Tweet
Does anyone have a trick or script to convert collapsed reads back to raw fasta reads? I need them in raw fasta to be able to map with bowtie.
a perl script maybe will do it?
a perl script maybe will do it?
-
-
What are collapsed reads? -
>1-1377297
tgtaaacatcctcgactggaagct
>2-783040
tttggcaatggtagaactcacact
>3-461345
tagcttatcagactgatgttgacaComment
-
This looks like fasta to me, I'm still not sure what "collapsed reads" mean.Originally posted by Palgrave View Post
You can add "-f" to your bowtie command for alignment of reads in fasta format.Comment
-
I'm guessing that what you have are miRNA reads, with all identical sequences "collapsed" and your definition line means >[miRNA-id]-[counts].Originally posted by Palgrave View Post
I'm also guessing that you are asking how to create a file that contains 1,377,297 copies of miRNA-1, 783,040 copies of miRNA-2, etc.
Is that what you want to do? If it is, please don't. It would be a waste of time and cpu cycles to have Bowtie map exactly the same sequence 1,377,297 times. Map each unique sequence just once and then account for sequence abundance in your downstream analysis.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