Take a look at these links and get a hang of it. You can also see this. Another thing is you have to convert sam to bam and for each samples use featurecounts to extract the raw read counts and then take this matrix of rew read counts for all the sample and feed them in DESeq2 and run the differential expression analysis ( obviously you have to make your custom design and also choose the normalization method that best fits for your data).

sam ->bam-> featureCounts on all bam files->obtain countmatrix data file -> DESeq2 -> Perform DEA

Hi katerina192,

When you have sam file, firstly you should get the count data. For a beginner, please make use of Trinity pipeline which has in built scripts to count the data from sam/bam files and find the diff expressed genes using DESeq2 and other tools. It has extensive manual which is quite easy to follow as a beginner. there is mailing list where you could post and get help immediately.

https://github.com/trinityrnaseq/trinityrnaseq/wiki/Post-Transcriptome-Assembly-Downstream-Analyses

https://github.com/trinityrnaseq/trinityrnaseq/wiki/Trinity-Transcript-Quantification

https://github.com/trinityrnaseq/trinityrnaseq/wiki/Trinity-Differential-Expression