############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.14-bioc/R/bin/R CMD build --keep-empty-dirs --no-resave-data sparseDOSSA ### ############################################################################## ############################################################################## * checking for file ‘sparseDOSSA/DESCRIPTION’ ... OK * preparing ‘sparseDOSSA’: * checking DESCRIPTION meta-information ... OK * installing the package to build vignettes * creating vignettes ... ERROR --- re-building ‘sparsedossa-vignette.Rmd’ using rmarkdown sparseDOSSA package:sparseDOSSA R Documentation _S_p_a_r_s_e _D_a_t_a _O_b_s_e_r_v_a_t_i_o_n_s _f_o_r _S_i_m_u_l_a_t_i_n_g _S_y_n_t_h_e_t_i_c _A_b_u_n_d_a_n_c_e _D_e_s_c_r_i_p_t_i_o_n: Sparse Data Observations for Simulating Synthetic Abundance _U_s_a_g_e: sparseDOSSA( strNormalizedFileName = "SyntheticMicrobiome.pcl", strCountFileName = "SyntheticMicrobiome-Counts.pcl", parameter_filename = "SyntheticMicrobiomeParameterFile.txt", bugs_to_spike = 0, spikeFile = NA, calibrate = NA, datasetCount = 1, read_depth = 8030, number_features = 300, bugBugCorr = "0.5", spikeCount = "1", lefse_file = NULL, percent_spiked = 0.03, minLevelPercent = 0.1, number_samples = 50, max_percent_outliers = 0.05, number_metadata = 5, spikeStrength = "1.0", seed = NA, percent_outlier_spikins = 0.05, minOccurence = 0, verbose = TRUE, minSample = 0, scalePercentZeros = 1, association_type = "linear", noZeroInflate = FALSE, noRunMetadata = FALSE, runBugBug = FALSE ) _A_r_g_u_m_e_n_t_s: strNormalizedFileName: This output file records the synthetic microbiome data for null community (no spike-in and outliers), outlier-added community without spike-in and final spiked data. We put samples in columns and features in rows. The first chunk of the file is metadata, with row names Metadata_. The second chunk is for null community, with row names Feature_Lognormal_. The third chunk is for outlier-introduced community, with row names Feature_Outlier_*. The last chunk is for spiked data, with row names Feature_spike. This file records relative abundance data. strCountFileName: This output file has the same organization as the file strNormalizedFileName but records raw counts data. parameter_filename: This output file records diagnostic information and values of model parameters as well as the spike-in assignment. The most part of this file is used only for debugging. Users can focus on lines after Minimum Spiked-in Samples. Those lines record which metadata are correlated with which feature. The format is all metadata that are correlated with a specific features are listed under the name of the feature. bugs_to_spike: Number of bugs to correlate with others. A non-negative integer value is expected. spikeFile: The name of the file where the correlation values are stored. Should have fields `Domain`, `Range`, and `Correlation`. calibrate: Calibration file for generating the random log normal data. TSV file (column = feature). datasetCount: The number of bug-bug spiked datasets to generate. A positive integer value is expected. read_depth: Simulated read depth for counts. A positive integer value is expected. number_features: The number of features per sample to create. A positive integer value is expected. bugBugCorr: A vector of string separated values for the correlation values of the pairwise bug-bug associations. This is the correlation of the log-counts. Values are comma-separated; for example: 0.7,0.5. Default is 0.5. spikeCount: Counts of spiked metadata used in the spike-in dataset - These values should be comma delimited values, in the order of the spikeStrength values (if given), Can be one value, in this case the value will be repeated to pair with the spikeCount values (if multiple are present). For example 1,2,3. lefse_file: Folder containing lefSe inputs. percent_spiked: The percent of features spiked-in. A real number between 0 and 1 is expected. minLevelPercent: Minimum percent of measurements out of the total a level can have in a discontinuous metadata (rounded up to the nearest count). A real number between 0 and 1 is expected. number_samples: The number of samples