Interpretation of Δexon–Δintron vs Δintron scatterplots before and after removing the bias term
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Dear REMBRANTS team,
I have applied your pipeline to a dataset of different cell lines within the same cell type. Differential expression analysis revealed a large number of downregulated/upregulated genes between them, and I would also expect some deviations from stability.
When running the pipeline, scatter plots of Δexon–Δintron vs Δintron are produced (see one example attached). I uncommented from your code, the plotting of loess fitting regression line and seems to fit a constant line in Δexon–Δintron=0 (red), either before or after correction. I do not see any trends like those the paper (Fig 1.c and 1.d).
Could you please share your interpretation of these plots with me?
The data was generated using a total RNAseq protocol, has good coverage and the Δexon vs Δexon displays good correlation.
Below the relevant text printed by the pipeline:
[1] "Optimizing read count cutoff at stringency 0.99 ..."
[1] "Total correlation is 1"
[1] "Total number of genes is 15181"
[1] "Maximum correlation is 1"
[1] "Selected threshold is 5.87159523748979"
[1] "Number of remaining genes is 12773"
.
Many thanks,
Ivan
Hi Hamed,
Thanks for the quick reply. I checked the files as suggested. Indeed they were basically the same, so I applied CRIES and ran REMBRANDTS again. This time the results are of course more informative. Please find the same plots/info below:
1] "Optimizing read count cutoff at stringency 0.99 ..."
[1] "Total correlation is 0.592024058847667"
[1] "Total number of genes is 13915"
[1] "Maximum correlation is 0.704987667859836"
[1] "Selected threshold is 8.2731303169406"
[1] "Number of remaining genes is 4779"
Just one quick question, could you please provide me with a quick interpretation of the corrected plot, why does the slope becomes positive?
Appreciate your help and looking forward for the downstream analysis.
Best,
Ivan