Unconfigured Ad

Collapse
X
 
  • Filter
  • Time
  • Show
Clear All
new posts
  • muzz56
    Member
    • Sep 2010
    • 14

    regulatory program

    I am sorry if this post is a wee bit misplaced, but I am still hoping someone out there has encountered a similar problem and solved it.
    I have transcript abundance values (rpkm) and now I want to cluster them in some meaningful way. What I really want to do is make regulatory programs such that cluster x can be said to be regulated by regulator(s) y. The program should take as input, the rpkm values and a list of some potential regulators, then output the clusters linked to a regulator(s). I've been messing with Genomica but it runs very slowly and the support from the developers ain't there. I am wondering if someone knows something that can do a similar job, or how to make Genomica run faster.
    Thanks in advance and again, my sincere apologies if this doesn't belong here.

Latest Articles

Collapse

  • SEQadmin2
    Advanced Sequencing Platforms Tackle Neuroscience’s Toughest Genomics Problems
    by SEQadmin2



    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
  • SEQadmin2
    Cancer Drug Resistance: The Lingering Barrier to Rising Survival
    by SEQadmin2



    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
  • GATTACAT
    Reply to Nine Things a Sample Prep Scientist Thinks About Before Sequencing
    by GATTACAT
    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

ad_right_rmr

Collapse

News

Collapse

Topics Statistics Last Post
Started by SEQadmin2, Yesterday, 10:26 AM
0 responses
13 views
0 reactions
Last Post SEQadmin2  
Started by SEQadmin2, 07-09-2026, 10:04 AM
0 responses
26 views
0 reactions
Last Post SEQadmin2  
Started by SEQadmin2, 07-08-2026, 10:08 AM
0 responses
16 views
0 reactions
Last Post SEQadmin2  
Started by SEQadmin2, 07-07-2026, 11:05 AM
0 responses
33 views
0 reactions
Last Post SEQadmin2  
Working...