Hi, this could be the general question regarding differential gene expression analysis.

Method 1: Mapping with STAR/HISAT2, counting the reads with HTSEQ, then DSEQ2.

Method 2: Count without alignment with Salmon and DESEQ2.

I usually do with the traditional method 1. But when I am comparing the two methods, getting about more than 60 percent differentially expressed genes? Did anyone experience that, or Did anyone do the same as I? What could be the potential reason for this difference?

You are performing DE across the same samples?

There are a number of differences, hence the development of methods like RSEM, kallisto, and Salmon, but I think most of all you would expect genes in gene families (with sequence homology) to be "up-regulated" in methods that don't throw out multi-mapping reads but proportionally assign them.

HTSEq is way less smart about dealing with ambiguously aligning reads than salmon. I'd believe salmon. If you want to stick with your STAR alignment, you could use RSEM; that program is smart about dealing with ambiguous reads. You just have to configure STAR to export a transcripome-based sam file.