My questions are: 

1) The basic statistics shows that my data encoding is Sanger/illumina 1.9. When I grooming my data for downstream analysis in Galaxy, is that correct I choose "Sanger" for the input FASTQ quality score type?

2) Based on the per base sequence quality, the quality scores are above 20.0 for both forward and reverse data. Do I still need to trim off my data? 

3) The result for "Per base sequence content", "Per base GC content", "sequence duplication level" are fail. What are these three results indicate? What are the solution for these problems? 

4) What the overrepresented sequence indicate? Do I need to trim off the overrepresented sequence? 

5) Based on the K-mer content, how could I analyse and justify whether this is good data or not?

6) In the reverse data FastQC  report, "per sequence GC content" seem not good. What do this indicate? 

7) How could I identify the adapter sequence in my RNA-seq data and how could could I remove?

8) After grooming data,  running FastQC on data, adapter removal, is there  any other pre-processing steps need to be done before running bowtie and top hat?  

Many Thanks in advance for your kind assistance and supports. 

Best regards

Ng Kiaw Kiaw

PhD student

RIKEN Yokohama Campus

Japan.