...

Please note that the normalization method used by Partek Genomics Suite is Reads Per Kilobase per Million mapped reads (RPKM) (Mortazavi et al. 2008). In brief, this normalization method counts total reads in a sample, divides by one million to create a per million scaling factor for each sample; then divides the read counts for the feature (exon, transcript, or gene) by the per million scaling factor to normalize for sequencing depth and give a reads per million value; and finally divides reads per million values by the length of the feature (exon, transcript, or gene) in kilobases to normalize for feature size. 

...

• Select OK to perform the RNA-seq Seq quantification 

Reads will now be assigned to individual transcripts of a gene based on the Expectation/Maximization (E/M) algorithm (Xing, et al. 2006). In Partek Genomics Suite software, the E/M algorithm is modified to accept paired-end reads, junction aligned reads, and multiple aligned reads if these are present in your data. For a detailed description of the E/M algorithm, refer to the RNA-Seq white paper (Help > On-line Tutorials > White Papers). Several spreadsheets containing the analyzed results will be generated. Progress bars in the lower left-hand corner RNA-seq Seq Quantification window and the main window will update as the data is analyzed. 

...

The contents of this spreadsheet are explained in more detail in a later section of the tutorial - ___ Detecting Unexplained Regions. 

...