Row |
Level |
Rule Name |
Subject |
Property |
Value |
0 |
WARN |
annotation_whitespace |
OBCS:0000062 |
IAO:0000115 |
A plan specification that provides a detailed outline of which measurements will be taken at what times, on which material, in what manner, and by whom. Sampling plans should be designed in such a way that the resulting data will contain a representative sample of the parameters of interest and allow for all questions, as stated in the goals, to be answered. |
1 |
WARN |
annotation_whitespace |
OBCS:0000118 |
IAO:0000115 |
A quantitative confidence value that expresses how many times more likely the data are under one model than the other. |
2 |
WARN |
annotation_whitespace |
OBCS:0000124 |
IAO:0000115 |
A statistical data analysis objective where the aim is to make inference using population sample data. |
3 |
WARN |
annotation_whitespace |
OBCS:0000126 |
IAO:0000119 |
WEB: http://en.wikipedia.org/wiki/Random_variable |
4 |
WARN |
annotation_whitespace |
OBCS:0000127 |
IAO:0000115 |
An objective specification where the aim is to collect data. |
5 |
WARN |
annotation_whitespace |
OBCS:0000134 |
IAO:0000119 |
WEB: http://www.stats.gla.ac.uk/steps/glossary/probability_distributions.html#contvar |
6 |
WARN |
annotation_whitespace |
OBCS:0000135 |
IAO:0000119 |
WEB: http://www.stats.gla.ac.uk/steps/glossary/probability_distributions.html#contvar |
7 |
WARN |
annotation_whitespace |
OBCS:0000140 |
IAO:0000115 |
A normalization data transformation that used to create normalized gene expression level from microarray raw data. The raw intensity values are background corrected, log2 transformed and then quantile normalized in the RMA normalization process. |
8 |
WARN |
annotation_whitespace |
OBCS:0000141 |
IAO:0000119 |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC33173/http://en.wikipedia.org/wiki/Significance_analysis_of_microarrays |
9 |
WARN |
annotation_whitespace |
OBCS:0000142 |
IAO:0000119 |
http://en.wikipedia.org/wiki/Signal-to-noise_ratiohttp://www.ncbi.nlm.nih.gov/pubmed/10521349 |
10 |
WARN |
annotation_whitespace |
OBCS:0000147 |
IAO:0000119 |
http://www.pnas.org/content/102/43/15545.abstract |
11 |
WARN |
annotation_whitespace |
OBCS:0000164 |
IAO:0000119 |
Storey J.D. (2007) The optimal discovery procedure: A new approach to simultaneous significance testing, Journal of the Royal Statistical Society, Series B, 69: 347-368.
Storey J.D., Dai J.Y., and Leek J.T. (2007) The optimal discovery procedure for large-scale significance testing, with applications to comparative microarray experiments, Biostatistics, 8: 414-432.
Leek J.T,. Monsen E.C., Dabney A.R., and Storey J.D. (2006) EDGE: Extraction and analysis of differential gene expression, Bioinformatics, 22: 507-508.
Storey J.D., Xiao W., Leek J.T., Tompkins R.G., and Davis R.W. (2005) Significance analysis of time course microarray experiments, Proceedings of the National Academy of Sciences, 102: 12837-12842.
|
12 |
WARN |
annotation_whitespace |
OBCS:0000165 |
IAO:0000115 |
A software that can be used to produce lists of differentially expressed genes with confidence measures attached. These lists are generated via a False Discovery Rate (FDR) method of controlling the false positives. Patterns from Gene Expression (PaGE) is more than a differential expression analysis tool. PaGE is a tool to attach descriptive, dependable, and easily interpretable expression patterns to genes across multiple conditions, each represented by a set of replicated array experiments.
