Package: KBoost 1.13.0

Luis F. Iglesias-Martinez

KBoost: Inference of gene regulatory networks from gene expression data

Reconstructing gene regulatory networks and transcription factor activity is crucial to understand biological processes and holds potential for developing personalized treatment. Yet, it is still an open problem as state-of-art algorithm are often not able to handle large amounts of data. Furthermore, many of the present methods predict numerous false positives and are unable to integrate other sources of information such as previously known interactions. Here we introduce KBoost, an algorithm that uses kernel PCA regression, boosting and Bayesian model averaging for fast and accurate reconstruction of gene regulatory networks. KBoost can also use a prior network built on previously known transcription factor targets. We have benchmarked KBoost using three different datasets against other high performing algorithms. The results show that our method compares favourably to other methods across datasets.

Authors:Luis F. Iglesias-Martinez [aut, cre], Barbara de Kegel [aut], Walter Kolch [aut]

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KBoost/json (API)

# Install 'KBoost' in R:
install.packages('KBoost', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/luisiglm/kboost/issues

Datasets:
  • D4_multi_1 - Dream 4 multifactorial pertubation challenge dataset 1
  • D4_multi_2 - Dream 4 multifactorial pertubation challenge dataset 2
  • D4_multi_3 - Dream 4 multifactorial pertubation challenge dataset 3
  • D4_multi_4 - Dream 4 multifactorial pertubation challenge dataset 4
  • D4_multi_5 - Dream 4 multifactorial pertubation challenge dataset 5
  • G_D4_multi_1 - Gold Standard Dream 4 multifactorial pertubation challenge dataset 1
  • G_D4_multi_2 - Gold Standard Dream 4 multifactorial pertubation challenge dataset 2
  • G_D4_multi_3 - Gold Standard Dream 4 multifactorial pertubation challenge dataset 3
  • G_D4_multi_4 - Gold Standard Dream 4 multifactorial pertubation challenge dataset 4
  • G_D4_multi_5 - Gold Standard Dream 4 multifactorial pertubation challenge dataset 5
  • Gerstein_Prior_ENET_2 - Gene Regulatory Network from human ChIP-Seq data in Encode
  • Human_TFs - Index of human genes' Symbols, Entrez and Ensembl for K-Boost Pacakge that correspond to transcription factors.
  • IRMA_Gold - IRMA Gold Standard Network
  • irma_off - IRMA Off Dataset
  • irma_on - IRMA On Dataset

On BioConductor:KBoost-1.13.0(bioc 3.20)KBoost-1.12.0(bioc 3.19)

bioconductor-package

18 exports 0.61 score 0 dependencies 1 mentions

Last updated 2 months agofrom:ed58a71680

Exports:add_namesAUPR_AUROC_matrixd4_mfacget_prior_Gersteinget_tfs_humangrid_search_kboostirma_checkkboostKBoost_human_symbolkernel_normalkernel_pc_boostingKPCnet_dist_binnet_refinenet_summary_binRBF_Ktab_2_matrix_D4write_GRN_D4

Dependencies:

KBoost

Luis F. Iglesias-Martinez, Barbara De Kegel and Walter Kolch

Rendered fromKBoost.Rmdusingknitr::rmarkdownon Jun 30 2024.

Last update: 2021-04-01
Started: 2021-01-25

Readme and manuals

Help Manual

Help pageTopics
Function to add names to network for the user.add_names
Function to calculate the AUROC and AUPR of a known network. This function was made to test the R implementation of the KBoost Package.AUPR_AUROC_matrix
Function to obtain the AUPR and AUROC in the DREAM4 Multifactorial Challenge.d4_mfac
Dream 4 multifactorial pertubation challenge dataset 1D4_multi_1
Dream 4 multifactorial pertubation challenge dataset 2D4_multi_2
Dream 4 multifactorial pertubation challenge dataset 3D4_multi_3
Dream 4 multifactorial pertubation challenge dataset 4D4_multi_4
Dream 4 multifactorial pertubation challenge dataset 5D4_multi_5
Gold Standard Dream 4 multifactorial pertubation challenge dataset 1G_D4_multi_1
Gold Standard Dream 4 multifactorial pertubation challenge dataset 2G_D4_multi_2
Gold Standard Dream 4 multifactorial pertubation challenge dataset 3G_D4_multi_3
Gold Standard Dream 4 multifactorial pertubation challenge dataset 4G_D4_multi_4
Gold Standard Dream 4 multifactorial pertubation challenge dataset 5G_D4_multi_5
Gene Regulatory Network from human ChIP-Seq data in EncodeGerstein_Prior_ENET_2
Function to build a prior using a previously built Network on ChIP-Seq.get_prior_Gerstein
Function to automatically assign Human TFs given a list of Symbols.get_tfs_human
Function to perform a grid search and find the hyperparameters.grid_search_kboost
Index of human genes' Symbols, Entrez and Ensembl for K-Boost Pacakge that correspond to transcription factors.Human_TFs
Function to produce the AUPR and AUROC Results on the IRMA datasets.irma_check
IRMA Gold Standard NetworkIRMA_Gold
IRMA Off Datasetirma_off
IRMA On Datasetirma_on
A function to run KBoost.kboost
Function for KBoost on data from a human sample annotated with Symbol names.KBoost_human_symbol
A function to perform feature normalization in kernel space.kernel_normal
Function to perform Kernel Principal Component Boostingkernel_pc_boosting
Function to calculate the principal components of a kernel.KPC
Function to calculate the distance between nodes.net_dist_bin
Function to do a heuristic post-processing that improves accuracy. Each column is multiplied by its variance.net_refine
Function to summarize the GRN filtered with a threshold,net_summary_bin
Function to calculate the RBF Kernel of a matrix X with width g.RBF_K
Function to produce the gold standard of the DREAM4 Multifactorial Challenge in matrix format.tab_2_matrix_D4
Function to write output in DREAM4 Challenge Format.write_GRN_D4