Seqanswers Leaderboard Ad

Collapse

Announcement

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

  • xfh
    replied
    thank you very much again, someone told me that the dataset can be fitting with R package "spline.smooth" first and then make ANCOVA ~

    Leave a comment:


  • JackieBadger
    replied
    Hmmm good question. I think someone with a stats background (i.e. not me) could answer your question accurately, but I'll have a guess:

    I think you would do two separate ANCOVAs, one each for you two age brackets. From these I believe you could compare the correlation p values, but not the slopes i.e. the effect size. For this I think you would need to use something like as Tukey's ad hoc test.

    Don't hold me to that!
    You should get advice from someone with more knowledge on the matter than I can provide.

    J

    Leave a comment:


  • xfh
    replied
    thank you for your information. and here i want to ask how to handle the dataset. because the age and number of samples are different. the data is not paired. like ancova(x,y), the vector x,y should be same length and paired, right?

    Leave a comment:


  • JackieBadger
    replied
    Two decent introductions into ANCOVA



    Leave a comment:


  • xfh
    started a topic how to make ANCOVA in two indenpendent dataset

    how to make ANCOVA in two indenpendent dataset

    for example, there are two gene expression microarray datasets,

    samples 1
    gene 14 year-old 25 year-old .....

    LDH 0.2 0.8 ....

    samples 2
    gene 12 year-old 20year-old .....

    LDH 0.25 0.78

    if i know the LDH gene expression level is increasing with age, I want to know the correlataion of the gene expression change in aging process between two samples, how i calculated the Pearson correlation. and how I make a ANCOVA in the above LDH expression between the two samples.

Latest Articles

Collapse

  • seqadmin
    Exploring Human Diversity Through Large-Scale Omics
    by seqadmin


    In 2003, researchers from the Human Genome Project (HGP) announced the most comprehensive genome to date1. Although the genome wasn’t fully completed until nearly 20 years later2, numerous large-scale projects, such as the International HapMap Project and 1000 Genomes Project, continued the HGP's work, capturing extensive variation and genomic diversity within humans. Recently, newer initiatives have significantly increased in scale and expanded beyond genomics, offering a more detailed...
    Today, 06:43 AM
  • 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

ad_right_rmr

Collapse

News

Collapse

Topics Statistics Last Post
Started by seqadmin, 06-21-2024, 07:49 AM
0 responses
15 views
0 likes
Last Post seqadmin  
Started by seqadmin, 06-20-2024, 07:23 AM
0 responses
16 views
0 likes
Last Post seqadmin  
Started by seqadmin, 06-17-2024, 06:54 AM
0 responses
18 views
0 likes
Last Post seqadmin  
Started by seqadmin, 06-14-2024, 07:24 AM
0 responses
28 views
0 likes
Last Post seqadmin  
Working...
X