I tried to process a RNA-Seq experiment myself, but when I upload the file in IGV and look at the coverage track, I see not an "equal distribution" of reads over the whole transcript (so roughly a plateau), but rather mountains .
My questions more precise: Maybe I cut the wrong adapters off? However, I firstly remove rRNA sequences with bowtie, this works. Or is there a parameter I have to change in my STAR command?
I downloaded the raw data from Geo: https://www.ncbi.nlm.nih.gov/sra/?term=SRA160745 More precisely here: https://trace.ncbi.nlm.nih.gov/Traces/sra/?run=SRR1630838
(If I am correct, the FASTQC report shows that the read length is between 25 and 40 nts, with apr. 50 million sequences.)
Briefly to how I processed the data:
1) I trimmed the adapters using cutadapt. I obtained the adapter sequences from the paper Gao et al. (2015) "Quantitative profiling of initiating ribosomes in vivo": "Deep sequencing. Single-stranded template was amplified by PCR by using the Phusion high-fidelity (HF) enzyme (NEB) according to the manufacturer’s instructions. The oligonucleotide primers qNTI200 (5 -CAAGCAGAAGACGGCATA- 3 ) and qNTI201 (5 -AATGATACGGCGACCACCG ACAGGTTCAGAGTTCTAC AGTCCGACG- 3 ) were used to create DNA suitable for sequencing, i.e., DNA with Illumina cluster generation sequences on each end and a sequencing primer binding site."
2) I used STAR for the alignment: STAR --genomeDir file/to/STAR_Index_Genome_100/ --alignEndsType EndToEnd --readFilesIn file.fasta --runThreadN 2 --outFilterMismatchNmax 3 --outFilterMultimapNmax 20 --chimScoreSeparation 10 --chimScoreMin 20 --chimSegmentMin 15 --outSAMattributes All --outFilterIntronMotifs RemoveNoncanonicalUnannotated --alignSJoverhangMin 500 --outFileNamePrefix /path/to/star_output/ --outReadsUnmapped Fastx --outSAMtype BAM SortedByCoordinate --quantMode GeneCounts --outWigType bedGraph read1_5p --outWigNorm RPM --outSAMstrandField intronMotif --outSAMmultNmax 1 --outMultimapperOrder Random