Projets autour de l'Hi-C

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)
p. 3

The Hi-C experiment (taken from SF’s slides)
p. 4

The Hi-C matrix (taken from SF’s slides)
p. 5

Outline
Clustering based on Hi-C matrices
Differential analysis of Hi-C matrices
Work in progress
p. 6

Are we able to partition a chromosome into densely connected contiguous
elements? ⇔ clustering of the chromosome based on Hi-C matrix similarity
p. 7

▶ 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)
p. 7

R package adjclust
p. 8

Outline
Work in progress
p. 9

Pig3D genome project (taken from SF’s slides)
[Marti-Marimon et al., 2018]
p. 10

Problem of Hi-C differential analysis approaches
Problem of Hi-C differential analysis approaches:
p. 11

A new differential analysis method: treediff (taken from SF’s
slides)
p. 12

A new differential analysis method: treediff
τ1 τ2
dwPD(τ1, τ2) = 2 ×
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x1,9(τ1)
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x3,8(τ1)
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x1,9(τ2)
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x3,8(τ2)
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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)
p. 14

Outline
Work in progress
p. 15

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
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.
p. 16

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