Tweet
After running BBRepair the log file states: "Changed from ASCII-33 to ASCII-64 on input quality 97 for base C while prescanning." It does this for base scores 66, 95, and 98. I would like to run the files through quality trimming, but am now unsure how the quality scores are encoded (sanger, illumina, etc). Prior to BBRepair, some files had sanger scores, and other had illumina. Any help would be greatly appreciated.
-
-
If the encoding was detected correctly, or if you add the flag "changequality=f", the output will retain the same encoding as the input. It's always best to tell it what the encoding is, though, because it is not possible to detect the quality score encoding with 100% accuracy. You can specify encoding with these flags:
qin=64 qout=33
That will force the input to be treated as ASCII-64 (old Illumina) and the output will be ASCII-33 (Sanger). It's normally easiest to work with data when all sets have the same encoding... -
Thank you for your quick response. Even though the log file says the quality encoding changes, when I check the file's quality encoding with testformat.sh in bbmap (from your comment here https://www.biostars.org/p/63225/), the output states that the file is in its original encoding. I was hoping you could clarify whether repair.sh permanently or temporarily changes quality encoding.
Thank you!!Last edited by gstone; 02-27-2017, 08:13 PM.Comment
-
Sorry, I guess the message is unclear. When it says this:
"Changed from ASCII-33 to ASCII-64 on input quality 97 for base C while prescanning."
That means it started with the assumption that your data is in ASCII-33, but examined the file, and decided the input was ASCII-64. So, it processed the file assuming the data was ASCII-64. In that case, it does not change the data at all - what changes is the assumption about how to interpret the data. In other words, your data is unchanged.Comment
-
Great, thank you so much for the clarification!Comment
-
If your data is in phred+64 format (only possible if it is pretty old) then remember to use qin=64 option with other bbtools.Comment
-
Genomics studies in neuroscience face a special challenge due to the brain’s complexity and scarcity of samples. Mapping changes in cell type and state using conventional next-generation sequencing methods remains challenging. Advances in technologies like single-cell sequencing, spatial transcriptomics, and long-read sequencing have opened the door to deeper studies of the brain and diseases like Alzheimer’s, amyotrophic lateral sclerosis (ALS), and schizophrenia.
...07-09-2026, 11:10 AM -
Cancer survival rates have significantly increased in the last few decades in the United States, reaching a combined 70% 5-year survival rate by 2021. Behind this number, there are years of research to find new therapies, drug targets, and early detection methods. But there is one core challenge that keeps slowing down these advances, and it’s about drug resistance.
There is no single reason why many patients don’t respond to treatment as expected. Cancer is...07-08-2026, 05:17 AM -
Love this - good data definitely starts from good input, and poor input can only give relatively poor data. I particularly like the mention of Nanodrop/absorbance based methods for quantification. It's such a toss up if you'll get an accurate reading or what amounts to a randomly generated number, and a lot of library/sequencing related issues can be traced back to poor quant.07-01-2026, 11:43 AM
Comment