Tweet
Hello, I run a core facility for the University of Arizona and we are about to jump into next gen seq. This is my first post and I'm not sure if this is the appropriate place to ask this question but I was wondering if there was a consensus from actual researchers on which next gen platform is preferred. Any and all replies are appreciated. I'm very excited to be a part of such a great forum!
-
Ryan Sprissler
Staff Scientist - manager University of Arizona Genetic Core (UAGC) -
Hey Ryan!
I moved your post to the general forum so it gets wider viewing.
I think for a core facility you will need 454 + either Solexa/SOLiD. The drastic differences in read length/throughput are a good complement.
As to Solexa vs. SOLiD, there isn't much to judge yet for the ABI technology...that will likely play out over the next years. -
Thanks ECO,
I agree they are a great compliment to each other, with limited resources we are forced to pick one or the other. I have just started to see publications come out using SOLiD data and the sales reps are getting pretty pushy here at the end of Q4. Just wanted to find out if anybody had serious problems with either platform. Thanks again, by the way loved the Tasmanian Devil pic!Ryan Sprissler
Staff Scientist - manager University of Arizona Genetic Core (UAGC)Comment
-
Before jumping in you should definitely get a sense of what the PIs would get the most out of. While they are both considered next gen systems, short read and long read sequences are often very different animals as far as the applications they are used for. For example, 454 would be a waste for small RNA analysis and expression tags - but it can't be beat for metagenomics and transcriptome analysis.
While I wouldn't underestimate ABI, I think Illumina beat them for this generation of short read next gen systemsComment
-
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