Tweet
In a SAM file generated from Bowtie, I found one entry has '*' in the CIGAR field. What does this mean, bad alignment?
Thanks
Thanks
-
-
It means "not available" in the SAM spec. Typically, this happens when the read isn't aligned (RNAME - 3rd field - is also '*' and 0x4 is set in the FLAG field). -
Thanks, arvid.
To what extend, Bowtie sets the FLAG to 0x4 for a read, and make the CIGAR field "not abailable". What are the measure and threshold bowtie uses for setting this?
ThanksComment
-
Well, using the settings (default or your specific choices), Bowtie found no reportable alignment for that read.
It is not possible to make a general statement about this behaviour here as it depends entirely on the settings you provided bowtie with and the nature of your reads and reference. Check the bowtie manual, typically you should look at alignment and reporting modes - these and their sub-options control alignment sensitivity and reporting filters.Comment
-
Hi Arvid,
Thank you very much for the help.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.
...Yesterday, 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