spell-checking README file

diff --git a/README b/README
index a8e2d9d..59872cb 100644
--- a/README
+++ b/README
@@ -98,7 +98,7 @@ RACS
  |   └── defns
  |   |   └── TT_gene.id
  |   |   └── TT_mRNA.id
- |   |   +-- OXY_gene.id
+ |   |   └── OXY_gene.id
  |   └── test
  |        └── lst
  ├── datasets
@@ -280,7 +280,7 @@ that we have included to normalize your INPUT/IP-reads.
 This script is called "normalizedORF.sh" and is located in the core subdirectory.
 The script requires three mandatory arguments:
 	1st argument: "FINAL.table.*"  file generated from the RACS' ORF pipeline
-	2nd argument: "PF-INPUT-value"  PF value correspoding to the INPUT file
+	2nd argument: "PF-INPUT-value"  PF value corresponding to the INPUT file
 	3rd argument: "PF-IP-value"  PF value corresponding to the IP file

 Please notice that arguments 2 and 3, are the actual numerical values corresponding to the PF clusters
@@ -337,12 +337,12 @@ memory utilization.

 - Downloading datasets
   We provide two scripts that will allow the user download the reference
-genomic files for Tetrahymena thermophila and Oxytrichia trifallax, as well as,
-the publicly available ChIP-seq data for the Oxytrichia trifallax.
+genomic files for Tetrahymena thermophila and Oxytricha trifallax, as well as,
+the publicly available ChIP-seq data for the Oxytricha trifallax.
 Both scripts are available in the 'datasets' directory:
 	get_GFF3-files.sh  will download the corresponding gff3 files for T.thermophila and O.trifallax.

-	get_OXYchIPseq-files.sh  will download two runs of ChIP-next gen. seq. data for Oxytrichia trifallax. Because this data is located at NCBI repositories the user should have installed the SRA toolkit tools in order to access and download this data.
+	get_OXYchIPseq-files.sh  will download two runs of ChIP-next gen. seq. data for Oxytricha trifallax. Because this data is located at NCBI repositories the user should have installed the SRA toolkit tools in order to access and download this data.

 - Comparison tools

@@ -418,8 +418,8 @@ cut-offs when your data includes wild-types or negative controls.
 The script can be found in the core directory, and is named "normalizeORG.sh".
 It requires 3 arguments:
    - 1st argument: "FINAL.table.*"  file from RACS' ORF pipeline
-   - 2nd argument: "PF-INPUT-value"  PF value correspoding to the INPUT file
-   - 3rd argument: "PF-IP-value"  PF value correspoding to the IP file
+   - 2nd argument: "PF-INPUT-value"  PF value corresponding to the INPUT file
+   - 3rd argument: "PF-IP-value"  PF value corresponding to the IP file
    - 4th argument: 'A' or 'D' (OPTIONAL), when this 4th argument is specified, an additional table is created being ordered with respect to the IP/INPUT ratio, in "A"scending or "D"ecreasing order

        PATHtoRACS/core/normalizeORF.sh  FINAL.table.XXXX  14694464  10148171
@@ -432,11 +432,11 @@ See,
 	datasets/PostProcessing_Intergenic.xlsx


-IV) Proccessing generic organisms/terms, other than Tetrahymena thermophila
+IV) Processing generic organisms/terms, other than Tetrahymena thermophila

 IV.i) Reference table manipulation
 	During the analysis and determination of ORF, the reference file for
-the given organsim is processed by selecting the appropiate terms and filters
+the given organism is processed by selecting the appropriate terms and filters
 to carve the corresponding terms.
 In the subdirectory "core/defns", we present examples of what terms and
 filters have to be specified; eg.
@@ -454,8 +454,8 @@ or, the "genes" for the Oxytricha trifallax,


 IV.ii) ORF determination
-	For analizing generic organisms and terms, we need to propagate the infromation
-passed to the "table.sh" script as explaied in the previous edamples for the analysis of
+	For analyzing generic organisms and terms, we need to propagate the information
+passed to the "table.sh" script as explained in the previous examples for the analysis of
 ORFs,

 	PATHtoRACSrepo/core/countReads.sh   data2/_1_MED1_INPUT_S25_L007_R1_001.fastq.gz  data2/_3_MED1_IP_S27_L007_R1_001.fastq.gz  T_thermophila_June2014_assembly.fasta  T_thermophila_June2014.gff3  /dev/shm/  16  PATHtoRACS/core/defns/TT_mRNA.id
@@ -468,7 +468,7 @@ Oxytricha trifallax ChIP-Seq run #1.


 IV.iii) IGR determination
-	Determining IGR for generic organism does nto requirei any special
+	Determining IGR for generic organism does not require any special
 considerations other than using the "FINAL.table.*" file generated by the RACS'
 ORF tool. Eg.

@@ -481,7 +481,7 @@ where the file "sample.input" contains the following files:


 IV.iv) Full analysis of Oxytricha trifallax
-	We describe the ste-by-step case of how to analyze the data for the Oxytricha trifallax
+	We describe the step-by-step case of how to analyze the data for the Oxytricha trifallax

 	# 1) create a directory where allocate the data
 	mkdir oxy
@@ -499,7 +499,7 @@ IV.iv) Full analysis of Oxytricha trifallax
 	# 4) determination of the IGRs
 	# 4.i) first, cd into the ORF_... directory generated by the previous step where the results from the ORF part of the RACS pipeline were placed
 	cd ORF_...
-	# 4.ii) create the "sample.input" file containing the bames of the *.fastq.gz files to be processed, eg.
+	# 4.ii) create the "sample.input" file containing the names of the *.fastq.gz files to be processed, eg.
 	ls -1 *fastq.gz-sorted.bam > sample.input
 	# 4.iii) run the IGR determination part of the RACS pipeline
 	PATHtoRACSrepo/core/intergenic/det-interGenes.sh FINAL.table.SRX483016_1-SRX483017_1 Oxytricha_trifallax_022112.gff3 interGENs_run1_OXY.csv  sample.input
@@ -521,7 +521,7 @@ does that generating some visuals comparisons.
 		source("PATHtoRACSrepo/tools/compare.R")


-	V.2-ii) Now, you have a list of functions and datasets laoded ready to
+	V.2-ii) Now, you have a list of functions and datasets loaded ready to
 be used, including some tests cases:

 		ls()
@@ -539,7 +539,7 @@ For instance, 'sampleIBD1/sampleIBD2' are ORF generated with RACS, while
 eg.
 		ibdX(sampleIBD1,macsIBD1, "comparison_ibd1.pdf")

-several static PDF plots would be generated, as well as, interavtive plots
+several static PDF plots would be generated, as well as, interactive plots
 generated using the plotly library which would be stored in HTML files.

 	V.2-iv) Alternatively, one could inspect more in detail the results
@@ -549,7 +549,7 @@ scores between the results from both programs:
         overlap.RACSvsMACS <- comparison(sampleIBD1,macsIBD1, DBG=FALSE)

 this will return a dataframe containing the scaffolds, coordinates for the
-beggining and end determined by RACS and MACS2 respectively, and an overlap
+beginning and end determined by RACS and MACS2 respectively, and an overlap
 score; ie.

         scaffold        x1      x2      y1      y2      overlap