Ryan C. Thompson
330f2b34c6
Update CD4 examples
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README.mkdn
[MOFA](https://github.com/PMBio/MOFA) was used to analyze RNA-seq data
and ChIP-seq data for 3 histone marks together, looking for sources of
variation shared acorss all data types. Two different analyses were
done, one with ChIP-seq reads counted in promoter regions, and one
with ChIP-seq reads counted in called peaks. Each analysis is split
into two steps. The first step ("run") is fitting the model (which
takes a long time) and performing some basic QC, while the second step
("analyze") loads the fitted model and performs some analysis.
## Peak-based analysis
- Step 1: [`peak-mofa-run.html`](peak-mofa-run.html)
- Step 2: [`peak-mofa-analyze.html`](peak-mofa-analyze.html)
## Promoter-based analysis
- Step 1: [`promoter-mofa-run.html`](promoter-mofa-run.html)
- Step 2: [`promoter-mofa-analyze.html`](promoter-mofa-analyze.html)
and ChIP-seq data for 3 histone marks together, looking for sources of
variation shared acorss all data types. Two different analyses were
done, one with ChIP-seq reads counted in promoter regions, and one
with ChIP-seq reads counted in called peaks. Each analysis is split
into two steps. The first step ("run") is fitting the model (which
takes a long time) and performing some basic QC, while the second step
("analyze") loads the fitted model and performs some analysis.
## Peak-based analysis
- Step 1: [`peak-mofa-run.html`](peak-mofa-run.html)
- Step 2: [`peak-mofa-analyze.html`](peak-mofa-analyze.html)
## Promoter-based analysis
- Step 1: [`promoter-mofa-run.html`](promoter-mofa-run.html)
- Step 2: [`promoter-mofa-analyze.html`](promoter-mofa-analyze.html)