--- a/SeqSero2/README.md	Thu Apr 18 16:14:32 2019 -0400
+++ b/SeqSero2/README.md	Fri Jun 07 15:48:15 2019 -0400
@@ -1,42 +1,42 @@
-# SeqSero2 alpha-test version
-Salmonella serotyping from genome sequencing data
-
+# SeqSero2 v1.0.0
+Salmonella serotype prediction from genome sequencing data
 
 # Introduction 
-SeqSero2 is a pipeline for Salmonella serotype determination from raw sequencing reads or genome assemblies. This is a alpha test version. A web app will be available soon.
-
+SeqSero2 is a pipeline for Salmonella serotype prediction from raw sequencing reads or genome assemblies
 
 # Dependencies 
-SeqSero has two modes:
+SeqSero has three workflows:
 
+(A) Allele micro-assembly (default). This workflow takes raw reads as input and performs targeted assembly of serotype determinant alleles. Assembled alleles are used to predict serotype and flag potential inter-serotype contamination in sequencing data (i.e., presence of reads from multiple serotypes due to, for example, cross or carryover contamination during sequencing). 
 
-(A) k-mer based mode (default), which applies unique k-mers of serotype determinant alleles to determine Salmonella serotypes in a fast speed. Special thanks to Dr. Hendrik Den Bakker for his significant contribution to this mode, details can be found in [SeqSeroK](https://github.com/hcdenbakker/SeqSeroK) and [SalmID](https://github.com/hcdenbakker/SalmID).
+Allele micro-assembly workflow depends on:
 
-K-mer mode is a independant pipeline, it only requires:
+1. Python 3;
+
+2. [Burrows-Wheeler Aligner v0.7.12](http://sourceforge.net/projects/bio-bwa/files/);
+
+3. [Samtools v1.8](http://sourceforge.net/projects/samtools/files/samtools/);
+
+4. [NCBI BLAST v2.2.28+](https://blast.ncbi.nlm.nih.gov/Blast.cgi?PAGE_TYPE=BlastDocs&DOC_TYPE=Download);
+
+5. [SRA Toolkit v2.8.0](http://www.ncbi.nlm.nih.gov/Traces/sra/sra.cgi?cmd=show&f=software&m=software&s=software);
+
+6. [SPAdes v3.9.0](http://bioinf.spbau.ru/spades);
+
+7. [Bedtools v2.17.0](http://bedtools.readthedocs.io/en/latest/);
+
+8. [SalmID v0.11](https://github.com/hcdenbakker/SalmID).
+
+
+(B) Raw reads k-mer. This workflow takes raw reads as input and performs rapid serotype prediction based on unique k-mers of serotype determinants. 
+
+Raw reads k-mer workflow (originally SeqSeroK) depends on:
 
 1. Python 3;
 2. [SRA Toolkit](http://www.ncbi.nlm.nih.gov/Traces/sra/sra.cgi?cmd=show&f=software&m=software&s=software) (optional, just used to fastq-dump sra files);
 
 
-(B) allele based mode (if users want to extract serotype determinant alleles), which applies a hybrid approach of reads-mapping and micro-assembly.
-
-Allele mode depends on:
-
-1. Python 3; 
-
-2. [Burrows-Wheeler Aligner](http://sourceforge.net/projects/bio-bwa/files/); 
-
-3. [Samtools](http://sourceforge.net/projects/samtools/files/samtools/);
-
-4. [NCBI BLAST](https://blast.ncbi.nlm.nih.gov/Blast.cgi?PAGE_TYPE=BlastDocs&DOC_TYPE=Download);
-
-5. [SRA Toolkit](http://www.ncbi.nlm.nih.gov/Traces/sra/sra.cgi?cmd=show&f=software&m=software&s=software);
-
-6. [SPAdes](http://bioinf.spbau.ru/spades);
-
-7. [Bedtools](http://bedtools.readthedocs.io/en/latest/);
-
-8. [SalmID](https://github.com/hcdenbakker/SalmID).
+(C) Genome assembly k-mer. This workflow takes genome assemblies as input and the rest of the workflow largely overlaps with the raw reads k-mer workflow
 
 
 # Executing the code 
@@ -44,7 +44,7 @@
 
     Usage: SeqSero2_package.py 
 
-    -m <string> (which mode to apply, 'k'(kmer mode), 'a'(allele mode), default=k)
+    -m <string> (which workflow to apply, 'a'(raw reads allele micro-assembly), 'k'(raw reads and genome assembly k-mer), default=a)
 
     -t <string> (input data type, '1' for interleaved paired-end reads, '2' for separated paired-end reads, '3' for single reads, '4' for genome assembly, '5' for nanopore fasta, '6'for nanopore fastq)
 
@@ -56,23 +56,22 @@
  
     -d <string> (output directory name, if not set, the output directory would be 'SeqSero_result_'+time stamp+one random number)
 	
-	-c <flag> (if '-c' was flagged, SeqSero2 will use clean mode and only output serotyping prediction without the directory containing log files)
+	-c <flag> (if '-c' was flagged, SeqSero2 will only output serotype prediction without the directory containing log files)
 	
 
 # Examples
+Allele mode:
+
+    # Allele workflow ("-m a", default), for separated paired-end raw reads ("-t 2"), use 10 threads in mapping and assembly ("-p 10")
+    SeqSero2_package.py -p 10 -t 2 -i R1.fastq.gz R2.fastq.gz
+	
 K-mer mode:
 
-    # K-mer (default), for separated paired-end raw reads ("-t 2")
-	SeqSero2_package.py -t 2 -i R1.fastq.gz R2.fastq.gz
-	
-	# K-mer (default), for assemblies ("-t 4", assembly only predcited by K-mer mode)
-	SeqSero2_package.py -t 4 -i assembly.fasta
+    # Raw reads k-mer ("-m k"), for separated paired-end raw reads ("-t 2")
+    SeqSero2_package.py -m k -t 2 -i R1.fastq.gz R2.fastq.gz
 
-Allele mode:
-
-    # Allele mode ("-m a"), for separated paired-end raw reads ("-t 2"), use 10 threads in mapping and assembly ("-p 10")
-	SeqSero2_package.py -m a -p 10 -t 2 -i R1.fastq.gz R2.fastq.gz
-	
+    # Genome assembly k-mer ("-t 4", genome assemblies only predicted by the k-mer workflow, "-m k")
+    SeqSero2_package.py -m k -t 4 -i assembly.fasta
 	
 # Output 
 Upon executing the command, a directory named 'SeqSero_result_Time_your_run' will be created. Your result will be stored in 'Seqsero_result.txt' in that directory. And the assembled alleles can also be found in the directory if using "-m a" (allele mode).