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![Francesco GadaletaSelect and Connect: the benefits of building networks in genetics
NETWORK
VALIDATION
GeneNetWeaver
‣ generates synthetic μA data from regulatory network
‣ several conditions (simulation of μA noise, network
perturbations, time series, generation of samples using
multifactorial equations)
‣ Golden Standard (GS)
Directed unweighted signed network, based on
transcription factor network (TFN) of E.coli [1]](https://image.slidesharecdn.com/networkgenetics-150619113724-lva1-app6891/85/Network-genetics-15-320.jpg)
Uploaded byFrancesco Gadaleta
Network genetics
Francesco Gadaleta discusses using penalized regression methods like the lasso and elastic net to select covariates and build gene networks from microarray experiments. These methods allow for variable selection and network construction while accounting for issues like multicollinearity. Gadaleta demonstrates his "Select and Connect" approach on both synthetic data from a known regulatory network as well as real gene expression data, showing it can accurately identify hub genes and network connections. He also discusses parallelizing the computations and integrating multiple networks.
![[JEEConf 2015] Lessons from Building a Modern B2C System in Scala](https://cdn.slidesharecdn.com/ss_thumbnails/yuriyguts-lessonsfrombuildingamodernb2csysteminscalav2-150526144611-lva1-app6892-thumbnail.jpg?width=640&height=640&fit=bounds)
Network genetics
- 1. Francesco GadaletaUniversity ofLiege - Montefiore Institute Select and Connect the benefits of building networks in genetics Francesco Gadaleta PhD - Montefiore Institute ULg
- 2. Francesco GadaletaSelect andConnect: the benefits of building networks in genetics • Genetics and Networks • Variable selection with penalised regression • Application to Gene Expression Profiles • Demo OUTLINE
- 3. Francesco GadaletaSelect andConnect: the benefits of building networks in genetics Given a set of microarray experiments HOW select covariates build networks ?
- 4. Francesco GadaletaSelect andConnect: the benefits of building networks in genetics EXPLAIN PREDICTOR gene interaction best SNP selection phenotype survival
- 5. Francesco GadaletaSelect andConnect: the benefits of building networks in genetics ?ASSOCIATION CORRELATION CAUSALITY A B REGULATION
- 6. Francesco GadaletaSelect andConnect: the benefits of building networks in genetics PENALISED REGRESSION least squares elastic net ridge regression fused group quadratic programming hierarchical LASSO nonlinear penalised multivariate linear regression gradient descent
- 7. Francesco GadaletaSelect andConnect: the benefits of building networks in genetics OPTIMISATION PROBLEMS IN MACHINE LEARNING Def. convex set X Def. convex function Optimisation problem
- 8. Francesco GadaletaSelect andConnect: the benefits of building networks in genetics GRADIENT Where’s the min? follow the
- 9. Francesco GadaletaSelect andConnect: the benefits of building networks in genetics local minima are also global minima fast convergence WHY CONVEXITY? Introduce gradients, subgradients and epigraphs … some proofs here gradient/coordinate descent
- 10. Francesco GadaletaSelect andConnect: the benefits of building networks in genetics OPTIMISATION METHODS FOR GRADIENT DESCENT works fine but can be slow COORDINATE DESCENT cycle through each predictor in turn compute residuals convex ANDdifferentiable convex PATHWISE COORDINATE DESCENT start with large (sparse model) apply COORDINATE DESCENT decrease (zero coordinates stay zero!)
- 11. Francesco GadaletaSelect andConnect: the benefits of building networks in genetics min penalty (sparsity) covariance matrix (association) gene matrix response
- 12. Francesco GadaletaSelect andConnect: the benefits of building networks in genetics MULTICOLLINEARITY y B C D lack of independency presence of interdependency least square regression fails approach singularity explodes
- 13. Francesco GadaletaSelect andConnect: the benefits of building networks in genetics i NETWORK CONSTRUCTION
- 14. Francesco GadaletaSelect andConnect: the benefits of building networks in genetics matrix of regression coefficients symmetric not symmetric A B A B A B
- 15. Francesco GadaletaSelect andConnect: the benefits of building networks in genetics NETWORK VALIDATION GeneNetWeaver ‣ generates synthetic μA data from regulatory network ‣ several conditions (simulation of μA noise, network perturbations, time series, generation of samples using multifactorial equations) ‣ Golden Standard (GS) Directed unweighted signed network, based on transcription factor network (TFN) of E.coli [1]
- 16. Francesco GadaletaSelect andConnect: the benefits of building networks in genetics SYNTHETIC DATA GENERATION ‣ Used no noise, multifactorial based GS networks 50 nodes with 3 regulators (TFs) 200 nodes with 10 regulators (TFs)
- 17. Francesco GadaletaSelect andConnect: the benefits of building networks in genetics SELECT AND CONNECT IN ACTION
- 18. Francesco GadaletaSelect andConnect: the benefits of building networks in genetics REAL NETWORK 200nodes 212connections
- 19. Francesco GadaletaSelect andConnect: the benefits of building networks in genetics PREDICTED NETWORK 200nodes 360connections
- 20. Francesco GadaletaSelect andConnect: the benefits of building networks in genetics DEGREE CORRELATION 86% false positives predicted hubs correctly detected
- 21. Francesco GadaletaSelect andConnect: the benefits of building networks in genetics BETWEENESS CORRELATION 83%
- 22. Francesco GadaletaSelect andConnect: the benefits of building networks in genetics LASSO is quadratic programming (polynomial) COMPUTATIONAL COMPLEXITY Time-complexity of iterative convex optimisation is tricky to analyse (it depends on a convergence criterion) :-):-( Coordinate descent requires O(np) operations :-|
- 23. Francesco GadaletaSelect andConnect: the benefits of building networks in genetics PARALLEL COMPUTATIONS (permutation tests)
- 24. Francesco GadaletaSelect andConnect: the benefits of building networks in genetics 200 genes, 400 permutations, 5 cpus 100 100100 100 as fast as 100 permutations
- 25. Francesco GadaletaSelect andConnect: the benefits of building networks in genetics 200 genes, 400 permutations, 40 cpus 100 100100 100 100 100100 100 100 100100 100 1:25 25:50 175:200 asfastas25genesand100permutations …
- 26. Francesco GadaletaSelect andConnect: the benefits of building networks in genetics NETWORK INTEGRATION
- 27. Francesco GadaletaSelect andConnect: the benefits of building networks in genetics NETWORK INTEGRATION how do we connect networks? how do we deal with diverse datasets?
- 28. Francesco GadaletaSelect andConnect: the benefits of building networks in genetics – Niels Bohr “Prediction is very difficult, especially about the future.” genes www.worldofpiggy.com @worldofpiggy francesco.gadaleta@gmail.com
- 29. Francesco GadaletaSelect andConnect: the benefits of building networks in genetics thank you. www.worldofpiggy.com @worldofpiggy francesco.gadaleta@gmail.com