to generate. A positive integer greater than 0 is expected. max_percent_outliers: The maximum percent of outliers to spike into a sample. A real number between 0 and 1 is expected. number_metadata: Indicates how many metadata are created, number_metadata*2 = number continuous metadata, number_metadata = number binary metadata, number_metadata = number quaternary metadata, A positive integer greater than 0 is expected. spikeStrength: Strength of the metadata association with the spiked-in feature, These values should be comma delimited and in the order of the spikeCount values (if given),Can be one value, in this case the value will be repeated to pair with the spikeStrength values (if multiple are present). For example 0.2,0.3,0.4. seed: A seed to freeze the random generation of counts/relative abundance,If left as default (NA), generation is random - If seeded, data generation will be random within a run but identical if ran again under the same settings,an integer is expected. percent_outlier_spikins: The percent of samples to spike in outliers. A real number between 0 to 1 is expected. minOccurence: Minimum counts a bug can have for the occurrence quality control filter used when creating bugs (filtering minimum number of counts in a minimum number of samples). A positive integer is expected. verbose: If True logging and plotting is made by the underlying methodology. This is a flag, it is either included or not included in the command line, no value needed. minSample: Minimum samples a bug can be in for the occurrence quality control filter used when creating bugs (filtering minimum number of counts in a minimum number of samples). A positive integer is expected. scalePercentZeros: A scale used to multiply the percent zeros of all features across the sample after it is derived from the relationships with it and the feature abundance or calibration file. Requires a number greater than 0. A number greater than 1 increases sparsity, a number less than 1 decreases sparsity, O removes sparsity, 1 (default) does not change the value and the value. association_type: The type of association to generate. Options are 'linear' or 'rounded_linear'. noZeroInflate: If given, zero inflation is not used when generating a feature. This is a flag, it is either included or not included in the command line, no value needed. noRunMetadata: If given, no metadata files are generated, This is a flag, it is either included or not included in the command line, no value needed. runBugBug: If given, bug-bug interaction files are generated in addition to any metadata files. This is a flag, it is either included or not included in the command line, no value needed. _V_a_l_u_e: A list contains the names of the output files. _A_u_t_h_o_r(_s): Boyu Ren, Emma Schwager, Timothy Tickle, Curtis Huttenhower _E_x_a_m_p_l_e_s: sparseDOSSA(strNormalizedFileName = "SyntheticMicrobiome.pcl", strCountFileName = "SyntheticMicrobiome-Counts.pcl", parameter_filename = "SyntheticMicrobiomeParameterFile.txt", bugs_to_spike = 0, calibrate = NA, datasetCount = 1, read_depth = 8030, number_features = 300, spikeCount = "1", lefse_file = NA, percent_spiked = 0.03, minLevelPercent = 0.1, number_samples = 50, max_percent_outliers = 0.05, number_metadata = 5, spikeStrength = "1.0", seed = 1, percent_outlier_spikins = 0.05, minOccurence = 0, verbose = TRUE, minSample = 0, association_type = "linear", noZeroInflate = FALSE, noRunMetadata = FALSE, runBugBug = FALSE) Warning in sparseDOSSA::sparseDOSSA() : number of associations = 0, and no spike file specified; no bug-bug spike-ins will be done. Parameters BEFORE Calibration File Length exp NA Length vdMu NA length vdSD NA length vdPercentZero NA Read depth 8030 Parameters AFTER Calibration File (if no calibration file is used, defaults are shown) Length exp 1 Length vdMu 1 length vdSD 1 length vdPercentZero 1 Read depth 8030 Feature Count 300 func_generate_random_lognormal_matrix START start funcGenerateFeatureParameters funcGenerateFeatureParameters: Generating vdExp Vector. LogMu 2.39794758911363 LogSD 1.33357395233333 Threshold 26.178898826878 funcGenerateFeatureParameters: Generating vdSD