Seqanswers Leaderboard Ad

Collapse

Announcement

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

  • Differential expression gene list from TCGA level 3 RNASeq V2 datasets downloaded fro

    I am interested in calculating differential expression of genes for tumor vs. normal samples from RNASeq V2 level 3 datasets for TCGA (downloaded from UCSC Cancer Browser). This data is from *.rsem.genes.normalized_results, log2(x+1) transformed and upper quantile normalized

    After browsing a lot of literature, blogs and forums, I am able to note following methods of calculate differential expression from TCGA datasets.

    1. Fold change Since the values from UCSC are already log 2 transformed, for a gene x, of tumor y, Log 2 fold change can be calculated as (log 2 transformed gene expression value of tumor sample) - (log 2 transformed gene expression value of matched normal sample).

    2. Packages like limma to fit a linear model to the log2-transformed data using an empirical Bayes method to moderate standard errors.

    3. Package EBSeq, as RSEM’s original paper since that algorithm takes into account the stochastic nature of the RSEM output.

    4. Or, I should get expected_counts or scaled-estimates from TCGA data-portal and then use voom() to normalize, as well as packages like DESeq, EBSeq, limma for differential expression

    5. Z-score (if comparing tumor vs. normal) = [(value gene X in tumor Y) - (mean gene X in normal)] / (standard deviation of gene X in normal)

    I also see variation of Z-score application as

    (A) in the TCGA cases where tumor samples are more than normal like say 500 tumor samples out of which only 65 have matched normal sample

    (B) In TCGA cases where you have only tumor samples or you want to consider only tumor samples and you can compare it with data of normal tissues as from GTEx

    (C) In cases where you have only tumor samples and twisting the calculations as

    Z-score= [(gene x log value – mean of log values gene x for all tumor tissues)/ standard deviation of gene x from mean of all tumor tissues]

    I would appreciate if fellow members can comment or suggest or share there experiences on dealing with such kind of datasets, on the following lines:

    Query 1: Have I understood these methods correct? How else we can calculate differential from TCGA datasets?

    Query 2. Since, Z-score assumes normal distribution and for RNASeq expression values one would not expect normal distribution, one should go for quantile normalization, but as TCGA datasets in UCSC is already quantile normalized, should these values be used directly and simply calculate fold change with that.

    Query 3. Are all the variations of Z-score mentioned in point 5 valid?

    Query 4: Which of the above or any other method is the most recommended method to calculate differential expression for tumor vs. normal samples from TCGA datasets and why?

Latest Articles

Collapse

  • seqadmin
    Strategies for Sequencing Challenging Samples
    by seqadmin


    Despite advancements in sequencing platforms and related sample preparation technologies, certain sample types continue to present significant challenges that can compromise sequencing results. Pedro Echave, Senior Manager of the Global Business Segment at Revvity, explained that the success of a sequencing experiment ultimately depends on the amount and integrity of the nucleic acid template (RNA or DNA) obtained from a sample. “The better the quality of the nucleic acid isolated...
    03-22-2024, 06:39 AM
  • seqadmin
    Techniques and Challenges in Conservation Genomics
    by seqadmin



    The field of conservation genomics centers on applying genomics technologies in support of conservation efforts and the preservation of biodiversity. This article features interviews with two researchers who showcase their innovative work and highlight the current state and future of conservation genomics.

    Avian Conservation
    Matthew DeSaix, a recent doctoral graduate from Kristen Ruegg’s lab at The University of Colorado, shared that most of his research...
    03-08-2024, 10:41 AM

ad_right_rmr

Collapse

News

Collapse

Topics Statistics Last Post
Started by seqadmin, Yesterday, 06:37 PM
0 responses
11 views
0 likes
Last Post seqadmin  
Started by seqadmin, Yesterday, 06:07 PM
0 responses
10 views
0 likes
Last Post seqadmin  
Started by seqadmin, 03-22-2024, 10:03 AM
0 responses
51 views
0 likes
Last Post seqadmin  
Started by seqadmin, 03-21-2024, 07:32 AM
0 responses
67 views
0 likes
Last Post seqadmin  
Working...
X