Tweet
Can someone explain to me what the orientation in paired-end RNA-seq data means? Is forward/forward the standard orientation? How does this affect tophat options, just specify unstranded Rna-seq?
-
-
What protocol did you use for library preparation? Normally for ScriptSeq Illumina libraries, the forward reads would correspond to the DNA coding strand while the reverse reads would be reverse complements, -
If you are only looking for a primer on the "paired end" part have a look at this blog entry: http://www.homolog.us/blogs/blog/201...looking-reads/ You are less likely to have the second kind of libraries mentioned in the post.Comment
-
-
I'm not sure what the 'standard orientation' is.
But if you want to know more about read-orientation then take a look at these threads:
And while 'unstranded' is the default mode for tophat/bowtie, you need to change that if your library is something else.Comment
-
Well, I think the quickest test to assess if they are directional and how forward to reverse are handled in the librarires, you could map to a couple of genes and have a look in e.g. IGV to see if it makes sense. Or easier extract some read pairs from the raw sequencing files, and have a look how they align with BLAT.Originally posted by Nick View PostComment
-
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