Vector. funcGenerateFeatureParameters: Generating vdMu Vector. funcGenerateFeatureParameters: Generating vdPercentZero Vector. ***Scale*** 1 ***vdPercentZero*** 0.381001612630270.5110492804597510.6158370514574770.6378085929853660.7496316601717770.971922394681468 stop funcGenerateFeatureParameters func_generate_random_lognormal_matrix: START Making features Start funcShuffleMatrix stop func_generate_random_lognormal_matrix start func_generate_random_lognormal_with_outliers Stop func_generate_random_lognormal_with_outliers start func_generate_random_lognormal_with_multivariate_spikes stop func_generate_random_lognormal_with_multivariate_spikes Warning in sparseDOSSA::sparseDOSSA(number_features = n.microbes, number_samples = n.samples, : number of associations = 0, and no spike file specified; no bug-bug spike-ins will be done. Parameters BEFORE Calibration File Length exp NA Length vdMu NA length vdSD NA length vdPercentZero NA Read depth 8030 Parameters AFTER Calibration File (if no calibration file is used, defaults are shown) Length exp 1 Length vdMu 1 length vdSD 1 length vdPercentZero 1 Read depth 8030 Feature Count 150 func_generate_random_lognormal_matrix START start funcGenerateFeatureParameters funcGenerateFeatureParameters: Generating vdExp Vector. LogMu 0.423465540160656 LogSD 2.66714790466667 Threshold 59.1226199198229 funcGenerateFeatureParameters: Generating vdSD Vector. funcGenerateFeatureParameters: Changing low SDs to a little more than 0. # occurences = 17 funcGenerateFeatureParameters: Generating vdMu Vector. funcGenerateFeatureParameters: Generating vdPercentZero Vector. ***Scale*** 1 ***vdPercentZero*** 0.1578260789197270.5924273440414080.9109121177078920.7750377328571650.9975385701217940.999995440684144 stop funcGenerateFeatureParameters func_generate_random_lognormal_matrix: START Making features Start funcShuffleMatrix stop func_generate_random_lognormal_matrix start func_generate_random_lognormal_with_outliers Stop func_generate_random_lognormal_with_outliers start func_generate_random_lognormal_with_multivariate_spikes stop func_generate_random_lognormal_with_multivariate_spikes Warning in sparseDOSSA::sparseDOSSA(spikeStrength = "2.0", spikeCount = "2") : number of associations = 0, and no spike file specified; no bug-bug spike-ins will be done. Parameters BEFORE Calibration File Length exp NA Length vdMu NA length vdSD NA length vdPercentZero NA Read depth 8030 Parameters AFTER Calibration File (if no calibration file is used, defaults are shown) Length exp 1 Length vdMu 1 length vdSD 1 length vdPercentZero 1 Read depth 8030 Feature Count 300 func_generate_random_lognormal_matrix START start funcGenerateFeatureParameters funcGenerateFeatureParameters: Generating vdExp Vector. LogMu 2.39794758911363 LogSD 1.33357395233333 Threshold 26.178898826878 funcGenerateFeatureParameters: Generating vdSD Vector. funcGenerateFeatureParameters: Generating vdMu Vector. funcGenerateFeatureParameters: Generating vdPercentZero Vector. ***Scale*** 1 ***vdPercentZero*** 0.3746673573278570.5048328481615370.6319034163667740.6454097383217940.7733402691990640.979238841041799 stop funcGenerateFeatureParameters func_generate_random_lognormal_matrix: START Making features Start funcShuffleMatrix stop func_generate_random_lognormal_matrix start func_generate_random_lognormal_with_outliers Stop func_generate_random_lognormal_with_outliers start func_generate_random_lognormal_with_multivariate_spikes stop func_generate_random_lognormal_with_multivariate_spikes Parameters BEFORE Calibration File Length exp NA Length vdMu NA length vdSD NA length vdPercentZero NA Read depth 8030 Parameters AFTER Calibration File (if no calibration file is used, defaults are shown) Length exp 1 Length vdMu 1 length vdSD 1 length vdPercentZero 1 Read depth 8030 Feature Count 300 func_generate_random_lognormal_matrix START start funcGenerateFeatureParameters funcGenerateFeatureParameters: Generating vdExp Vector. LogMu 2.39794758911363 LogSD 1.33357395233333 Threshold 26.178898826878 funcGenerateFeatureParameters: Generating vdSD Vector. funcGenerateFeatureParameters: Generating vdMu Vector. funcGenerateFeatureParameters: Generating