diff_expr | R Documentation |
After selecting control and test samples for each contrast, surrogate variable
analysis (sva
) and differential expression analysis is performed.
diff_expr(
esets,
data_dir = getwd(),
annot = "SYMBOL",
prev_anals = list(NULL),
svanal = TRUE,
recheck = FALSE,
postfix = NULL,
port = 3838
)
esets |
List of annotated esets. Created by |
data_dir |
String specifying directory of GSE folders. |
annot |
String, column name in fData common to all esets. For duplicated values in this column, the row with the highest interquartile range across selected samples will be kept. If meta-analysis will follow, appropriate values are "SYMBOL" (default - for gene level analysis) or, if all esets are from the same platform, "PROBE" (for probe level analysis). |
prev_anals |
Previous result of |
svanal |
Use surrogate variable analysis? Default is |
recheck |
Would you like to recheck previous group/contrast annotations? Requires
|
postfix |
Optional string to append to saved results. Useful if need to run multiple meta-analyses on the same series but with different contrasts. |
port |
See |
Click the Download icon and fill in the Group name column and optionally the Pairs column. Then save and upload the filled in metadata csv. After doing so, select a test and control group to compare and click the + icon to add the contrast. Repeat previous step to add additional contrasts. After control and test samples have been added for all contrasts that you wish to include, click the Done button. Repeat for all GSEs.
Paired samples (e.g. the same subject before and after treatment) can be specified by filling out the Pairs column before uploading the metadata.
For each GSE, analysis results are saved in the corresponding GSE
folder in data_dir
that was created by get_raw
. If analyses
needs to be repeated, previous results can be reloaded with load_diff
and supplied to the prev_anals
parameter. In this case, previous
selections, names, and pairs will be reused.
List of named lists, one for each GSE. Each named list contains:
pdata |
data.frame with phenotype data for selected samples.
Columns |
top_tables |
List with results of |
ebayes_sv |
Results of call to |
annot |
Value of |
library(lydata)
# location of raw data
data_dir <- system.file("extdata", package = "lydata")
# gather GSE names
gse_names <- c("GSE9601", "GSE15069", "GSE50841", "GSE34817", "GSE29689")
# load first eset
esets <- load_raw(gse_names[1], data_dir)
# run analysis (opens GUI)
# anals_old <- diff_expr(esets, data_dir)
# re-run analysis on first eset
prev <- load_diff(gse_names[1], data_dir)
anals <- diff_expr(esets[1], data_dir, prev_anals = prev)
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