Unconfigured Ad

Collapse
X
 
  • Filter
  • Time
  • Show
Clear All
new posts
  • Name_less_
    Member
    • Oct 2014
    • 12

    Script for FPKM with Deseq2 - help

    Hello to all.
    I'm new in R, but I'm working with RNA-seq data for a work in a course.
    Specifically, I have a count matrix similar to that:

    gene sample1 sample2 sample3 sample4 gene_length(nt)
    A 10 100 1000 10000 5000
    B 20 200 2000 20000 5000
    C 30 300 3000 30000 5000
    D 1 5 10 15 5000

    I maked a Perl script to calculate FPKM, but now also I need to make other in R.
    I read that DESEQ2 have functions to obtain fpkm.
    But, at the moment for me has been impossible to generate a script for that.

    I've only done this, but have error ("Error in all_dims[, 1L]"):
    -----------------------------------------------

    library(DESeq2)

    data <- read.delim(file = "prueba.tab",header = TRUE,
    sep = "\t", stringsAsFactors = FALSE)

    se <- SummarizedExperiment(list(counts=data), colData=DataFrame(sample=1:4))
    dds <- DESeqDataSet(se, ~ 1)

    fpkm(dds)

    -----------------------------------------------

    Someone can help me with that?

    Thanks for all!

Latest Articles

Collapse

  • SEQadmin2
    Proteomic Platforms: How to Choose the Right Analytical Strategy to Improve Detection and Clinical Applications
    by SEQadmin2


    Proteomics platforms are evolving rapidly, with advances in mass spectrometry and affinity-based approaches expanding what researchers can detect and at what scale. As the field moves toward deeper proteome coverage and clinical applications, scientists face an increasingly complex landscape of tools. This article will explore how researchers are navigating these choices to find the right platform for their work.

    The systematic characterization of the human proteome has
    ...
    07-20-2026, 11:48 AM
  • 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

ad_right_rmr

Collapse

News

Collapse

Topics Statistics Last Post
Started by SEQadmin2, 07-24-2026, 12:17 PM
0 responses
28 views
0 reactions
Last Post SEQadmin2  
Started by SEQadmin2, 07-23-2026, 11:41 AM
0 responses
21 views
0 reactions
Last Post SEQadmin2  
Started by SEQadmin2, 07-20-2026, 11:10 AM
0 responses
210 views
0 reactions
Last Post SEQadmin2  
Started by SEQadmin2, 07-13-2026, 10:26 AM
0 responses
78 views
0 reactions
Last Post SEQadmin2  
Working...