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Convert SEDesign to data.frame of design factors

Source: R/jam_sedesign_to_factors.R
sedesign_to_factors.Rd

Convert SEDesign to data.frame of design factors

Usage

sedesign_to_factors(
  sedesign,
  se = NULL,
  factor_names = NULL,
  factor_sep = "_",
  default_order = c("appearance", "mixedSort"),
  verbose = FALSE,
  ...
)

Arguments

sedesign

SEDesign object

se

SummarizedExperiment object which contains SummarizedExperiment::colData() with columns of design annotations. When present, values in the factor data.frame will be matched to values in these columns in order to re-use factor levels where possible. When factor_names is not defined, this step will also re-use the associated colnames from colData(se) when the values are matched.

factor_names

character vector of colnames to use for the resulting design factor colnames.

factor_sep

character string with expected delimiter between factors, default "_", for example "WT_Treated".

default_order

character string indicating how to order factor levels when a colname in the factor data.frame is not a factor in the matching colData() column.

  • "appearance": factor levels are defined in the order they appear in the sample data

  • "mixedSort": factor levels are defined by sorting data using jamba::mixedSort() which performs proper alphanumeric sorting, such that "Treat2" appears before "Treat10" for example.

verbose

logical indicating whether to print verbose output.

Value

data.frame with one column for each experiment design factor, where each column is converted to factor for non-numeric columns, and where colnames are defined as follows:

  • use factor_colnames when supplied

  • use the corresponding column in colData(se) when se is supplied

  • use factor# format for all other columns

Details

This function is a utility function intended to convert SEDesign objects, which contain a design matrix, into a data.frame representing the experimental design factors used to produce the design matrix.

See also

Other jam experiment design: check_sedesign(), contrast2comp(), contrast_colors_by_group(), contrast_names_to_sedesign(), contrasts_to_factors(), contrasts_to_venn_setlists(), draw_oneway_contrast(), draw_twoway_contrast(), filter_contrast_names(), groups_to_sedesign(), plot_sedesign(), validate_sedesign()

Examples

isamples_1 <- paste0(
   rep(c("DMSO", "Etop", "DMSO", "Etop"), each=6),
   "_",
   rep(c("NF", "Flag"), each=12),
   "_",
   rep(c("WT", "KO", "WT", "KO", "WT", "D955N", "WT", "D955N"), each=3),
   "_",
   LETTERS[1:3])
# simple data.frame with group information
idf <- data.frame(jamba::rbindList(strsplit(isamples_1, "_")))[,1:3]
rownames(idf) <- isamples_1;
# convert to sedesign
sedesign <- groups_to_sedesign(idf)
plot_sedesign(sedesign, axis1=2, axis2=3, axis3=1, label_cex=0.5)


# prepare colData data.frame
cdf <- data.frame(check.names=FALSE, stringsAsFactors=FALSE,
   jamba::rbindList(strsplit(isamples_1, "_")))
colnames(cdf) <- c("Treatment", "Flag", "Genotype", "Rep")
rownames(cdf) <- sedesign@samples;
cdf
#>                   Treatment Flag Genotype Rep
#> DMSO_NF_WT_A           DMSO   NF       WT   A
#> DMSO_NF_WT_B           DMSO   NF       WT   B
#> DMSO_NF_WT_C           DMSO   NF       WT   C
#> DMSO_NF_KO_A           DMSO   NF       KO   A
#> DMSO_NF_KO_B           DMSO   NF       KO   B
#> DMSO_NF_KO_C           DMSO   NF       KO   C
#> Etop_NF_WT_A           Etop   NF       WT   A
#> Etop_NF_WT_B           Etop   NF       WT   B
#> Etop_NF_WT_C           Etop   NF       WT   C
#> Etop_NF_KO_A           Etop   NF       KO   A
#> Etop_NF_KO_B           Etop   NF       KO   B
#> Etop_NF_KO_C           Etop   NF       KO   C
#> DMSO_Flag_WT_A         DMSO Flag       WT   A
#> DMSO_Flag_WT_B         DMSO Flag       WT   B
#> DMSO_Flag_WT_C         DMSO Flag       WT   C
#> DMSO_Flag_D955N_A      DMSO Flag    D955N   A
#> DMSO_Flag_D955N_B      DMSO Flag    D955N   B
#> DMSO_Flag_D955N_C      DMSO Flag    D955N   C
#> Etop_Flag_WT_A         Etop Flag       WT   A
#> Etop_Flag_WT_B         Etop Flag       WT   B
#> Etop_Flag_WT_C         Etop Flag       WT   C
#> Etop_Flag_D955N_A      Etop Flag    D955N   A
#> Etop_Flag_D955N_B      Etop Flag    D955N   B
#> Etop_Flag_D955N_C      Etop Flag    D955N   C

