# HG changeset patch # User grau # Date 1383861565 18000 # Node ID fa520092c603a609085f44c11b770a396c81e1bc # Parent 247f7edbe7f8dab304e3a2038b3c7b2ba278a905 Uploaded diff -r 247f7edbe7f8 -r fa520092c603 DimontDataExtractor.xml --- a/DimontDataExtractor.xml Thu Nov 07 15:17:42 2013 -0500 +++ b/DimontDataExtractor.xml Thu Nov 07 16:59:25 2013 -0500 @@ -1,21 +1,21 @@ - + Extracts genomic regions specified in a BED-like file format in the annotated FastA format as required by Dimont -extract_data_single_galaxy.pl $genomefa $regions $chromcol $startcol $seccol $seccoord $width $statcol extracted.fa +extract_data_single_galaxy.pl $genomefa $regions $chromcol $startcol $seccol $seccoord $width $statcol $extracted - - + + - - + + - + @@ -28,7 +28,7 @@ - + @@ -39,7 +39,7 @@ - + diff -r 247f7edbe7f8 -r fa520092c603 DimontPredictorWeb.jar Binary file DimontPredictorWeb.jar has changed diff -r 247f7edbe7f8 -r fa520092c603 DimontPredictorWeb.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/DimontPredictorWeb.xml Thu Nov 07 16:59:25 2013 -0500 @@ -0,0 +1,107 @@ + +DimontPredictor for predicting binding sites using a Dimont model +java -Xms256M -Xmx2G -jar \$JAR_PATH/DimontPredictorWeb.jar --run $script_file $summary $summary.id $__new_file_path__ $summary.extra_files_path + + + + + + + + + + + + + + + + + + + + + JAR_PATH + java + + + +<DimontPredictor_ps_Dimont> +<value> +${DimontPredictor_ps_Dimont}</value> +<extension> +${DimontPredictor_ps_Dimont.ext}</extension> +</DimontPredictor_ps_Dimont> + +<DimontPredictor_ps_Input_sequences> +<value> +${DimontPredictor_ps_Input_sequences}</value> +<extension> +${DimontPredictor_ps_Input_sequences.ext}</extension> +</DimontPredictor_ps_Input_sequences> + +<DimontPredictor_ps_Value_tag> +${DimontPredictor_ps_Value_tag}</DimontPredictor_ps_Value_tag> + +<DimontPredictor_ps_Weighting_factor> +${DimontPredictor_ps_Weighting_factor}</DimontPredictor_ps_Weighting_factor> + +<DimontPredictor_ps_p_value> +${DimontPredictor_ps_p_value}</DimontPredictor_ps_p_value> + + + + + + + + + + + + + + + + + + +**DimontPredictor** allows for predicting binding sites in new data using a previously trained Dimont model. For training a Dimont model see tool "Dimont". + +This tool may be useful if you, for instance, want to predict binding sites of a previously discovered motifs in other data sets, or if you want to try different p-values for filtering predictions. + +Input sequences must be supplied in an annotated FastA format as a file uploaded by the "Upload File" task in section "Get Data" of Galaxy or generated using the "Dimont Data Extractor" tool. +In the annotation of each sequence, you need to provide a value that reflects the confidence that this sequence is bound by the factor of interest. +Such confidences may be peak statistics (e.g., number of fragments under a peak) for ChIP data or signal intensities for PBM data. + +For instance, an annotated FastA file for ChIP-exo data could look like:: + + > signal: 515 + ggccatgtgtatttttttaaatttccac... + > signal: 199 + GGTCCCCTGGGAGGATGGGGACGTGCTG... + ... + +where the confidence for the first two sequences amounts to 515 and 199, respectively. +The FastA comment may contain additional annotations of the format ``key1 : value1; key2: value2;...