Description Usage Arguments Details Value See Also Examples
View source: R/diff_exp_plots.R
Export differential features for use in clusterProfiler term enrichment.
1 2 3 4 5 6 7 8 9 | export_for_enrichment(
experiment,
data_type = c("tss", "tsr"),
de_comparisons = "all",
log2fc_cutoff = 1,
fdr_cutoff = 0.05,
keep_unchanged = FALSE,
anno_categories = NULL
)
|
experiment |
TSRexploreR object. |
data_type |
Whether to export genes associated with differential TSSs ('tss') or TSRs ('tsr'). |
de_comparisons |
Character vector of differential expression comparisons to export. |
log2fc_cutoff |
Differential features not meeting this |log2(fold change)| threshold will not be considered. |
fdr_cutoff |
Differential features not meeting this significance threshold will not be considered. |
keep_unchanged |
Logical for inclusion of genes not significantly changed in the exported list. |
anno_categories |
Vector of annotation categories to keep. If NULL no filtering by annotation type occurs. |
This function outputs a data.frame that is formatted for use with the 'compareCluster' function of the clusterProfiler library. The 'geneId', 'sample', and 'de_status' columns can be used in the formula 'geneId ~ sample + de_status'.
'de_comparisons' are the names given to the comparisons from the 'comparison_name' argument of the 'differential_expression' function. 'log2fc_cutoff' and 'fdr_cutoff' are the log2(fold change) and FDR cutoffs used for determination of significance.
'keep_unchanged' controls whether genes with the category of 'unchanged' (not differentially expressed) are returned in the table. Additionally, genes can be returned based on whether they have differential features within a certain relative genomic location, such as promoter. This is controlled by providing a vector of annotation types to 'anno_types'.
data.frame of genes and differential expression status of TSSs or TSRs.
fit_de_model
to fit a differential expression model.
differential_expression
to find differential TSSs or TSRs.
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 | data(TSSs)
annotation <- system.file("extdata", "S288C_Annotation.gtf", package="TSRexploreR")
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, genome_annotation=annotation) %>%
format_counts(data_type="tss") %>%
annotate_features(data_type="tss")
diff_tss <- exp %>%
fit_de_model(data_type="tss", formula=~condition, method="edgeR") %>%
differential_expression(
data_type="tss",
comparison_name="Diamide_vs_Untreated",
comparison_type="coef",
comparison=2)
diff_tss <- export_for_enrichment(diff_tss, data_type="tss")
|
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