vdPercentZero Vector. ***Scale*** 1 ***vdPercentZero*** 0.3633915617519070.5066083164694770.6415395150725680.6430270400425560.765606066986950.98663686342397 stop funcGenerateFeatureParameters func_generate_random_lognormal_matrix: START Making features Start funcShuffleMatrix stop func_generate_random_lognormal_matrix start func_generate_random_lognormal_with_outliers Stop func_generate_random_lognormal_with_outliers start func_generate_random_lognormal_with_multivariate_spikes stop func_generate_random_lognormal_with_multivariate_spikes Parameters for Bug-Bug spikes BEFORE Calibration File Length exp NA Length vdMu NA length vdSD NA length vdPercentZero NA Read depth 8030 Parameters for Bug-Bug spikes AFTER Calibration File (if no calibration file is used, defaults are shown) Length exp 1 Length vdMu 1 length vdSD 1 length vdPercentZero 1 Read depth 8030 Feature Count 300 start funcGenerateFeatureParameters funcGenerateFeatureParameters: Generating vdExp Vector. LogMu 2.39794758911363 LogSD 1.33357395233333 Threshold 26.178898826878 funcGenerateFeatureParameters: Generating vdSD Vector. funcGenerateFeatureParameters: Generating vdMu Vector. funcGenerateFeatureParameters: Generating vdPercentZero Vector. ***Scale*** 1 ***vdPercentZero*** 0.3829492145282010.5109190497750480.6404247633832220.6420645335775940.765839028655390.974570579534246 stop funcGenerateFeatureParameters start func_get_corr_mat_from_num start func_generate_spike_structure end func_generate_spike_structure end func_get_corr_mat_from_num func_generate_random_lognormal_matrix START start funcGenerateFeatureParameters stop funcGenerateFeatureParameters func_generate_random_lognormal_matrix: START Making features stop func_generate_random_lognormal_matrix Warning in sparseDOSSA::sparseDOSSA(strNormalizedFileName = "my_Microbiome.pcl", : number of associations = 0, and no spike file specified; no bug-bug spike-ins will be done. Parameters BEFORE Calibration File Length exp NA Length vdMu NA length vdSD NA length vdPercentZero NA Read depth 8030 Parameters AFTER Calibration File (if no calibration file is used, defaults are shown) Length exp 1 Length vdMu 1 length vdSD 1 length vdPercentZero 1 Read depth 8030 Feature Count 300 func_generate_random_lognormal_matrix START start funcGenerateFeatureParameters funcGenerateFeatureParameters: Generating vdExp Vector. LogMu 2.39794758911363 LogSD 1.33357395233333 Threshold 26.178898826878 funcGenerateFeatureParameters: Generating vdSD Vector. funcGenerateFeatureParameters: Generating vdMu Vector. funcGenerateFeatureParameters: Generating vdPercentZero Vector. ***Scale*** 1 ***vdPercentZero*** 0.3727369629860380.519256938589810.629850979173920.6415346803430020.7665530005976420.994435891635014 stop funcGenerateFeatureParameters func_generate_random_lognormal_matrix: START Making features Start funcShuffleMatrix stop func_generate_random_lognormal_matrix start func_generate_random_lognormal_with_outliers Stop func_generate_random_lognormal_with_outliers start func_generate_random_lognormal_with_multivariate_spikes stop func_generate_random_lognormal_with_multivariate_spikes [WARNING] Could not parse YAML metadata at line 17 column 1: :2:75: Unexpected ' ' pandoc-citeproc: reference paulson not found pandoc-citeproc: reference xochi2012 not found pandoc-citeproc: reference paulson not found pandoc-citeproc: reference mice not found Could not fetch https://latex.codecogs.com/png.image?%5Cdpi%7B110%7D&space;%5Cbg_white&space;mice.txt HttpExceptionRequest Request { host = "latex.codecogs.com" port = 443 secure = True requestHeaders = [] path = "/png.image" queryString = "?%5Cdpi%7B110%7D&space;%5Cbg_white&space;mice.txt" method = "GET" proxy = Nothing rawBody = False redirectCount = 10 responseTimeout = ResponseTimeoutDefault requestVersion = HTTP/1.1 } (InternalException (HandshakeFailed Error_EOF)) Error: processing vignette 'sparsedossa-vignette.Rmd' failed with diagnostics: pandoc document conversion failed with error 61 --- failed re-building ‘sparsedossa-vignette.Rmd’ SUMMARY: processing the following file failed: ‘sparsedossa-vignette.Rmd’ Error: Vignette re-building failed. Execution halted