``. +We also provide an example_ input file. + +Accordingly, you would need to set the parameter "Value tag" to ``signal`` for this input file. + +The parameter "Weighting factor" defines the proportion of sequences that you expect to be bound by the targeted factor with high confidence. For ChIP data, the default value of ``0.2`` typically works well. +For PBM data, containing a large number of unspecific probes, this parameter should be set to a lower value, e.g. ``0.01``. + +The parameter "p-value" defines a threshold on the p-values of predicted binding sites, and only binding sites with a lower p-value are reported by DimontPredictor. +The Dimont tool uses a p-value threshold of ``1E-3``, which is also the default value of DimontPredictor. + +You can also install this web-application within your local Galaxy server. Instructions can be found at the Dimont_ page of Jstacs. +There you can also download a command line version of DimontPredictor. + +If you experience problems using DimontPredictor, please contact_ us. + +.. _example: http://www.jstacs.de/downloads/dimont-example.fa +.. _Dimont: http://jstacs.de/index.php/Dimont +.. _contact: mailto:grau@informatik.uni-halle.de + + + diff -r 247f7edbe7f8 -r fa520092c603 DimontWeb.xml --- a/DimontWeb.xml Thu Nov 07 15:17:42 2013 -0500 +++ b/DimontWeb.xml Thu Nov 07 16:59:25 2013 -0500 @@ -1,5 +1,5 @@ -Dimont, a universal tool for de-novo motif discovery (beta). +Dimont, a universal tool for de-novo motif discovery. java -Xms256M -Xmx2G -jar \$JAR_PATH/DimontWeb.jar --run $script_file $summary $summary.id $__new_file_path__ $summary.extra_files_path @@ -107,7 +107,7 @@ **Dimont** is a universal tool for de-novo motif discovery. Dimont has successfully been applied to ChIP-seq, ChIP-exo and protein-binding microarray (PBM) data. -Input sequences must be supplied in an annotated FastA format as a file uploaded by the "Upload File" task in section "Get Data" of Galaxy. +Input sequences must be supplied in an annotated FastA format as a file uploaded by the "Upload File" task in section "Get Data" of Galaxy or generated using the "Dimont Data Extractor" tool. In the annotation of each sequence, you need to provide a value that reflects the confidence that this sequence is bound by the factor of interest. Such confidences may be peak statistics (e.g., number of fragments under a peak) for ChIP data or signal intensities for PBM data. In addition, you need to provide an anchor position within the sequence. In case of ChIP data, this anchor position could for instance be the peak summit. diff -r 247f7edbe7f8 -r fa520092c603 extract_data_single_galaxy.pl --- a/extract_data_single_galaxy.pl Thu Nov 07 15:17:42 2013 -0500 +++ b/extract_data_single_galaxy.pl Thu Nov 07 16:59:25 2013 -0500 @@ -80,7 +80,7 @@ } close(IN); -print "Read input file ".$bed."\n"; +#print "Read input file ".$bed."\n"; if($sort){ diff -r 247f7edbe7f8 -r fa520092c603 test-data/.DS_Store Binary file test-data/.DS_Store has changed diff -r 247f7edbe7f8 -r fa520092c603 test-data/predictor_test.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/predictor_test.xml Thu Nov 07 16:59:25 2013 -0500 @@ -0,0 +1,285 @@ + +de.jstacs.data.alphabets.DNAAlphabetContainerjava.lang.Integer0[D2-2.034267647272289-0.2525781403291907de.