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Understanding Sleuth output for multiple samples
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2.1 years ago
Bombay, India

I have RNAseq data from 10 different condition with two biological replicates each. I have run Kallisto on all the samples with 100 bootstraps.

I passed all the samples to Sleuth for analysis with a reference table as mentioned in the "getting started" page.

sample   condition
A1         A
A2         A
B1         B
B2         B
C1         C
C2         C


...and so on.

I fitted the model as described in the "getting started" page and exported the results obtained by

results_table <- sleuth_results(so, 'reduced:full', test_type = 'lrt')


I export this table as a CSV file with columns which include p-value and q-value (and other metrics). What I do not understand is what do these p-values signify. What happens when multiple conditions are passed; does Sleuth do a pairwise comparison? If that is so then there should be a p-value/q-value (and other values) for each pair. I am not getting that.

When I input multiple conditions then do p-values denote differential expression in all the conditions or at least one condition?

If possible also let me know (some page/resource on) what other models can be fit on the data (from the "getting started" example, it appears that different models are possible but the manual and the preprint do not mention anything other than the intercept-only model).

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