# prepare assay matrix
imatrix <- matrix(data=seq_len(nrow(cdf) * 10), ncol=nrow(cdf));
colnames(imatrix) <- rownames(cdf);
rownames(imatrix) <- paste0("row", 1:10);
# prepare se
se <- SummarizedExperiment::SummarizedExperiment(
   assays=list(raw=imatrix),
   colData=cdf)

sedesign_to_factors(sedesign, se=se)
#>                   Treatment Flag Genotype
#> DMSO_NF_WT_A           DMSO   NF       WT
#> DMSO_NF_WT_B           DMSO   NF       WT
#> DMSO_NF_WT_C           DMSO   NF       WT
#> DMSO_NF_KO_A           DMSO   NF       KO
#> DMSO_NF_KO_B           DMSO   NF       KO
#> DMSO_NF_KO_C           DMSO   NF       KO
#> DMSO_Flag_WT_A         DMSO Flag       WT
#> DMSO_Flag_WT_B         DMSO Flag       WT
#> DMSO_Flag_WT_C         DMSO Flag       WT
#> DMSO_Flag_D955N_A      DMSO Flag    D955N
#> DMSO_Flag_D955N_B      DMSO Flag    D955N
#> DMSO_Flag_D955N_C      DMSO Flag    D955N
#> Etop_NF_WT_A           Etop   NF       WT
#> Etop_NF_WT_B           Etop   NF       WT
#> Etop_NF_WT_C           Etop   NF       WT
#> Etop_NF_KO_A           Etop   NF       KO
#> Etop_NF_KO_B           Etop   NF       KO
#> Etop_NF_KO_C           Etop   NF       KO
#> Etop_Flag_WT_A         Etop Flag       WT
#> Etop_Flag_WT_B         Etop Flag       WT
#> Etop_Flag_WT_C         Etop Flag       WT
#> Etop_Flag_D955N_A      Etop Flag    D955N
#> Etop_Flag_D955N_B      Etop Flag    D955N
#> Etop_Flag_D955N_C      Etop Flag    D955N

# confirm first column contains proper factor order
sedesign_to_factors(sedesign, se=se)[,1]
#>  [1] DMSO DMSO DMSO DMSO DMSO DMSO DMSO DMSO DMSO DMSO DMSO DMSO Etop Etop Etop
#> [16] Etop Etop Etop Etop Etop Etop Etop Etop Etop
#> Levels: DMSO Etop

# demonstrate reverse order of Treatment column levels
SummarizedExperiment::colData(se)$Treatment <- factor(
   SummarizedExperiment::colData(se)$Treatment,
   levels=c("Etop", "DMSO"))
sedesign_to_factors(sedesign, se=se)[,1]
#>  [1] DMSO DMSO DMSO DMSO DMSO DMSO DMSO DMSO DMSO DMSO DMSO DMSO Etop Etop Etop
#> [16] Etop Etop Etop Etop Etop Etop Etop Etop Etop
#> Levels: Etop DMSO

# define Treatment column levels again
SummarizedExperiment::colData(se)$Treatment <- factor(
   SummarizedExperiment::colData(se)$Treatment,
   levels=c("DMSO", "Etop"))
sedesign_to_factors(sedesign, se=se)[,1]
#>  [1] DMSO DMSO DMSO DMSO DMSO DMSO DMSO DMSO DMSO DMSO DMSO DMSO Etop Etop Etop
#> [16] Etop Etop Etop Etop Etop Etop Etop Etop Etop
#> Levels: DMSO Etop