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.GenDisMixClassifierParameterSet + + + + + +java.lang.Integer8de.jstacs.parameters.SelectionParameter +java.lang.Stringalgorithmjava.lang.Stringthe algorithm that should be used for numerical optimizationde.jstacs.DataTypeBYTEjava.lang.Booleantruejava.lang.Booleantruenulljava.lang.Booleantruede.jstacs.parameters.SimpleParameterSet + +java.lang.Integer13de.jstacs.parameters.SimpleParameter +java.lang.Stringsteepest descentnullde.jstacs.DataTypeBYTEjava.lang.Booleanfalsejava.lang.Booleantruejava.lang.Stringjava.lang.Booleantruenullnulljava.lang.Byte16 +de.jstacs.parameters.SimpleParameter +java.lang.Stringconjugate gradients (F., R.)nullde.jstacs.DataTypeBYTEjava.lang.Booleanfalsejava.lang.Booleantruejava.lang.Stringjava.lang.Booleantruenullnulljava.lang.Byte17 +de.jstacs.parameters.SimpleParameter +java.lang.Stringconjugate gradients (P., R. positive)nullde.jstacs.DataTypeBYTEjava.lang.Booleanfalsejava.lang.Booleantruejava.lang.Stringjava.lang.Booleantruenullnulljava.lang.Byte18 +de.jstacs.parameters.SimpleParameter +java.lang.Stringquasi newton (D., F., P.)nullde.jstacs.DataTypeBYTEjava.lang.Booleanfalsejava.lang.Booleantruejava.lang.Stringjava.lang.Booleantruenullnulljava.lang.Byte19 +de.jstacs.parameters.SimpleParameter +java.lang.Stringquasi newton (B., F., G., S.)nullde.jstacs.DataTypeBYTEjava.lang.Booleanfalsejava.lang.Booleantruejava.lang.Stringjava.lang.Booleantruenullnulljava.lang.Byte20 +de.jstacs.parameters.SimpleParameter +java.lang.Stringlimited memory quasi newton (B., F., G., S.; n=3)nullde.jstacs.DataTypeBYTEjava.lang.Booleanfalsejava.lang.Booleantruejava.lang.Stringjava.lang.Booleantruenullnulljava.lang.Byte3 +de.jstacs.parameters.SimpleParameter +java.lang.Stringlimited memory quasi newton (B., F., G., S.; n=4)nullde.jstacs.DataTypeBYTEjava.lang.Booleanfalsejava.lang.Booleantruejava.lang.Stringjava.lang.Booleantruenullnulljava.lang.Byte4 +de.jstacs.parameters.SimpleParameter +java.lang.Stringlimited memory quasi newton (B., F., G., S.; n=5)nullde.jstacs.DataTypeBYTEjava.lang.Booleanfalsejava.lang.Booleantruejava.lang.Stringjava.lang.Booleantruenullnulljava.lang.Byte5 +de.jstacs.parameters.SimpleParameter +java.lang.Stringlimited memory quasi newton (B., F., G., S.; n=6)nullde.jstacs.DataTypeBYTEjava.lang.Booleanfalsejava.lang.Booleantruejava.lang.Stringjava.lang.Booleantruenullnulljava.lang.Byte6 +de.jstacs.parameters.SimpleParameter +java.lang.Stringlimited memory quasi newton (B., F., G., S.; n=7)nullde.jstacs.DataTypeBYTEjava.lang.Booleanfalsejava.lang.Booleantruejava.lang.Stringjava.lang.Booleantruenullnulljava.lang.Byte7 +de.jstacs.parameters.SimpleParameter +java.lang.Stringlimited memory quasi newton (B., F., G., S.; n=8)nullde.jstacs.DataTypeBYTEjava.lang.Booleanfalsejava.lang.Booleantruejava.lang.Stringjava.lang.Booleantruenullnulljava.lang.Byte8 +de.jstacs.parameters.SimpleParameter +java.lang.Stringlimited memory quasi newton (B., F., G., S.; n=9)nullde.jstacs.DataTypeBYTEjava.lang.Booleanfalsejava.lang.Booleantruejava.lang.Stringjava.lang.Booleantruenullnulljava.lang.Byte9 +de.jstacs.parameters.SimpleParameter +java.lang.Stringlimited memory quasi newton (B., F., G., S.; n=10)nullde.jstacs.DataTypeBYTEjava.lang.Booleanfalsejava.lang.Booleantruejava.lang.Stringjava.lang.Booleantruenullnulljava.lang.Byte10 + + +java.lang.Integer2java.lang.Integer4 +de.jstacs.parameters.SelectionParameter +java.lang.Stringtermination conditionjava.lang.Stringthe terminantion condition for stopping the training algorithmde.jstacs.DataTypePARAMETERSETjava.lang.Booleantruejava.lang.Booleantruenulljava.lang.Booleantruede.jstacs.parameters.SimpleParameterSet + +java.lang.Integer8de.jstacs.parameters.ParameterSetContainer +java.lang.StringAbsoluteValueConditionParameterSetjava.lang.Stringde.jstacs.DataTypePARAMETERSETnulljava.lang.Classde.jstacs.algorithms.optimization.termination.AbsoluteValueCondition$AbsoluteValueConditionParameterSet +de.jstacs.parameters.ParameterSetContainer +java.lang.StringCombinedConditionParameterSetjava.lang.Stringde.jstacs.DataTypePARAMETERSETnulljava.lang.Classde.jstacs.algorithms.optimization.termination.CombinedCondition$CombinedConditionParameterSet +de.jstacs.parameters.ParameterSetContainer +java.lang.StringIterationConditionParameterSetjava.lang.Stringde.jstacs.DataTypePARAMETERSETnulljava.lang.Classde.jstacs.algorithms.optimization.termination.IterationCondition$IterationConditionParameterSet +de.jstacs.parameters.ParameterSetContainer +java.lang.StringMultipleIterationsConditionParameterSetjava.lang.Stringde.jstacs.DataTypePARAMETERSETnulljava.lang.Classde.jstacs.algorithms.optimization.termination.MultipleIterationsCondition$MultipleIterationsConditionParameterSet +de.jstacs.parameters.ParameterSetContainer +java.lang.StringSmallDifferenceOfFunctionEvaluationsConditionParameterSetjava.lang.Stringde.jstacs.DataTypePARAMETERSETnullde.jstacs.algorithms.optimization.termination.SmallDifferenceOfFunctionEvaluationsCondition$SmallDifferenceOfFunctionEvaluationsConditionParameterSet + + + +java.lang.Integer1de.jstacs.parameters.SimpleParameter +java.lang.Stringepsilonjava.lang.Stringthe epsilon for the difference of function evaluations used for deciding whether to stop the algorithm or notde.jstacs.DataTypeDOUBLEjava.lang.Booleantruejava.lang.Booleantruenulljava.lang.Booleantruede.jstacs.parameters.validation.NumberValidator +java.lang.Stringjava.lang.Doublejava.lang.String0.0java.lang.String1.7976931348623157E308 +java.lang.Double1.0E-6java.lang.Double1.0E-4 + + + +java.lang.Classde.jstacs.algorithms.optimization.termination.SmallDifferenceOfFunctionEvaluationsCondition + +de.jstacs.parameters.ParameterSetContainer +java.lang.StringSmallGradientConditonParameterSetjava.lang.Stringde.jstacs.DataTypePARAMETERSETnulljava.lang.Classde.jstacs.algorithms.optimization.termination.SmallGradientConditon$SmallGradientConditonParameterSet +de.jstacs.parameters.ParameterSetContainer +java.lang.StringSmallStepConditionParameterSetjava.lang.Stringde.jstacs.DataTypePARAMETERSETnulljava.lang.Classde.jstacs.algorithms.optimization.termination.SmallStepCondition$SmallStepConditionParameterSet +de.jstacs.parameters.ParameterSetContainer +java.lang.StringTimeConditionParameterSetjava.lang.Stringde.jstacs.DataTypePARAMETERSETnulljava.lang.Classde.jstacs.algorithms.optimization.termination.TimeCondition$TimeConditionParameterSet + + +java.lang.Integer4java.lang.Integer4 +de.jstacs.parameters.SimpleParameter +java.lang.Stringline epsilonjava.lang.Stringthe threshold for stopping the line search in the numerical