|
13 |
WARN |
annotation_whitespace |
OBCS:0000165 |
IAO:0000116 |
The input consists of (replicated) intensities from a collection of array experiments from two or more conditions (or from a collection of direct comparisons on 2-channel arrays). The output consists of patterns, one for each row identifier in the data file. One condition is used as a reference to which the other types are compared. The length of a pattern equals the number of non-reference sample types. The symbols in the patterns are integers, where positive integers represent up-regulation as compared to the reference sample type and negative integers represent down-regulation. The patterns are based on the false discovery rates for each position in the pattern, so that the number of positive and negative symbols that appear in each position of the pattern is as descriptive as the data variability allows. The patterns generated are easily interpretable in that integers are used to represent different levels of up- or down-regulation as compared to the reference sample type. |
14 |
WARN |
annotation_whitespace |
OBCS:0000167 |
IAO:0000119 |
http://en.wikipedia.org/wiki/Peak_calling |
15 |
WARN |
annotation_whitespace |
OBCS:0000226 |
IAO:0000115 |
A data set that is an aggregate of numerical data item. |
16 |
WARN |
annotation_whitespace |
OBCS:0000231 |
IAO:0000115 |
A rate of deaths (in general, or due to a specific cause) that in a particular population, scaled to the size of that population, per unit of time. |
17 |
WARN |
annotation_whitespace |
OBCS:0000232 |
IAO:0000115 |
A rate of unit shif in a hospital. |
18 |
WARN |
annotation_whitespace |
OBCS:0000264 |
IAO:0000115 |
A broad class of computational algorithms that rely on repeated random sampling to obtain numerical results.The goal of Monte Carlo analysis is to trace out the structure of the distributions of model output that results from specified uncertainty distributions of model inputs and model parameters. |
19 |
WARN |
annotation_whitespace |
OBCS:0000330 |
IAO:0000115 |
Organizational uncertainty arose when information was lost or trapped owing to the local division of labor or the circumstances of alliances and collaborations. |
20 |
WARN |
annotation_whitespace |
OBCS:0000331 |
IAO:0000115 |
Technical uncertainty developed as a result of inadequate tools or ambiguous information about techniques. Technical uncertainty arose from difficulties with subjects, equipment, and procedures, including the lack of standard measurement techniques. |
21 |
WARN |
annotation_whitespace |
OBCS:0000343 |
IAO:0000115 |
Reducible ignorance may be resolved by conducting further research, which implies that it might be possible to somehow achieve a better understanding. |
22 |
WARN |
annotation_whitespace |
OBCS:0000344 |
IAO:0000115 |
Irreducible ignorance applies when neither research nor development can provide sufficient knowledge about the essential relationships. |
23 |
WARN |
annotation_whitespace |
OBCS:0000345 |
IAO:0000115 |
Total ignorance is the other extreme from determinism on the scale of uncertainty, which implies a deep level of uncertainty, to the extent that we do not even know that we do not know. |
24 |
WARN |
annotation_whitespace |
OBCS:0000346 |
IAO:0000115 |
Context uncertainty includes uncertainty about the external economic, environmental, political, social, and technological situation that forms the context for the problem being examined. The context could fall within the past, the present, or the future. |
