Ryan C. Thompson 60d111c398 Initial import into git 9 лет назад
..
FPKM by Peak Status H3K4.pdf 60d111c398 Initial import into git 9 лет назад
Promoter Peak Distance Profile.pdf 60d111c398 Initial import into git 9 лет назад
README.mkdn 60d111c398 Initial import into git 9 лет назад
p-value distributions.pdf 60d111c398 Initial import into git 9 лет назад
promoter-edger-topgenes3-ql.xlsx 60d111c398 Initial import into git 9 лет назад
rnaseq-edgeR-vs-limma.pdf 60d111c398 Initial import into git 9 лет назад
rnaseq-limma-weighted-vs-uw.pdf 60d111c398 Initial import into git 9 лет назад
rnaseq-maplots-limma-sampleweights.pdf 60d111c398 Initial import into git 9 лет назад

README.mkdn

This is a series of example plots and tables from a combined
RNA-seq/ChIP-seq study on differences between naive and memory T-cell
activation.

- [p-value distributions.pdf](p-value distributions.pdf) is a series
of p-value histograms for each of the contrasts tested. A contrast
with no significant differential expression would exhibit a uniform
distribution, while differential expression would be reflected by an
excess of small p-values.
- [FPKM by Peak Status H3K4.pdf](FPKM by Peak Status H3K4.pdf) shows
the variation in gene expression based on the presence or absence of
two histone marks in the gene promoters.
- [promoter-edger-topgenes3-ql.xlsx](promoter-edger-topgenes3-ql.xlsx)
is a spreadsheet of all promoters with differential histone
modification in their promoters based on the ChIP-seq read counts.
- [Promoter Peak Distance Profile.pdf](Promoter Peak Distance Profile.pdf)
shows the distribution of distances from transcription
start sites to the nearest peak for the three histone modifications
studied. This was used to determine the "promoter radius" for read
counting. Notably, the three histone marks do not all have the same
promoter radius.
- [rnaseq-edgeR-vs-limma.pdf](rnaseq-edgeR-vs-limma.pdf) and
[rnaseq-limma-weighted-vs-uw.pdf](rnaseq-limma-weighted-vs-uw.pdf)
show comparisons of p-values for all genes in each contrast of the
RNA-seq data, comparing edgeR and limma-voom with/without sample
quality weights. The final choice of method was limma-voom with
sample quality weights.
- [rnaseq-maplots-limma-sampleweights.pdf](rnaseq-maplots-limma-sampleweights.pdf)
shows the MA plot for each contrast of the RNA-seq data