Description Usage Arguments Details Value See Also Examples
Find differential TSSs or TSRs from previously generated edgeR or DESeq2 model.
1 2 3 4 5 6 7 8 | differential_expression(
experiment,
data_type = c("tss", "tsr", "tss_features", "tsr_features"),
comparison_name,
comparison_type,
comparison,
shrink_lfc = FALSE
)
|
experiment |
TSRexploreR object. |
data_type |
Whether the input was generated from TSSs ('tss') or TSRs ('tsr'). |
comparison_name |
The name given to the comparison when stored back into the TSRexploreR object. |
comparison_type |
For DEseq2, either 'contrast' or 'name'. For edgeR, either 'contrast' or 'coef'. |
comparison |
For DESeq2, the contrast or name. For edgeR, the coefficients or contrasts. |
shrink_lfc |
For DESeq2, whether the log2 fold changes are shrunk (TRUE) or not (FALSE). |
Calculatse the differential TSSs or TSRs for the desired contrast. 'comparison_type' corresponds to the way the comparison will be performed, with edgeR having the 'contrast' and 'coef' options, and DESeq2 having the 'contrast' and 'name' options. The actual contrast is specified with 'comparison', the format of which should match with the option provided to 'comparison_type'. If DESeq2 is used and 'shrink_lfc' is TRUE, apeglm is used to shrink the Log2 fold changes to mitigate the effect size of genes with lower levels of expression. The results for the contrast will be stored back into the TSRexploreR object with the name provided to 'comparison_name'.
TSRexploreR object with results for given contrast.
fit_de_model
to fit DEseq2 or edgeR model to data.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | data(TSSs)
sample_sheet <- data.frame(
sample_name=c(
sprintf("S288C_D_%s", seq_len(3)),
sprintf("S288C_WT_%s", seq_len(3))
),
file_1=rep(NA, 6), file_2=rep(NA, 6),
condition=c(
rep("Diamide", 3),
rep("Untreated", 3)
)
)
exp <- TSSs %>%
tsr_explorer(sample_sheet=sample_sheet) %>%
format_counts(data_type="tss")
# Differential TSSs with DESeq2.
exp <- fit_de_model(exp, data_type="tss", formula=~condition, method="edgeR")
exp <- differential_expression(
exp, data_type="tss",
comparison_name="Diamide_vs_Untreated",
comparison_type="coef",
comparison=2
)
|
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