Seqanswers Leaderboard Ad

Collapse

Announcement

Collapse
No announcement yet.
X
 
  • Filter
  • Time
  • Show
Clear All
new posts

  • Normalisation of RNAseq data from UCSC Xena Browser

    Dear all

    I am very new to this so apologies in advance..

    I am trying to teach myself the basics of R and bioinformatics and would like to attempt some analysis of TCGA data

    I have downloaded the RNA-seq data from the LUAD TCGA data set using the 'HTSeq-Counts' link from this page:



    I would like just do a simple correlation of expression of gene y with gene z

    I then want to perform Kaplan-Meier analysis of overall survival after dividing patients into high and low expression of gene y (using the median to split the cohorts)

    My questions are about normalising the data, before I perform the analyses

    1) The UCSC page explains that the data has been log(x+1) transformed. I would like to know if the raw data was normalised for library size prior to log transformation? If not, is this necessary?

    I obtained the count matrix and back-transformed the counts ((2^x) - 1) and I then summed the total counts per sample and obtained different values per sample, which makes me assume that the counts were not corrected for library size

    2) Finally, assuming that the data have not been normalised for library size (or distribution etc) what method would you suggest to normalise for my analysis. I understand I could just do TPM or could do TMM or another method such as that used by DESeq2

    Thanks in advance for any help, I did try to find the answer to q1 elsewhere but couldn't

Latest Articles

Collapse

  • seqadmin
    Best Practices for Single-Cell Sequencing Analysis
    by seqadmin



    While isolating and preparing single cells for sequencing was historically the bottleneck, recent technological advancements have shifted the challenge to data analysis. This highlights the rapidly evolving nature of single-cell sequencing. The inherent complexity of single-cell analysis has intensified with the surge in data volume and the incorporation of diverse and more complex datasets. This article explores the challenges in analysis, examines common pitfalls, offers...
    06-06-2024, 07:15 AM
  • seqadmin
    Latest Developments in Precision Medicine
    by seqadmin



    Technological advances have led to drastic improvements in the field of precision medicine, enabling more personalized approaches to treatment. This article explores four leading groups that are overcoming many of the challenges of genomic profiling and precision medicine through their innovative platforms and technologies.

    Somatic Genomics
    “We have such a tremendous amount of genetic diversity that exists within each of us, and not just between us as individuals,”...
    05-24-2024, 01:16 PM

ad_right_rmr

Collapse

News

Collapse

Topics Statistics Last Post
Started by seqadmin, Yesterday, 07:49 AM
0 responses
12 views
0 likes
Last Post seqadmin  
Started by seqadmin, 06-20-2024, 07:23 AM
0 responses
14 views
0 likes
Last Post seqadmin  
Started by seqadmin, 06-17-2024, 06:54 AM
0 responses
16 views
0 likes
Last Post seqadmin  
Started by seqadmin, 06-14-2024, 07:24 AM
0 responses
24 views
0 likes
Last Post seqadmin  
Working...
X