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Interpretation of Δexon–Δintron vs Δintron scatterplots before and after removing the bias term #13

@rosshandler

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@rosshandler

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"
.
scatterplot CellLine1_rep1 exon

scatterplot

Many thanks,
Ivan

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