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						Release History 
V1.2.1: minor manual corrections on Nov/30/2012 (SVN Revision 452) 


V1.2: some names change based on R naming convention on Nov/16/2012 (SVN Revision 441) 
elispot(datafile, fileformat = "", resultfile="", normalization.scale=10^6, nzero.rule = 2, plot.fileformat="eps", plot.overviewfile="", 
plot.summaryfile ="", plot.subjectfile="", plot.rawfile="", rplots=TRUE)

Bug Fixes:	
1, changed function name from elispot_est() to elispot()
2, changed arguments names based on R naming convention, normalization_scale -> normalization.scale; zero_num ->nzero.rule; plot_fileformat->plot.fileformat;plot_overview_filename->plot.overviewfile;
   plot_summary_filename ->plot.summaryfile; plot_subject_filename->plot.subjectfile; plot_raw_filename->plot.rawfile
3, changed default output names, data_file_estimates.csv -> data_file_output.csv  
4, improved manual more understandable for lab people  
5, improved GenePattern parameter names and descriptions with updated information  
6, changed GenePattern Module Category and Module name to "LDA Data Processing Tools" -> "ELISpot Data Processing"

V1.1: some new features and bug fixes on Nov/02/2012 (SVN Revision 425) 

R function interface:
elispot_est(datafile, fileformat = "", resultfile="", normalization_scale=10^6, zero_num = 2, plot_fileformat="eps", plot_overview_filename="", 
plot_summary_filename ="", plot_subject_filename="", plot_raw_filename="", rplots=TRUE)

Default output files:
1, data_file_estimates.csv
2, data_file_overview.eps
3, data_file_summary.eps
4, data_file_subject.eps
5, data_file_raw.eps

New Features:
1, New argument, zero_num, default 2, the number of first zeros rule to judge estimate as zero. For example, if one sample first two highest dilution spots counts are zero, the estimate is zero regardless of the rest of spots count.  
2, New argument, rplots, default TRUE, turn on or off R windows device
3, New argument, plot_raw_filename, default <datafile_base>_raw.<datafile_extension>, the experiment raw data plots output file, which has each plot for individual sample against different dilution levels
4, New output plot file for raw experiment data
5, Produced all kinds of plots for non-BLIS data as well  
6, Added normalization scale suffix on Y axis label for all estimates plots except raw plots, such as "/1000000 cells"
7, Added release history document
8, Added user manual document 

Bug Fixes:						
1, Removed all spot estimates columns' name prefix "Well Value." for BLIS data in output file according to Jean's suggestion.   	
2, Sorted x coordinates into ascending order before plot
3, Removed GenePattern module unexpected Rplots.pdf file, which is R window plots, by new rplots argument   
4, Changed some default output files' name, such as "_estimates" instead of "_results" and "_overview" instead of "_all" 
5, Changed the plot layout to 4 columns and 4 rows from 5 columns and 4 rows to make the plot a little bigger 
6, Changed the thumb view of plots to portrait vertical orientation instead of landscape horiental orientation, such as overview, subjects, and raw plots  
7, Added more validation rules for id, time and dilution columns  	
8, Updated some error messages more descriptive	
9, Updated GenePattern GUI input fields with the latest chanegs and more descriptive message for each field									
		

		
V1.0: initial release on Oct/19/2012 (SVN Revision 404)

R function interface:
elispot_est = function(datafile, resultfile="", fileformat = "", normalization_scale=10^6, plot_filetype="eps", plot_all_filename="", 
plot_summary_filename ="", plot_subject_filename="")

Default output files:
1, data_file_results.csv
2, data_file_all.eps
3, data_file_summary.eps
4, data_file_subject.eps

New Features:
1, Input data file with several formats, such as CSV, TAB, and TSV 
2, Visualize BLIS dataset estimate results with three types of plots, all, summary and subject.    
3, Automatically recognize id, time, spot count columns by predefined makers 
4, Fully customized parameters with default values  
5, Estimate against BLIS datasets and other generic datasets
6, Two automated data QA processing , first two dilutions rule and first three zero rule
7, Two deliverables, R package and GenePattern module 
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