Unconfigured Ad

Collapse
X
 
  • Filter
  • Time
  • Show
Clear All
new posts
  • bigmw
    Senior Member
    • Aug 2013
    • 124

    Update in the gage RNA-seq pathway analysis joint workflow

    There were some typos in page 11 of the “RNA-seq Data Pathway and Gene-set Analysis Workflows” vignette (gage 2.12.1, December 20, 2013). This only occurred with the joint workflow details (with DESeq/DESeq2, edgeR, Limma or Cufflinks). RNA-Seq pathway analyses following the native workflow or the Quick Start are not affected.

    Original code was:
    ..
    sel.l <- cnts.kegg.p$less[, "q.val"] < 0.1 & !is.na(cnts.kegg.p$less[,"q.val"])
    path.ids.l <- rownames(cnts.kegg.p$less)[sel.l]
    ..
    The typos resulted in “Error: object 'cnts.kegg.p' not found”. Here cnts.kegg.p should be fc.kegg.p instead. The typos have been corrected in the updated package (gage 2.12.2):
    GAGE is a published method for gene set (enrichment or GSEA) or pathway analysis. GAGE is generally applicable independent of microarray or RNA-Seq data attributes including sample sizes, experimental designs, assay platforms, and other types of heterogeneity, and consistently achieves superior performance over other frequently used methods. In gage package, we provide functions for basic GAGE analysis, result processing and presentation. We have also built pipeline routines for of multiple GAGE analyses in a batch, comparison between parallel analyses, and combined analysis of heterogeneous data from different sources/studies. In addition, we provide demo microarray data and commonly used gene set data based on KEGG pathways and GO terms. These funtions and data are also useful for gene set analysis using other methods.

Latest Articles

Collapse

  • 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
  • SEQadmin2
    Nine Things a Sample Prep Scientist Thinks About Before Sequencing
    by SEQadmin2


    I’m not a sequencing expert. I’m a purification scientist who uses NGS to evaluate workflows my group develops. With this perspective, we think about the sample first and the NGS workflow second. The sequencer is an exceptionally honest reporter, but it can only report on what you give it, so whether you get clean, interpretable data from an NGS workflow is largely determined before you begin.

    Here are nine questions we think about, in roughly the order they matter, before...
    06-18-2026, 07:11 AM

ad_right_rmr

Collapse

News

Collapse

Topics Statistics Last Post
Started by SEQadmin2, 07-02-2026, 11:08 AM
0 responses
24 views
0 reactions
Last Post SEQadmin2  
Started by SEQadmin2, 06-30-2026, 05:37 AM
0 responses
23 views
0 reactions
Last Post SEQadmin2  
Started by SEQadmin2, 06-26-2026, 11:10 AM
0 responses
23 views
0 reactions
Last Post SEQadmin2  
Started by SEQadmin2, 06-17-2026, 06:09 AM
0 responses
55 views
0 reactions
Last Post SEQadmin2  
Working...