stratégie à 2/3 ans 7 avril 2023 / Nathalie Vialaneix p. 14

16. Outline Clustering based on Hi-C matrices Differential analysis of Hi-C matrices Work in progress Réunion SAaB : stratégie à 2/3 ans 7 avril 2023 / Nathalie Vialaneix p. 15

17. Current and future work on Hi-C and Hi-C differential analysis ▶ Chrocodiff: review of the different methods/tools for the differential analysis of Hi-C data ▶ DG PhD thesis: minimum and maximum differential subtrees (challenges: multiple testing control in a hierarchical setting, very large computational problems, ...) ▶ ChrocoNet: network DigitBio Réunion SAaB : stratégie à 2/3 ans 7 avril 2023 / Nathalie Vialaneix p. 16

18. References Ambroise, C., Dehman, A., Neuvial, P., Rigaill, G., and Vialaneix, N. (2019). Adjacency-constrained hierarchical clustering of a band similarity matrix with application to genomics. Algorithms for Molecular Biology, 14:22. Marti-Marimon, M., Vialaneix, N., Voillet, V., Yerle-Bouissou, M., Lahbib-Mansais, Y., and Liaubet, L. (2018). A new approach of gene co-expression network inference reveals significant biological processes involved in porcine muscle development in late gestation. Scientific Report, 8:10150. Neuvial, P., Randriamihamison, N., Chavent, M., Foissac, S., and Vialaneix, N. (2022). Testing differences in structure between families of trees. Preprint submitted for publication. Randriamihamison, N., Vialaneix, N., and Neuvial, P. (2021). Applicability and interpretability of Ward’s hierarchical agglomerative clustering with or without contiguity constraints. Journal of Classification, 38:363–389. Réunion SAaB : stratégie à 2/3 ans 7 avril 2023 / Nathalie Vialaneix p. 16

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