I was analysing a bad sequencing run of some RNA data using FastQC, I supplied it RNA-STAR-aligned bam files (and the human reference). The output of MultiQC had many more "unique reads" in the sequence counts table than there were reads in the FastQ files that were fed to RNA-STAR.
At first, I realized that all the FastQC stats were about "mappings", not reads (as they were labeled), but "unique mappings" doesn't seem to make sense either, because even if I consider the possibility that segments of reads were mapping in different places, the numbers don't make sense. Here is the worst case:
- Max read length after trimming: 47 bases
- Number of reads in the original FastQ file that went into STAR: 59M
Bam Stat Table Numbers:
- Total records: 391 million
- Unique mappings: 3.1 million
- Non-primary Hits: 335 million
FastQC Sequence Counts Bar graph:
- "Unique reads": 185 million
- "Duplicate reads": 206 million
While I found documentation stating that you can run FastQC on bam files, there were no caveats I could find about it needing to be unmapped reads.
Can anyone explain precisely why there can be 185 million "unique reads" when bam stats says there were 3 million unique mappings and the number of reads is 59M?