Perform customizable filtering and the main DTU calling with DRIMSeq.
run_drimseq( counts, tx2gene, pd, id_col = NULL, cond_col, cond_levels = NULL, filtering_strategy = "bulk", add_pseudocount = FALSE, BPPARAM = BiocParallel::SerialParam(), force_dense = TRUE, subset_feature = NULL, subset_sample = NULL, carry_over_metadata = TRUE, filter_only = FALSE, ... )
counts  Can be either:


tx2gene  Data frame, where the first column consists of feature identifiers and the second column consists of corresponding gene identifiers. Feature identifiers must match with the rownames of the counts object. If a Seurat object is provided in 
pd  Data frame with at least a column of sample/cell identifiers (rownames or specified in 
id_col  Name of the column in 
cond_col  Name of the column in 
cond_levels  Define two levels/groups of 
filtering_strategy  Define the filtering strategy to reduce and noise and increase statistical power.

add_pseudocount  Define 
BPPARAM  If multicore processing should be used, specify a 
force_dense  If you do not want to use a sparse Matrix for DRIMSeq calculations, you can force a dense conversion by specifying 
subset_feature  Subsets the provided count matrix to only specified features. Can be names, indices or logicals. 
subset_sample  Subsets the provided count matrix to only specified samples. Can be names, indices or logicals. 
carry_over_metadata  Specify if compatible additional columns of 
filter_only  Return filtered (sparse) matrix, without performing DRIMSeq statistical computations. 
...  Arguments passed on to

dturtle
object with the key results, that can be used in the DTUrtle steps hereafter. The object is just a easily accessible list with the following items:
meta_table_gene
: Data frame of the expressedin ratio of all genes. Expressedin is defined as expression > 0. Can be used to add gene level metainformation for plotting.
meta_table_tx
: Data frame of the expressedin ratio of all transcripts. Expressedin is defined as expression > 0. Can be used to add transcript level metainformation for plotting.
meta_table_sample
: Data frame of the provided sample level information (pd
). Can be used to add sample level metainformation for plotting.
drim
: Results of the DRIMSeq statistical computations (dmTest()
).
design
: Design matrix generated from the specified pd
columns.
group
: Vector which sample/cell belongs to which comparison group.
used_filtering_options
: List of the used filtering options.
add_pseudocount
: Keeps track if pseudocount was added in comparison.
If filter_only=TRUE
, only the filtered (sparse) matrix is returned.
Run the main DRIMSeq pipeline, including generation of a design matrix, gene/feature filtering and running the statistical computations of DRIMSeq (dmPrecision()
, dmFit()
and dmTest()
)
Other DTUrtle DTU:
combine_to_matrix()
,
import_counts()
,
posthoc_and_stager()
,
priming_bias_detection_probability()