Delete README.txt

README.txt

-Title: MeRIP-Seq pipeline analysis
-Author: Christophe Bécavin, Hub Bioinformatic and Biostatistic
-28 rue du Docteur Roux, Institut Pasteur, Paris
-GitLab: https://gitlab.pasteur.fr/cbecavin/MeRIPSeq/
-
-Executable (2 versions are available one for local computing, another for slurm cluster computing)
-# For local analysis
-sh run.sh project_name
-For example: sh run.sh Liver
-# For Slurm cluster
-nohup ./runServer.sh > runServer.log 2>&1 &
-# runServer.sh should be executable
-# chmod 777 Run.sh
-
-INSTALL first all dependencies: See INSTALL.txt
-
-PARAMETERS:
-project-name   -  Name of the project
-The list of file should be in your_folder/project_name_exp_design.txt
-Your sequencing data should be in : your_folder/RNASeq_raw/
-our experiment design file should be a tab-separated table with at least 5 columns:
------------------------------------------------------------------------
-DataName	IP_dataset	Input_dataset	BioCond	Seq
-Am_ZT3_1	Am_ZT3_IP_1	Am_ZT3_Input_1	Am	1
-Am_ZT13_1	Am_ZT13_IP_1	Am_ZT13_Input_1	Am	2
-CONV_ZT3_1	CONV_ZT3_IP_1	CONV_ZT3_Input_1	CONV	1
-CONV_ZT13_4	CONV_ZT13_IP_4	CONV_ZT13_Input_4	CONV	2
------------------------------------------------------------------------
-(See example/Liver_exp_design.txt) 
-
-###################################################################################
-# PIPELINE Description:
-# Setup true or false each step of the workflow to run it or not
-# INSTALL first all dependencies: See INSTALL.txt
-#
-# 1 - setup.sh - Prepare Analysis by creating all necessary folders
-# 2 - genome.sh - Prepare genome sequence, annotation, and windows for peak detection
-# 
-# Run on every dataset:
-# WARNING - Steps 3 to 7 are run separately for each datasets.
-# WARNING - They might take a ot of time to perform, so they can be parallelized on a cluster.
-# 3 - Trimming, mapping, BAM file filtering and quality control, And WIG calculation for peak detection
-# 4 - Calculate SeqDepth for peak detection techniques
-# 5 - HTSeq - Count number of reads per genes
-# 6 - coverage_window.py - Count number of reads per window
-# 7 - peak_detection.py - Run Fisher, POI,and RPMF peak detection techniques
-# 7 - MACS2 - Run MACS2 peak detection
-#
-# Run only one time per project_name 
-# 8 - MultiQC for quality control
-# 9 - finalize peak detection by filtering out "bad" peaks
-# 10 - (Optionnal) Annotate all peaks from all different techniques
-# 11 - Regroup peaks from all the detection techniques, annotate them, find overlap position with genes and referent MeRIP-Seq, CLIPSeq and TREW
-#
-# Run on every dataset:
-# 12 - HTSeq - Count number of reads in each methylation sites detected
-#
-# Run only one time per project_name 
-# 13 - Perform differential methylation sites analysis in R
-#
-#
-###################################################################################