covariate vs adjustvars
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justinjj ▴ 10
@justinjj-13530
Last seen 6.4 years ago

I'm using tuxedo work flow to find DGE  (ballgown) of RNAseq data control vs treated each with biological replicates. which one of the below matrix and stattest should be applied and why?

https://github.com/skptic/tuxedo-nf

any help would be appreciated, Thanks.

1.

sample condition Bioreplicate

sampleA Ctr rep1

sampleA Ctr rep2

sampleA Ctr rep3

sampleA Tre rep1

sampleA Tre rep2

sampleA Cre rep3

stat_results = stattest(bg, feature='transcript', meas='FPKM', covariate='condition', adjustvars=c('Bioreplicate'), getFC=TRUE)

 

2.

sample condition

sampleA Ctr

sampleA Ctr

sampleA Ctr

sampleA Tre

sampleA Tre

sampleA Tre

stat_results = stattest(bg, feature='transcript', meas='FPKM', covariate='condition', getFC=TRUE)

 

Another category two condition (control vs treated) from two different cell lines (a,b) with replicate (3).

Other than one of the above matrix to call control vs treated for each lines separately, I wanted to know genes which are diff.exp btn control vs treated in both cell lines. Could I use the below matrix?

1.

sample condition cell

sampleA Ctr cellA

sampleB Ctr cellA

sampleC Ctr cellA

sampleD Tre cellA

sampleE Tre cellA

sampleF Tre cellA

sampleG Ctr cellB

sampleH Ctr cellB

sampleI Ctr cellB

sampleJ Tre cellB

sampleK Tre cellB

sampleL Cre cellB

stat_results = stattest(bg, feature='transcript', meas='FPKM', covariate='condition', adjustvars=c('cell'), getFC=TRUE)

OR 

stat_results = stattest(bg, feature='transcript', meas='FPKM', covariate='cell', adjustvars=c('condition), timecourse=TRUE, getFC=TRUE)
ballgown rnaseq differential gene expression tuxedo • 1.4k views
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