25 |
WARN |
annotation_whitespace |
OBCS:0000351 |
IAO:0000115 |
Uncertainty about the external driving forces that produce changes within the system (the relevant scenario variables and policy variables) and the magnitude of the forces (the values of the scenario and policy variables). |
26 |
WARN |
annotation_whitespace |
OBCS:0000352 |
IAO:0000115 |
Uncertainty about the systemdata that ‘drive’ themodel and typically quantify relevant features of the reference system and its behaviour (e.g. land-use maps, data on infrastructure (roads, houses)). Uncertainty about system data is generated by a lack of knowledge of the properties (including both the deterministic and the stochastic properties) of the underlying system and deficiencies in the description of the variability that can be an inherent feature of some of the phenomena under observation. |
27 |
WARN |
annotation_whitespace |
OBCS:0000362 |
IAO:0000115 |
A belief is psychologically certain when the subject who has it is supremely convinced of its truth. Certainty in this sense is similar to incorrigibility, which is the property a belief has of being such that the subject is incapable of giving it up. But psychological certainty is not the same thing as incorrigibility. A belief can be certain in this sense without being incorrigible; this may happen, for example, when the subject receives a very compelling bit of counterevidence to the (previously) certain belief and gives it up for that reason. Moreover, a belief can be incorrigible without being psychologically certain. For example, a mother may be incapable of giving up the belief that her son did not commit a gruesome murder, and yet, compatible with that inextinguishable belief, she may be tortured by doubt. |
28 |
WARN |
annotation_whitespace |
http://purl.obolibrary.org/obo/obcs.owl |
dc11:contributor |
Chris Stoeckert @en |
29 |
WARN |
annotation_whitespace |
http://purl.obolibrary.org/obo/obcs.owl |
dc11:description |
OBCS stands for the Ontology of Biological and Clinical Statistics. OBCS is an ontology in the domain of biological and clinical statistics. It is aligned with the Basic Formal Ontology (BFO) and the Ontology for Biomedical Investigations (OBI). OBCS imports all possible biostatistics terms in OBI and includes many additional biostatistics terms, some of which were proposed and discussed in the OBI face-to-face workshop in Ann Arbor in 2012. @en |
30 |
WARN |
duplicate_exact_synonym |
OBCS:0000162 |
IAO:0000118 |
|
31 |
WARN |
duplicate_exact_synonym |
OBCS:0000163 |
IAO:0000118 |
|
32 |
WARN |
duplicate_exact_synonym |
OBCS:0000241 |
IAO:0000118 |
|
33 |
WARN |
duplicate_exact_synonym |
OBCS:0000243 |
IAO:0000118 |
|
34 |
WARN |
duplicate_exact_synonym |
OBCS:0000326 |
IAO:0000118 |
|
35 |
WARN |
duplicate_exact_synonym |
OBCS:0000327 |
IAO:0000118 |
|
36 |
WARN |
duplicate_exact_synonym |
OBCS:0000005 |
IAO:0000118 |
|
37 |
WARN |
duplicate_exact_synonym |
OBCS:0000211 |
IAO:0000118 |
|
38 |
WARN |
duplicate_exact_synonym |
OBCS:0000246 |
IAO:0000118 |
|
39 |
WARN |
duplicate_exact_synonym |
OBCS:0000247 |
IAO:0000118 |
|
40 |
WARN |
equivalent_class_axiom_no_genus |
OBCS:0000002 |
OBI:0000417 |
OBCS:0000127 |
41 |
WARN |
equivalent_class_axiom_no_genus |
OBCS:0000121 |
OBI:0000417 |
OBCS:0000124 |
42 |
WARN |
equivalent_class_axiom_no_genus |
OBCS:0000170 |
