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sc3-sc3-prepare.xml
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sc3-sc3-prepare.xml
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<tool id="sc3-prepare" name="SC3 read scater object" version="0.1.0">
<description>Loads normalised Scater object into a SC3 object</description>
<macros>
<import>macros.xml</import>
</macros>
<expand macro="requirements" />
<command detect_errors="exit_code"><![CDATA[
sc3-sc3-prepare.R -d SCATER-OBJECT -o OUTPUT-OBJECT-FILE
]]></command>
<inputs>
<param type="data" name="input1" format="rds" />
</inputs>
<outputs>
<data name="output1" format="rds" from_work_dir="R_sc3_prepared.rds" />
</outputs>
<tests>
<test>
<param name="input1" value="scater_log.rds"/>
<output name="output1" file="pbmc3k_scater_log.rds"/>
</test>
</tests>
<help><![CDATA[
Usage: /Users/ct5/anaconda3/envs/galaxy/bin/sc3-sc3-prepare.R [options]
Options:
-i INPUT-OBJECT-FILE, --input-object-file=INPUT-OBJECT-FILE
File name in which a serialized R SingleCellExperiment object where object matrix found
-f GENE-FILTER, --gene-filter=GENE-FILTER
A boolean variable which defines whether to perform gene filtering before SC3 clustering.
-p PCT-DROPOUT-MIN, --pct-dropout-min=PCT-DROPOUT-MIN
If gene_filter = TRUE, then genes with percent of dropouts smaller than pct_dropout_min are filtered out before clustering.
-q PCT-DROPOUT-MAX, --pct-dropout-max=PCT-DROPOUT-MAX
If gene_filter = TRUE, then genes with percent of dropouts larger than pct_dropout_max are filtered out before clustering.
-d D-REGION-MIN, --d-region-min=D-REGION-MIN
Defines the minimum number of eigenvectors used for kmeans clustering as a fraction of the total number of cells. Default is 0.04. See SC3 paper for more details.
-e D-REGION-MAX, --d-region-max=D-REGION-MAX
Defines the maximum number of eigenvectors used for kmeans clustering as a fraction of the total number of cells. Default is 0.07. See SC3 paper for more details.
-n SVM-NUM-CELLS, --svm-num-cells=SVM-NUM-CELLS
Number of randomly selected training cells to be used for SVM prediction. Default is NULL.
-r SVM-TRAIN-INDS, --svm-train-inds=SVM-TRAIN-INDS
Text file with one integer per line. Will be used to create a numeric vector defining indices of training cells that should be used for SVM training. The default is NULL.
-m SVM-MAX, --svm-max=SVM-MAX
Define the maximum number of cells below which SVM are not run.
-t N-CORES, --n-cores=N-CORES
Number of threads/cores to be used in the user's machine.
-s RAND-SEED, --rand-seed=RAND-SEED
sets the seed of the random number generator. SC3 is a stochastic method, so setting the rand_seed to a fixed values can be used for reproducibility purposes.
-k KMEANS-NSTART, --kmeans-nstart=KMEANS-NSTART
nstart parameter passed to kmeans function. Default is 1000 for up to 2000 cells and 50 for more than 2000 cells.
-a KMEANS-ITER-MAX, --kmeans-iter-max=KMEANS-ITER-MAX
iter.max parameter passed to kmeans function. Default is 1e+09.
-o OUTPUT-OBJECT-FILE, --output-object-file=OUTPUT-OBJECT-FILE
File name in which to store serialized R object of type 'SingleCellExperiment'.'
-h, --help
Show this help message and exit
]]></help>
<expand macro="citations" />
</tool>