trainingde.jstacs.DataTypeDOUBLEjava.lang.Booleantruejava.lang.Booleantruenulljava.lang.Booleantruede.jstacs.parameters.validation.NumberValidator +java.lang.Stringjava.lang.Doublejava.lang.String0.0java.lang.String1.7976931348623157E308 +java.lang.Double1.0E-9java.lang.Double1.0E-5 +de.jstacs.parameters.SimpleParameter +java.lang.Stringstart distancejava.lang.Stringthe start distance for the line search in the numerical trainingde.jstacs.DataTypeDOUBLEjava.lang.Booleantruejava.lang.Booleantruenulljava.lang.Booleantruede.jstacs.parameters.validation.NumberValidator +java.lang.Stringjava.lang.Doublejava.lang.String0.0java.lang.String1.7976931348623157E308 +java.lang.Double1.0java.lang.Double1.0 +de.jstacs.parameters.SimpleParameter +java.lang.Stringfree parametersjava.lang.StringIndicates whether only the free parameters or all parameters should be used.de.jstacs.DataTypeBOOLEANjava.lang.Booleantruejava.lang.Booleantruejava.lang.Stringjava.lang.Booleantruenulljava.lang.Booleanfalsejava.lang.Booleanfalse +de.jstacs.parameters.EnumParameter +java.lang.StringKindOfParameterjava.lang.StringIndicates whether special plugIn parameters or the zero vector should be used as start parameters. For non-concave problems it is highly recommended to use plugIn parameters.de.jstacs.DataTypeSTRINGjava.lang.Booleantruejava.lang.Booleantruenulljava.lang.Booleantruede.jstacs.parameters.SimpleParameterSet + +java.lang.Integer3de.jstacs.parameters.SimpleParameter +java.lang.StringZEROSnullde.jstacs.DataTypeSTRINGjava.lang.Booleanfalsejava.lang.Booleantruejava.lang.Stringjava.lang.Booleanfalsenullnulljava.lang.StringZEROS +de.jstacs.parameters.SimpleParameter +java.lang.StringLASTnullde.jstacs.DataTypeSTRINGjava.lang.Booleanfalsejava.lang.Booleantruejava.lang.Stringjava.lang.Booleanfalsenullnulljava.lang.StringLAST +de.jstacs.parameters.SimpleParameter +java.lang.StringPLUGINnullde.jstacs.DataTypeSTRINGjava.lang.Booleanfalsejava.lang.Booleantruejava.lang.Stringjava.lang.Booleanfalsenullnulljava.lang.StringPLUGIN + + +java.lang.Integer2java.lang.Integer2java.lang.StringPLUGINjava.lang.StringPLUGINjava.lang.Classde.jstacs.classifiers.differentiableSequenceScoreBased.OptimizableFunction$KindOfParameter +de.jstacs.parameters.SimpleParameter +java.lang.StringNormalizejava.lang.StringIf true the conditional likelihood will be normalized to the number of data sets.de.jstacs.DataTypeBOOLEANjava.lang.Booleantruejava.lang.Booleantruejava.lang.Stringjava.lang.Booleantruenulljava.lang.Booleantruejava.lang.Booleantrue +de.jstacs.parameters.SimpleParameter +java.lang.StringThreadsjava.lang.StringThe number of threads that is used during an optimization.de.jstacs.DataTypeINTjava.lang.Booleantruejava.lang.Booleantruenulljava.lang.Booleantruede.jstacs.parameters.validation.NumberValidator +java.lang.Stringjava.lang.Integerjava.lang.String1java.lang.String128 +java.lang.Integer1java.lang.Integer1 + + + +java.lang.Classde.jstacs.classifiers.differentiableSequenceScoreBased.gendismix.GenDisMixClassifier + +java.lang.Booleantruede.jstacs.parameters.SelectionParameter +java.lang.StringAlphabetjava.lang.StringThe alphabet the model works onde.jstacs.DataTypePARAMETERSETjava.lang.Booleantruejava.lang.Booleantruenulljava.lang.Booleantruede.jstacs.parameters.SimpleParameterSet + +java.lang.Integer2de.jstacs.parameters.ParameterSetContainer +java.lang.StringAlphabetContainerParameterSetjava.lang.Stringde.jstacs.DataTypePARAMETERSETnullde.jstacs.data.AlphabetContainerParameterSet + + + + + +java.lang.Integer1de.jstacs.parameters.SelectionParameter +java.lang.StringAlphabetjava.lang.StringSelect a discrete alphabetde.jstacs.DataTypePARAMETERSETjava.lang.Booleantruejava.lang.Booleanfalsenulljava.lang.Booleantruede.jstacs.parameters.SimpleParameterSet + +java.lang.Integer4de.jstacs.parameters.ParameterSetContainer +java.lang.StringDNAAlphabetParameterSetjava.lang.Stringde.jstacs.DataTypePARAMETERSETnullde.jstacs.data.alphabets.DNAAlphabet$DNAAlphabetParameterSet +de.jstacs.parameters.ParameterSetContainer +java.lang.StringProteinAlphabetParameterSetjava.lang.Stringde.jstacs.DataTypePARAMETERSETnullde.jstacs.data.alphabets.ProteinAlphabet$ProteinAlphabetParameterSet +de.jstacs.parameters.ParameterSetContainer +java.lang.StringGenericComplementableDiscreteAlphabetParameterSetjava.lang.Stringde.jstacs.DataTypePARAMETERSETnullde.jstacs.data.alphabets.GenericComplementableDiscreteAlphabet$GenericComplementableDiscreteAlphabetParameterSet + + + +java.lang.Integer1de.jstacs.parameters.SimpleParameter +java.lang.StringValues of the index for computings the reverse complementjava.lang.Stringde.jstacs.DataTypeSTRINGjava.lang.Booleantruejava.lang.Booleanfalsenulljava.lang.Booleanfalsenullnullnull + + + +java.lang.Classde.jstacs.data.alphabets.GenericComplementableDiscreteAlphabet + +de.jstacs.parameters.ParameterSetContainer +java.lang.StringDiscreteAlphabetParameterSetjava.lang.Stringde.jstacs.DataTypePARAMETERSETnullde.jstacs.data.alphabets.DiscreteAlphabet$DiscreteAlphabetParameterSet + + + +java.lang.Integer2de.jstacs.parameters.SimpleParameter +java.lang.StringValues of the alphabetjava.lang.StringThe possible values of the discrete alphabet.If the alphabet consists of single characters, e.g. A, C, G, and T, the values may be set as a single string, e.g. &quot;ACGT&quot;.If the alphabet consists of multi-character symbols, e.g. Gly, Asp, Ser,the symbols must be separated by spaces.de.jstacs.DataTypeSTRINGjava.lang.Booleantruejava.lang.Booleanfalsenulljava.lang.Booleanfalsenullnullnull +de.jstacs.parameters.SelectionParameter +java.lang.StringCase insensitivejava.lang.StringUse the alphabet case insensitivede.jstacs.DataTypeBOOLEANjava.lang.Booleantruejava.lang.Booleanfalsenulljava.lang.Booleantruede.jstacs.parameters.SimpleParameterSet + +java.lang.Integer2de.jstacs.parameters.SimpleParameter +java.lang.StringCase insensitivenullde.jstacs.DataTypeBOOLEANjava.lang.Booleanfalsejava.lang.Booleantruejava.lang.Stringjava.lang.Booleantruenullnulljava.lang.Booleantrue +de.jstacs.parameters.SimpleParameter +java.lang.StringCase sensitivenullde.jstacs.DataTypeBOOLEANjava.lang.Booleanfalsejava.lang.Booleantruejava.lang.Stringjava.lang.Booleantruenullnulljava.lang.Booleanfalse + + +java.lang.Integer0java.lang.Integer0 + + + +java.lang.Classde.jstacs.data.alphabets.DiscreteAlphabet + + + +java.lang.Integer0java.lang.Integer0 + + + +java.lang.Classde.jstacs.data.AlphabetContainer + +de.jstacs.data.AlphabetContainer$AlphabetContainerTypeDISCRETEjava.lang.Booleantrue + +de.jstacs.parameters.ParameterSetContainer +java.lang.StringDNAAlphabetContainerParameterSetjava.lang.Stringde.jstacs.DataTypePARAMETERSETnullde.jstacs.data.alphabets.DNAAlphabetContainer$DNAAlphabetContainerParameterSet + + +java.lang.Integer1java.lang.Integer0 +de.jstacs.parameters.SimpleParameter +java.lang.StringLengthjava.lang.StringThe length of sequences the model can work onde.jstacs.DataTypeINTjava.lang.Booleantruejava.lang.Booleantruenulljava.lang.Booleantruede.jstacs.parameters.validation.NumberValidator +java.lang.Stringjava.lang.Integerjava.lang.String0java.lang.String0 +java.lang.Integer0java.lang.Integer0 + +java.lang.Booleanfalsejava.lang.Double-0.29019836129972626[Lde.jstacs.sequenceScores.statisticalModels.differentiable.DifferentiableStatisticalModel;2projects.dimont.ThresholdedStrandChIPper +java.lang.Integer0java.lang.Integer1java.lang.Booleanfalse[Lde.jstacs.sequenceScores.statisticalModels.differentiable.DifferentiableStatisticalModel;1de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.MarkovModelDiffSM + +de.jstacs.data.alphabets.DNAAlphabetContainerjava.lang.Integer7[Lde.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree;7de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree +java.lang.Integer0[I0de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree$TreeElement +java.lang.Integer0java.lang.Integer-1null[Lde.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter;4de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter +java.lang.Double-1.8882500938776798java.lang.Byte0java.lang.Integer0java.lang.Double1.0java.lang.Integer0[[I0java.lang.Double1.0java.lang.Booleantruejava.lang.Double0.0java.lang.Double0.0 +de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter +java.lang.Double-2.3929793553147585java.lang.Byte1java.lang.Integer1java.lang.Double1.0java.lang.Integer0[[I0java.lang.Double1.0java.lang.Booleantruejava.lang.Double0.0java.lang.Double0.0 +de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter +java.lang.Double-0.27411896862354784java.lang.Byte2java.lang.Integer2java.lang.Double1.0java.lang.Integer0[[I0java.lang.Double1.0java.lang.Booleantruejava.lang.Double0.0java.lang.Double0.0 +de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter +java.lang.Double-3.074727770552047java.lang.Byte3java.lang.Integer3java.lang.Double1.0java.lang.Integer0[[I0java.lang.Double1.0java.lang.Booleantruejava.lang.Double0.0java.lang.Double0.0 + +java.lang.Integer-1[I0 +de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree +java.lang.Integer1[I0de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameterTree$TreeElement +java.lang.Integer0java.lang.Integer-1null[Lde.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter;4de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter +java.lang.Double-3.143173615307912java.lang.Byte0java.lang.Integer4java.lang.Double1.0java.lang.Integer1[[I0java.lang.Double1.0java.lang.Booleantruejava.lang.Double0.0java.lang.Double0.0 +de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter +java.lang.Double-3.0349593264798793java.lang.Byte1java.lang.Integer5java.lang.Double1.0java.lang.Integer1[[I0java.lang.Double1.0java.lang.Booleantruejava.lang.Double0.0java.lang.Double0.0 +de.jstacs.sequenceScores.statisticalModels.differentiable.directedGraphicalModels.BNDiffSMParameter 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