Complete report from DESeq2 analysis

degResults(res = NULL, dds, rlogMat = NULL, name, org = NULL,
  FDR = 0.05, do_go = FALSE, FC = 0.1, group = "condition",
  xs = "time", path_results = ".", contrast = NULL)

Arguments

res

output from DESeq2::results() function.

dds

DESeq2::DESeqDataSet() object.

rlogMat

matrix from DESeq2::rlog() function.

name

string to identify results

org

an organism annotation object, like org.Mm.eg.db. NULL if you want to skip this step.

FDR

int cutoff for false discovery rate.

do_go

boolean if GO enrichment is done.

FC

int cutoff for log2 fold change.

group

string column name in colData(dds) that separates samples in meaninful groups.

xs

string column name in colData(dss) that will be used as X axes in plots (i.e time)

path_results

character path where files are stored. NULL if you don't want to save any file.

contrast

list with character vector indicating the fold change values from different comparisons to add to the output table.

Value

ggplot2 object

Examples

data(humanGender) library(DESeq2) idx <- c(1:10, 75:85) dse <- DESeqDataSetFromMatrix(assays(humanGender)[[1]][1:1000, idx], colData(humanGender)[idx,], design=~group) dse <- DESeq(dse)
#> using pre-existing size factors
#> estimating dispersions
#> gene-wise dispersion estimates
#> mean-dispersion relationship
#> final dispersion estimates
#> fitting model and testing
#> -- replacing outliers and refitting for 1 genes #> -- DESeq argument 'minReplicatesForReplace' = 7 #> -- original counts are preserved in counts(dds)
#> estimating dispersions
#> fitting model and testing
res <- degResults(dds = dse, name = "test", org = NULL, do_go = FALSE, group = "group", xs = "group", path_results = NULL)
#> Doing rlog...
#> Getting result...
#> ## Comparison: test {.tabset} #> #> #> [1] "DESeqResults object of length 6 with 2 metadata columns"<br>[2] NA <br>[3] NA <br>[4] NA <br>[5] NA <br>[6] NA <br>[7] NA <br>[8] NA #> #> #> Differential expression file at: test_de.csv #> #> Normalized counts matrix file at: test_log2_counts.csv #> #> ### MA plot plot #>
#> #> #> ### Volcano plot #> #> #> #> ### QC for DE genes
#> #> #> ### Most significants, FDR< 0.05 and log2FC > 0.1 : 10
#> #> #> #> ### Plots top 9 most significants
#> No genes were mapped to rowData. check ann parameter values.
#> Using gene as id variables
#> #> #> #> ### Top DE table #> #> #> #> | | baseMean| log2FoldChange| lfcSE| stat| pvalue| padj| absMaxLog2FC| #> |:---------------|----------:|--------------:|---------:|---------:|---------:|---------:|------------:| #> |ENSG00000067048 | 1025.03783| 10.1571705| 0.4233146| 23.994380| 0.0000000| 0.0000000| 10.1571705| #> |ENSG00000012817 | 411.54387| 9.2394007| 0.4237379| 21.804517| 0.0000000| 0.0000000| 9.2394007| #> |ENSG00000067646 | 169.81477| 10.1874916| 0.6579432| 15.483847| 0.0000000| 0.0000000| 10.1874916| #> |ENSG00000005889 | 670.86191| -0.6919265| 0.1314523| -5.263708| 0.0000001| 0.0000353| 0.6919265| #> |ENSG00000006757 | 92.66111| -0.7666012| 0.1611520| -4.757006| 0.0000020| 0.0003930| 0.7666012| #> |ENSG00000073282 | 220.15603| -1.8685615| 0.4206120| -4.442482| 0.0000089| 0.0014821| 1.8685615| #> |ENSG00000005302 | 2026.54990| -0.7418952| 0.1763412| -4.207157| 0.0000259| 0.0036943| 0.7418952| #> |ENSG00000005020 | 1233.86316| 0.3888370| 0.0952312| 4.083085| 0.0000444| 0.0055552| 0.3888370| #> |ENSG00000003400 | 393.62677| 0.6803243| 0.1766475| 3.851310| 0.0001175| 0.0130542| 0.6803243| #> |ENSG00000069702 | 106.67010| -1.6323189| 0.4585611| -3.559654| 0.0003713| 0.0371343| 1.6323189| #> |ENSG00000010278 | 84.30823| 1.2035871| 0.3554857| 3.385754| 0.0007098| 0.0645300| 1.2035871| #> |ENSG00000023171 | 165.31692| -1.4022259| 0.4236024| -3.310240| 0.0009322| 0.0776799| 1.4022259| #> |ENSG00000072501 | 3694.76013| -0.5604815| 0.1707989| -3.281529| 0.0010325| 0.0794200| 0.5604815| #> |ENSG00000070018 | 119.89049| -1.0921227| 0.3512409| -3.109327| 0.0018751| 0.1339388| 1.0921227| #> |ENSG00000059377 | 131.98111| 0.8405094| 0.2744635| 3.062372| 0.0021959| 0.1463935| 0.8405094| #> |ENSG00000008277 | 377.43955| -0.6368732| 0.2136506| -2.980910| 0.0028739| 0.1796208| 0.6368732| #> |ENSG00000005059 | 479.12528| 0.4225402| 0.1492246| 2.831571| 0.0046320| 0.2289281| 0.4225402| #> |ENSG00000012963 | 1829.21224| 0.2471040| 0.0861859| 2.867104| 0.0041425| 0.2289281| 0.2471040| #> |ENSG00000038427 | 100.87217| -1.0743654| 0.3810269| -2.819658| 0.0048075| 0.2289281| 1.0743654| #> |ENSG00000068079 | 1035.17996| 0.4075632| 0.1415563| 2.879160| 0.0039874| 0.2289281| 0.4075632| #> #>