Mahmoud Ahmed MahShaaban

## ct_values.csv

          
            group
            GOI
            REF

            
              control
              32.37
              16.05

            
              control
              31.76
              15.1

            
              control
              31.8
              15.76

            
              treatment
              30.1
              18.56

            
              treatment
              29.78
              15.64

            
              treatment
              29.88
              14.76

## SummarizedExperiment_DiffBindcounts
# Create a dba.count object

library("BiocParallel")
library("DiffBind")

parallel=TRUE
BPPARAM=MulticoreParam(4)

ATAC_adult_BNST<- dba(sampleSheet = "Adult_ATAC_BNST1.csv", config=data.frame(AnalysisMethod=DBA_DESEQ2, fragmentSize = 0, th=.05),peakFormat="narrow")

## test-reproduce_app.R


library(imager)

# download data
if(!file.exists('./stats.csv')) {
  download.file('https://raw.githubusercontent.com/MahShaaban/colocr/master/inst/colocr_app/stats_18.09.02_05.15.01.csv',
                destfile = './stats.csv')
}
if(!file.exists('./inputs.csv')) {

## Image0004_.jpg

      
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                MahShaaban
                / Image0004_.jpg
            
            
              Last active
              August 8, 2018 07:49
            
              
                A simple script to show functionality of the colocr package
              
          
## draw_proteins.R
# load required libraries
library(tidyverse)

# load topology data and add ymin and ymax
thik1 <- read_csv('thik_features.csv')
thik1 <- thik1 %>%
  mutate(ymin = as.numeric(as.factor(protein)) -.2,
         ymax = as.numeric(as.factor(protein)) + .2)

# generate and save the figure

## CTFT_helper.R
#' Download Cancer Transcription Factor Targets data
#'
#' Download a coma separated file of Cistrome Cancer Transcription Factor Targets
#'
#' @param tf A character string of a transcription factor
#' @param file_type A character string of two options; 'cor' correlation to genes or 'rp' regulatory potential to genes
#' @param all A logical to whether to get only data for target genes or all genes
#' @param dir A character string for the directory to download data to
#'
#' @return A csv file

## TCGA_helpers.R
#' Merge TCGA data
#'
#' Merge data.frames of TCGA data into one tidy table
#'
#' @param study_data genetic profiles of a TCGA study
#'
#' @return A tidy data.frame
#'
#' @export
study_merge <- function(study_data) {
group	GOI	REF
control	32.37	16.05
control	31.76	15.1
control	31.8	15.76
treatment	30.1	18.56
treatment	29.78	15.64
treatment	29.88	14.76
	# Create a dba.count object

	library("BiocParallel")
	library("DiffBind")

	parallel=TRUE
	BPPARAM=MulticoreParam(4)

	ATAC_adult_BNST<- dba(sampleSheet = "Adult_ATAC_BNST1.csv", config=data.frame(AnalysisMethod=DBA_DESEQ2, fragmentSize = 0, th=.05),peakFormat="narrow")


	library(imager)

	# download data
	if(!file.exists('./stats.csv')) {
	download.file('https://raw.githubusercontent.com/MahShaaban/colocr/master/inst/colocr_app/stats_18.09.02_05.15.01.csv',
	destfile = './stats.csv')
	}
	if(!file.exists('./inputs.csv')) {
	# load required libraries
	library(tidyverse)

	# load topology data and add ymin and ymax
	thik1 <- read_csv('thik_features.csv')
	thik1 <- thik1 %>%
	mutate(ymin = as.numeric(as.factor(protein)) -.2,
	ymax = as.numeric(as.factor(protein)) + .2)

	# generate and save the figure
	#' Download Cancer Transcription Factor Targets data
	#'
	#' Download a coma separated file of Cistrome Cancer Transcription Factor Targets
	#'
	#' @param tf A character string of a transcription factor
	#' @param file_type A character string of two options; 'cor' correlation to genes or 'rp' regulatory potential to genes
	#' @param all A logical to whether to get only data for target genes or all genes
	#' @param dir A character string for the directory to download data to
	#'
	#' @return A csv file
	#' Merge TCGA data
	#'
	#' Merge data.frames of TCGA data into one tidy table
	#'
	#' @param study_data genetic profiles of a TCGA study
	#'
	#' @return A tidy data.frame
	#'
	#' @export
	study_merge <- function(study_data) {