# provide specific colnames to use from se object
sedesign_to_factors(sedesign,
   se=se,
   factor_names=c("Treatment", "Flag", "Genotyoe"))
#>              Treatment Flag Genotyoe
#> DMSO_NF_WT_A      DMSO   NF       WT
#> DMSO_NF_WT_B      DMSO   NF       WT
#> DMSO_NF_WT_C      DMSO   NF       WT
#> DMSO_NF_KO_A      DMSO   NF       KO
#> DMSO_NF_KO_B      DMSO   NF       KO
#> DMSO_NF_KO_C      DMSO   NF       KO
#>                   Treatment Flag Genotyoe
#> DMSO_NF_WT_A           DMSO   NF       WT
#> DMSO_NF_WT_B           DMSO   NF       WT
#> DMSO_NF_WT_C           DMSO   NF       WT
#> DMSO_NF_KO_A           DMSO   NF       KO
#> DMSO_NF_KO_B           DMSO   NF       KO
#> DMSO_NF_KO_C           DMSO   NF       KO
#> DMSO_Flag_WT_A         DMSO Flag       WT
#> DMSO_Flag_WT_B         DMSO Flag       WT
#> DMSO_Flag_WT_C         DMSO Flag       WT
#> DMSO_Flag_D955N_A      DMSO Flag    D955N
#> DMSO_Flag_D955N_B      DMSO Flag    D955N
#> DMSO_Flag_D955N_C      DMSO Flag    D955N
#> Etop_NF_WT_A           Etop   NF       WT
#> Etop_NF_WT_B           Etop   NF       WT
#> Etop_NF_WT_C           Etop   NF       WT
#> Etop_NF_KO_A           Etop   NF       KO
#> Etop_NF_KO_B           Etop   NF       KO
#> Etop_NF_KO_C           Etop   NF       KO
#> Etop_Flag_WT_A         Etop Flag       WT
#> Etop_Flag_WT_B         Etop Flag       WT
#> Etop_Flag_WT_C         Etop Flag       WT
#> Etop_Flag_D955N_A      Etop Flag    D955N
#> Etop_Flag_D955N_B      Etop Flag    D955N
#> Etop_Flag_D955N_C      Etop Flag    D955N
sedesign_to_factors(sedesign,
   se=se,
   factor_names=c("Treatment", "Flag", "Genotyoe"))[,1]
#>              Treatment Flag Genotyoe
#> DMSO_NF_WT_A      DMSO   NF       WT
#> DMSO_NF_WT_B      DMSO   NF       WT
#> DMSO_NF_WT_C      DMSO   NF       WT
#> DMSO_NF_KO_A      DMSO   NF       KO
#> DMSO_NF_KO_B      DMSO   NF       KO
#> DMSO_NF_KO_C      DMSO   NF       KO
#>  [1] DMSO DMSO DMSO DMSO DMSO DMSO DMSO DMSO DMSO DMSO DMSO DMSO Etop Etop Etop
#> [16] Etop Etop Etop Etop Etop Etop Etop Etop Etop
#> Levels: DMSO Etop

# substring of colnames(colData(se)) is acceptable
sedesign_to_factors(sedesign,
   factor_names=c("Treat", "Flag", "Genotyoe"),
   se=se)[,1]
#>              Treat Flag Genotyoe
#> DMSO_NF_WT_A  DMSO   NF       WT
#> DMSO_NF_WT_B  DMSO   NF       WT
#> DMSO_NF_WT_C  DMSO   NF       WT
#> DMSO_NF_KO_A  DMSO   NF       KO
#> DMSO_NF_KO_B  DMSO   NF       KO
#> DMSO_NF_KO_C  DMSO   NF       KO
#>  [1] DMSO DMSO DMSO DMSO DMSO DMSO DMSO DMSO DMSO DMSO DMSO DMSO Etop Etop Etop
#> [16] Etop Etop Etop Etop Etop Etop Etop Etop Etop
#> Levels: DMSO Etop