Description Usage Arguments Details Value Examples
scale_abundance() takes as input a 'tbl' formatted as | <SAMPLE> | <TRANSCRIPT> | <COUNT> | <...> | and Scales transcript abundance compansating for sequencing depth (e.g., with TMM algorithm, Robinson and Oshlack doi.org/10.1186/gb-2010-11-3-r25).
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 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 | scale_abundance(
.data,
.sample = NULL,
.transcript = NULL,
.abundance = NULL,
method = "TMM",
reference_sample = NULL,
action = "add",
reference_selection_function = NULL
)
## S4 method for signature 'spec_tbl_df'
scale_abundance(
.data,
.sample = NULL,
.transcript = NULL,
.abundance = NULL,
method = "TMM",
reference_sample = NULL,
action = "add",
reference_selection_function = NULL
)
## S4 method for signature 'tbl_df'
scale_abundance(
.data,
.sample = NULL,
.transcript = NULL,
.abundance = NULL,
method = "TMM",
reference_sample = NULL,
action = "add",
reference_selection_function = NULL
)
## S4 method for signature 'tidybulk'
scale_abundance(
.data,
.sample = NULL,
.transcript = NULL,
.abundance = NULL,
method = "TMM",
reference_sample = NULL,
action = "add",
reference_selection_function = NULL
)
## S4 method for signature 'SummarizedExperiment'
scale_abundance(
.data,
.sample = NULL,
.transcript = NULL,
.abundance = NULL,
method = "TMM",
reference_sample = NULL,
action = "add",
reference_selection_function = NULL
)
## S4 method for signature 'RangedSummarizedExperiment'
scale_abundance(
.data,
.sample = NULL,
.transcript = NULL,
.abundance = NULL,
method = "TMM",
reference_sample = NULL,
action = "add",
reference_selection_function = NULL
)
|
.data |
A 'tbl' formatted as | <SAMPLE> | <TRANSCRIPT> | <COUNT> | <...> | |
.sample |
The name of the sample column |
.transcript |
The name of the transcript/gene column |
.abundance |
The name of the transcript/gene abundance column |
method |
A character string. The scaling method passed to the back-end function (i.e., edgeR::calcNormFactors; "TMM","TMMwsp","RLE","upperquartile") |
reference_sample |
A character string. The name of the reference sample. If NULL the sample with highest total read count will be selected as reference. |
action |
A character string between "add" (default) and "only". "add" joins the new information to the input tbl (default), "only" return a non-redundant tbl with the just new information. |
reference_selection_function |
DEPRECATED. please use reference_sample. |
maturing
Scales transcript abundance compensating for sequencing depth (e.g., with TMM algorithm, Robinson and Oshlack doi.org/10.1186/gb-2010-11-3-r25). Lowly transcribed transcripts/genes (defined with minimum_counts and minimum_proportion parameters) are filtered out from the scaling procedure. The scaling inference is then applied back to all unfiltered data.
Underlying method edgeR::calcNormFactors(.data, method = c("TMM","TMMwsp","RLE","upperquartile"))
A tbl object with additional columns with scaled data as '<NAME OF COUNT COLUMN>_scaled'
A tbl object with additional columns with scaled data as '<NAME OF COUNT COLUMN>_scaled'
A tbl object with additional columns with scaled data as '<NAME OF COUNT COLUMN>_scaled'
A tbl object with additional columns with scaled data as '<NAME OF COUNT COLUMN>_scaled'
A 'SummarizedExperiment' object
A 'SummarizedExperiment' object
1 2 3 4 | tidybulk::counts_mini %>%
tidybulk(sample, transcript, count) %>%
identify_abundant() %>%
scale_abundance()
|
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