Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
In phylogenetic, the diversity measures as UniFrac, weighted UniFrac, and normalized weighted UniFrac are used to estimate the closeness between two samples of genetic material sequences. These measures are widely used in microbiology to compare microbial communities. Furthermore, when the sample size is large enough, very good results have been obtained experimentally. However, some authors do not suggest using them when the sample size is very small. Recently, it has been mentioned that the weighted UniFrac measure can be seen as the Kantorovich-Rubinstein metric between the corresponding empirical distributions of samples of genetic material. Also, it is well known that the Kantorovich-Rubinstein metric complies the metric definition. However, one of the main reasons to establish it is that the sample size is large enough. The goal of this article is to prove that the diversity measures UniFrac are not metrics when the sample size is very small, which justifies why it must not be used in that case, but yes the Kantorovich-Rubinstein metric.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6482663 | PMC |
http://dx.doi.org/10.1177/1176934319843515 | DOI Listing |
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