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comparison aldex2.R @ 1:75214276e2b7 draft default tip

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planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/aldex2 commit f9acc7c5710d6eb99a883cb83b7967e6af972f1b
author iuc
date Fri, 14 Jun 2024 21:21:29 +0000
parents f4d0bd4b4d6d
children
comparison
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0:f4d0bd4b4d6d 1:75214276e2b7
67 effect <- get_boolean_value(opt$effect) 67 effect <- get_boolean_value(opt$effect)
68 include_sample_summary <- get_boolean_value(opt$include_sample_summary) 68 include_sample_summary <- get_boolean_value(opt$include_sample_summary)
69 iterate <- get_boolean_value(opt$iterate) 69 iterate <- get_boolean_value(opt$iterate)
70 70
71 if (opt$analysis_type == "aldex") { 71 if (opt$analysis_type == "aldex") {
72 aldex_obj <- aldex(reads = reads_df, 72 aldex_obj <- aldex(
73 conditions_vector, 73 reads = reads_df,
74 mc.samples = opt$num_mc_samples, 74 conditions_vector,
75 test = opt$aldex_test, 75 mc.samples = opt$num_mc_samples,
76 effect = effect, 76 test = opt$aldex_test,
77 include.sample.summary = include_sample_summary, 77 effect = effect,
78 denom = opt$denom, 78 include.sample.summary = include_sample_summary,
79 iterate = iterate) 79 denom = opt$denom,
80 iterate = iterate
81 )
80 } else { 82 } else {
81 # Generate Monte Carlo samples of the Dirichlet distribution for each sample. Convert each 83 # Generate Monte Carlo samples of the Dirichlet distribution for each sample. Convert each
82 # instance using a log-ratio transform. This is the input for all further analyses. 84 # instance using a log-ratio transform. This is the input for all further analyses.
83 aldex_clr_obj <- aldex.clr(reads_df, conditions_vector, mc.samples = opt$num_mc_samples, denom = opt$denom) 85 aldex_clr_obj <- aldex.clr(reads_df, conditions_vector, mc.samples = opt$num_mc_samples, denom = opt$denom)
84 86
115 qgraph(dist, layout = "spring", vsize = 1) 117 qgraph(dist, layout = "spring", vsize = 1)
116 dev.off() 118 dev.off()
117 } else if (opt$analysis_type == "aldex_kw") { 119 } else if (opt$analysis_type == "aldex_kw") {
118 aldex_obj <- aldex.kw(aldex_clr_obj) 120 aldex_obj <- aldex.kw(aldex_clr_obj)
119 } else if (opt$analysis_type == "aldex_plot") { 121 } else if (opt$analysis_type == "aldex_plot") {
120 aldex_obj <- aldex(reads = reads_df, 122 aldex_obj <- aldex(
121 conditions_vector, 123 reads = reads_df,
122 mc.samples = opt$num_mc_samples, 124 conditions_vector,
123 test = opt$aldex_test, 125 mc.samples = opt$num_mc_samples,
124 effect = effect, 126 test = opt$aldex_test,
125 include.sample.summary = include_sample_summary, 127 effect = effect,
126 denom = opt$denom, 128 include.sample.summary = include_sample_summary,
127 iterate = iterate) 129 denom = opt$denom,
130 iterate = iterate
131 )
128 png(filename = opt$output) 132 png(filename = opt$output)
129 aldex.plot(x = aldex_obj, 133 aldex.plot(
130 type = opt$plot_type, 134 x = aldex_obj,
131 test = opt$plot_test, 135 type = opt$plot_type,
132 cutoff.pval = opt$cutoff_pval, 136 test = opt$plot_test,
133 cutoff.effect = opt$cutoff_effect, 137 cutoff.pval = opt$cutoff_pval,
134 xlab = opt$xlab, 138 cutoff.effect = opt$cutoff_effect,
135 ylab = opt$ylab) 139 xlab = opt$xlab,
140 ylab = opt$ylab
141 )
136 dev.off() 142 dev.off()
137 } else if (opt$analysis_type == "aldex_plot_feature") { 143 } else if (opt$analysis_type == "aldex_plot_feature") {
138 png(filename = opt$output) 144 png(filename = opt$output)
139 aldex.plotFeature(aldex_clr_obj, opt$feature_name) 145 aldex.plotFeature(aldex_clr_obj, opt$feature_name)
140 dev.off() 146 dev.off()