Skip to content

jyyulab/NetBID

Folders and files

NameName
Last commit message
Last commit date

Latest commit

author
Dong
Aug 9, 2019
24c362c · Aug 9, 2019

History

79 Commits
Aug 9, 2019
Jul 30, 2019
Aug 7, 2019
Aug 9, 2019
Aug 7, 2019
Feb 19, 2019
Aug 7, 2019
Feb 19, 2019
Aug 9, 2019
Aug 9, 2019
Aug 9, 2019
Aug 9, 2019

Repository files navigation

NetBID2

data-drivern Network-based Bayesian Inference of Drivers, Version II

Version 0.1.2 Update Notes:

  1. Create two "lazy mode" functions, NetBID.lazyMode.DriverVisualization(),NetBID.lazyMode.DriverEstimation()

  2. Add warning message for all functions

  3. Let color code set by user-defined, with two options: use_color,pre_define passed to get.class.color(). The modified functions are: draw.2D(), draw.2D.interactive(), draw.2D.text(), draw.3D(), draw.2D.ellipse(), draw.eset.QC(), draw.pca.keans(), draw.umap.kmeans(), draw.heatmap(), draw.categoryValue(),

  4. Add package information in calling functions to avoid possible conflict of function names

  5. Re-write the cal.Activity(), add in Matrix Cross Products, which will accelerate calculation time but it is memory consuming. memory_constrain option could be set.

  6. Modify the draw.eset.QC(), add correlation plot. Modify draw.network.QC(), add html_info_limit.

  7. Add draw.2D.interactive(), and add option "2D.interactive" to draw.pca.kmeans(), draw.umap.kmeans()

  8. Add functions to judge abnormal values.

  9. modify option name from network --> target_list in generate.masterTable()

  10. add option geneSymbol_column for SJAracne.prepare()

  11. rebuild on R 3.6.0

Install

remote install (not available yet)

library(devtools)
library(BiocManager)
# set repos, for R version 3.6.0, Bioconductor version 3.9
local({
  r <- getOption("repos")
  r["CRAN"] <- "https://cran.rstudio.com/"
  r["BioCsoft"] <- "https://bioconductor.org/packages/3.9/bioc"
  r["BioCann"] <- "https://bioconductor.org/packages/3.9/data/annotation"
  r["BioCexp"] <- "https://bioconductor.org/packages/3.9/data/experiment"
  options(repos = r)
})

devtools::install_github("jyyulab/NetBID-dev",ref='master',dependencies='Depends') 

or download the release version from https://github.com/jyyulab/NetBID-dev/releases/download/0.1.2/NetBID2_0.1.2.tar.gz

local install

pull the repos from github and install locally:

devtools::install(pkg='.',dependencies=TRUE) ## Install the package with dependencies.
devtools::install_deps(pkg = ".", dependencies = TRUE) ## Install package dependencies if needed.

download the directory to your workspace and then run:

devtools::install_local('NetBID2_0.1.2.tar.gz') ## 

Manual & Tutorial

manual: NetBID2_0.1.2.pdf

tutorial: https://jyyulab.github.io/NetBID-dev/

Demo

in demo_scripts/ directory

demo scripts for network generation

pipeline_network_demo1.R

  • Step1: load in gene expression datasets for network construction (exp-load)
  • Step2: normalization for the exp dataset (exp-QC)
  • Step3: check sample cluster info, optional (exp-cluster)
  • Step4: prepare SJARACNE (sjaracne-prep)

demo scripts for network-based analysis

pipeline_analysis_demo1.R

  • Step1: load in gene expression datasets for analysis (exp-load,exp-cluster,exp-QC)
  • Step2: activity calculation (act-prep,act-get)
  • Step3: get DE/DA (act-DA)
  • Step4: generate master table (ms-tab)

demo scripts for following analysis, mainly focus on visualization

analysis_and_plot_demo1.R

Part I: More details about the top drivers

QI.1: How to get the top drivers with significant differential activity (DA) in the comparison between G4 vs. other subtypes ?

QI.2: How to interpret the significance of top DA drivers ?

QI.3: What is the expression/activity pattern of these top DA drivers across sample subtypes?

QI.4: What are the biological functions of these top DA drivers ?

QI.5: What are the biological functions of the target genes of these top DA drivers ?

Part II: More details about the selected driver

QII.1: How to interpret the significance of the selected driver ?

QII.2: How to visualize the network structure of the selected driver ?

QII.3: What is the expression/activity of this selected driver across subtypes of sample ?

QII.4: What are the functions of the target genes of this selected driver ?

Part III: Other analyses NetBID2 can do

QIII.1: What are the activities of the curated gene sets across all samples ?

QIII.2: How to find drivers share significantly overlapped target genes ?

Q&A: How to modify the figure size created by draw. functions ?