OBI:0000312 |
OBCS:0000169 |
43 |
WARN |
equivalent_class_axiom_no_genus |
OBCS:0000224 |
OBCS:0000223 |
OBCS:0000010 |
44 |
WARN |
equivalent_class_axiom_no_genus |
OBCS:0000225 |
OBCS:0000223 |
OBCS:0000005 |
45 |
WARN |
equivalent_class_axiom_no_genus |
OBCS:0000230 |
OBI:0000293 |
OBI:0000078 |
46 |
WARN |
invalid_xref |
OBCS:0000012 |
oboInOwl:hasDbXref |
STATO_0000036 |
47 |
WARN |
missing_definition |
OBCS:0000020 |
IAO:0000115 |
|
48 |
WARN |
missing_definition |
OBCS:0000257 |
IAO:0000115 |
|
49 |
WARN |
missing_definition |
OBCS:0000258 |
IAO:0000115 |
|
50 |
WARN |
missing_definition |
OBCS:0000262 |
IAO:0000115 |
|
51 |
WARN |
missing_definition |
OBCS:0000271 |
IAO:0000115 |
|
52 |
WARN |
missing_definition |
OBCS:0000272 |
IAO:0000115 |
|
53 |
WARN |
missing_definition |
OBCS:0000273 |
IAO:0000115 |
|
54 |
WARN |
missing_definition |
OBCS:0000275 |
IAO:0000115 |
|
55 |
WARN |
missing_definition |
OBCS:0000276 |
IAO:0000115 |
|
56 |
WARN |
missing_definition |
OBCS:0000277 |
IAO:0000115 |
|
57 |
WARN |
missing_definition |
OBCS:0000278 |
IAO:0000115 |
|
58 |
WARN |
missing_definition |
OBCS:0000279 |
IAO:0000115 |
|
59 |
WARN |
missing_definition |
OBCS:0000280 |
IAO:0000115 |
|
60 |
WARN |
missing_definition |
OBCS:0000281 |
IAO:0000115 |
|
61 |
WARN |
missing_definition |
OBCS:0000282 |
IAO:0000115 |
|
62 |
WARN |
missing_definition |
OBCS:0000283 |
IAO:0000115 |
|
63 |
WARN |
missing_definition |
OBCS:0000284 |
IAO:0000115 |
|
64 |
WARN |
missing_definition |
OBCS:0000285 |
IAO:0000115 |
|
65 |
WARN |
missing_definition |
OBCS:0000286 |
IAO:0000115 |
|
66 |
WARN |
missing_definition |
OBCS:0000287 |
IAO:0000115 |
|
67 |
WARN |
missing_definition |
OBCS:0000288 |
IAO:0000115 |
|
68 |
WARN |
missing_definition |
OBCS:0000289 |
IAO:0000115 |
|
69 |
WARN |
missing_definition |
OBCS:0000290 |
IAO:0000115 |
|
70 |
WARN |
missing_definition |
OBCS:0000291 |
IAO:0000115 |
|
71 |
WARN |
missing_definition |
OBCS:0000292 |
IAO:0000115 |
|
72 |
WARN |
missing_definition |
OBCS:0000293 |
IAO:0000115 |
|
73 |
WARN |
missing_definition |
OBCS:0000294 |
IAO:0000115 |
|
74 |
WARN |
missing_definition |
OBCS:0000295 |
IAO:0000115 |
|
75 |
WARN |
missing_definition |
OBCS:0000296 |
IAO:0000115 |
|
76 |
WARN |
missing_definition |
OBCS:0000297 |
IAO:0000115 |
|
77 |
WARN |
missing_definition |
OBCS:0000298 |
IAO:0000115 |
|
78 |
WARN |
missing_definition |
OBCS:0000299 |
IAO:0000115 |
|
79 |
WARN |
missing_definition |
OBCS:0000300 |
IAO:0000115 |
|
80 |
WARN |
missing_definition |
OBCS:0000301 |
IAO:0000115 |
|
81 |
WARN |
missing_definition |
OBCS:0000302 |
IAO:0000115 |
|
82 |
WARN |
missing_definition |
OBCS:0000303 |
IAO:0000115 |
|
83 |
WARN |
missing_definition |
OBCS:0000304 |
IAO:0000115 |
|
84 |
WARN |
missing_definition |
OBCS:0000305 |
IAO:0000115 |
|
85 |
WARN |
missing_definition |
OBCS:0000306 |
IAO:0000115 |
|
86 |
WARN |
missing_definition |
OBCS:0000307 |
IAO:0000115 |
|
87 |
WARN |
missing_definition |
OBCS:0000308 |
IAO:0000115 |
|
88 |
WARN |
missing_definition |
OBCS:0000309 |
IAO:0000115 |
|
89 |
WARN |
missing_definition |
OBCS:0000310 |
IAO:0000115 |
|
90 |
WARN |
missing_definition |
OBCS:0000311 |
IAO:0000115 |
|
91 |
WARN |
missing_definition |
OBCS:0000312 |
IAO:0000115 |
|
92 |
WARN |
missing_definition |
OBCS:0000313 |
IAO:0000115 |
|
93 |
WARN |
missing_definition |
OBCS:0000314 |
IAO:0000115 |
|
94 |
WARN |
missing_definition |
OBCS:0000315 |
IAO:0000115 |
|
95 |
WARN |
missing_definition |
OBCS:0000316 |
IAO:0000115 |
|
96 |
WARN |
missing_definition |
OBCS:0000317 |
IAO:0000115 |
|
97 |
WARN |
missing_definition |
OBCS:0000318 |
IAO:0000115 |
|
98 |
WARN |
missing_definition |
OBCS:0000324 |
IAO:0000115 |
|
99 |
WARN |
missing_definition |
OBCS:0000325 |
IAO:0000115 |
|
100 |
WARN |
missing_definition |
OBCS:0000332 |
IAO:0000115 |
|
101 |
WARN |
missing_definition |
OBCS:0000333 |
IAO:0000115 |
|
102 |
WARN |
missing_definition |
OBCS:0000334 |
IAO:0000115 |
|
103 |
WARN |
missing_definition |
OBCS:0000335 |
IAO:0000115 |
|
104 |
WARN |
missing_definition |
OBCS:0000336 |
IAO:0000115 |
|
105 |
WARN |
missing_definition |
OBCS:0000337 |
IAO:0000115 |
|
106 |
WARN |
missing_definition |
OBCS:0000350 |
IAO:0000115 |
|
107 |
WARN |
missing_definition |
OBCS:0000353 |
IAO:0000115 |
|
108 |
WARN |
missing_definition |
OBCS:0000363 |
IAO:0000115 |
|
109 |
WARN |
missing_definition |
OBCS:0000364 |
IAO:0000115 |
|
110 |
WARN |
missing_definition |
OBCS:0000365 |
IAO:0000115 |
|
111 |
WARN |
missing_definition |
OBCS:0000366 |
IAO:0000115 |
|
112 |
WARN |
missing_definition |
OBCS:0000367 |
IAO:0000115 |
|
113 |
WARN |
missing_definition |
OBCS:0000368 |
IAO:0000115 |
|
114 |
WARN |
missing_definition |
OBCS:0000369 |
IAO:0000115 |
|
115 |
WARN |
missing_definition |
OBCS:0000370 |
IAO:0000115 |
|
116 |
WARN |
missing_definition |
OBCS:0000371 |
IAO:0000115 |
|
117 |
WARN |
missing_definition |
OBCS:0000372 |
IAO:0000115 |
|
118 |
WARN |
missing_definition |
OBCS:0000373 |
IAO:0000115 |
|
119 |
WARN |
missing_definition |
OBCS:0000374 |
IAO:0000115 |
|
120 |
INFO |
lowercase_definition |
OBCS:0000319 |
IAO:0000115 |
the chaotic and unpredictable nature of natural processes |
121 |
INFO |
lowercase_definition |
OBCS:0000320 |
IAO:0000115 |
‘non-rational’behaviour, discrepancies between what people say and what they actually do (cognitive dissoce), or deviations of ‘standard’ behavioural patterns (micro-level behaviour). |
122 |
INFO |
lowercase_definition |
OBCS:0000321 |
IAO:0000115 |
the chaotic and unpredictable nature of societal processes (macro-level behaviour). The need to consider societal and institutional processes as a major contributor to uncertainty due to variability can be inferred from various papers of Funtowicz, Ravetz, and de Marchi. |
123 |
INFO |
lowercase_definition |
OBCS:0000326 |
IAO:0000115 |
vagueness is associated with the lack of precise or sharp distinctions or boundaries |
124 |
INFO |
lowercase_definition |
OBCS:0000348 |
IAO:0000115 |
uncertainty about the form of the model itself. Model structure uncertainty arises from a lack of sufficient understanding of the system (past, present, or future) that is the subject of the policy analysis, including the behaviour of the system and the interrelationships among its elements. |
125 |
INFO |
lowercase_definition |
OBCS:0000349 |
IAO:0000115 |
uncertainty arising from the computer implementation of the model.Model technical uncertainty is the uncertainty generated by software or hardware errors, i.e. hidden flaws in the technical equipment. Software errors arise from bugs in software, design errors in algorithms and typing errors in model source code. Hardware errors arise from bugs, such as the bug in the early version of the Pentium processor, which gave rise to numerical error in a broad range of floating-point calculations performed on the processor. |