<codeclass="sourceCode R"><span><spanclass="va">our_data</span><spanclass="op">$</span><spanclass="va">bacteria</span><spanclass="op"><-</span><spanclass="fu"><ahref="../reference/as.mo.html">as.mo</a></span><spanclass="op">(</span><spanclass="va">our_data</span><spanclass="op">$</span><spanclass="va">bacteria</span>, info <spanclass="op">=</span><spanclass="cn">TRUE</span><spanclass="op">)</span></span>
<span><spanclass="co">#><spanstyle="color: #0000BB;">ℹ Retrieved values from the </span><spanstyle="color: #0000BB; background-color: #EEEEEE;">microorganisms.codes</span><spanstyle="color: #0000BB;"> data set for "ESCCOL",</span></span></span>
<span><spanclass="co">#><spanstyle="color: #0000BB;">ℹ Retrieved values from the </span><spanstyle="color: #0000BB; background-color: #EEEEEE;">`microorganisms.codes`</span><spanstyle="color: #0000BB;"> data set for "ESCCOL",</span></span></span>
<span><spanclass="co"><spanstyle="color: #0000BB;">#> "KLEPNE", "STAAUR", and "STRPNE".</span></span></span>
<span><spanclass="co">#><spanstyle="color: #0000BB;">ℹ Microorganism translation was uncertain for four microorganisms. Run</span></span></span>
<span><spanclass="co"><spanstyle="color: #0000BB;">#></span><spanstyle="color: #0000BB; background-color: #EEEEEE;">mo_uncertainties()</span><spanstyle="color: #0000BB;"> to review these uncertainties, or use</span></span></span>
<span><spanclass="co"><spanstyle="color: #0000BB;">#></span><spanstyle="color: #0000BB; background-color: #EEEEEE;">add_custom_microorganisms()</span><spanstyle="color: #0000BB;"> to add custom entries.</span></span></span></code></pre></div>
<span><spanclass="co"><spanstyle="color: #0000BB;">#></span><spanstyle="color: #0000BB; background-color: #EEEEEE;">`mo_uncertainties()`</span><spanstyle="color: #0000BB;"> to review these uncertainties, or use</span></span></span>
<span><spanclass="co"><spanstyle="color: #0000BB;">#></span><spanstyle="color: #0000BB; background-color: #EEEEEE;">`add_custom_microorganisms()`</span><spanstyle="color: #0000BB;"> to add custom entries.</span></span></span></code></pre></div>
<p>Apparently, there was some uncertainty about the translation to
<span><spanclass="co">#><spanstyle="color: #0000BB;">Matching scores are based on the resemblance between the input and the full</span></span></span>
<span><spanclass="co"><spanstyle="color: #0000BB;">#> taxonomic name, and the pathogenicity in humans. See </span><spanstyle="color: #0000BB; background-color: #EEEEEE;">?mo_matching_score</span><spanstyle="color: #0000BB;">.</span></span></span>
<span><spanclass="co"><spanstyle="color: #0000BB;">#> taxonomic name, and the pathogenicity in humans. See </span><spanstyle="color: #0000BB; background-color: #EEEEEE;">`?mo_matching_score`</span><spanstyle="color: #0000BB;">.</span></span></span>
<span><spanclass="co"><spanstyle="color: #0000BB;">#> Only the first 10 other matches of each record are shown. Run</span></span></span>
<span><spanclass="co"><spanstyle="color: #0000BB;">#></span><spanstyle="color: #0000BB; background-color: #EEEEEE;">print(mo_uncertainties(), n = ...)</span><spanstyle="color: #0000BB;"> to view more entries, or save</span></span></span>
<span><spanclass="co"><spanstyle="color: #0000BB;">#></span><spanstyle="color: #0000BB; background-color: #EEEEEE;">mo_uncertainties()</span><spanstyle="color: #0000BB;"> to an object.</span></span></span></code></pre></div>
<span><spanclass="co"><spanstyle="color: #0000BB;">#></span><spanstyle="color: #0000BB; background-color: #EEEEEE;">`print(mo_uncertainties(), n = ...)`</span><spanstyle="color: #0000BB;"> to view more entries, or save</span></span></span>
<span><spanclass="co"><spanstyle="color: #0000BB;">#></span><spanstyle="color: #0000BB; background-color: #EEEEEE;">`mo_uncertainties()`</span><spanstyle="color: #0000BB;"> to an object.</span></span></span></code></pre></div>
<p>That’s all good.</p>
</div>
<divclass="section level3">
@ -400,9 +400,9 @@ the methods on the <code><a href="../reference/first_isolate.html">first_isolate
<span><spanclass="co">#><spanstyle="color: #BB0000;">ℹ Determining first isolates using an episode length of </span><spanstyle="color: #BB0000; font-weight: bold;">365 days</span></span></span>
<span><spanclass="co">#><spanstyle="color: #0000BB;">ℹ Using column '</span><spanstyle="color: #0000BB; font-weight: bold;">bacteria</span><spanstyle="color: #0000BB;">' as input for </span><spanstyle="color: #0000BB; background-color: #EEEEEE;">col_mo</span><spanstyle="color: #0000BB;">.</span></span></span>
<span><spanclass="co">#><spanstyle="color: #0000BB;">ℹ Using column '</span><spanstyle="color: #0000BB; font-weight: bold;">date</span><spanstyle="color: #0000BB;">' as input for </span><spanstyle="color: #0000BB; background-color: #EEEEEE;">col_date</span><spanstyle="color: #0000BB;">.</span></span></span>
<span><spanclass="co">#><spanstyle="color: #0000BB;">ℹ Using column '</span><spanstyle="color: #0000BB; font-weight: bold;">patient_id</span><spanstyle="color: #0000BB;">' as input for </span><spanstyle="color: #0000BB; background-color: #EEEEEE;">col_patient_id</span><spanstyle="color: #0000BB;">.</span></span></span>
<span><spanclass="co">#><spanstyle="color: #0000BB;">ℹ Using column '</span><spanstyle="color: #0000BB; font-weight: bold;">bacteria</span><spanstyle="color: #0000BB;">' as input for </span><spanstyle="color: #0000BB; background-color: #EEEEEE;">`col_mo`</span><spanstyle="color: #0000BB;">.</span></span></span>
<span><spanclass="co">#><spanstyle="color: #0000BB;">ℹ Using column '</span><spanstyle="color: #0000BB; font-weight: bold;">date</span><spanstyle="color: #0000BB;">' as input for </span><spanstyle="color: #0000BB; background-color: #EEEEEE;">`col_date`</span><spanstyle="color: #0000BB;">.</span></span></span>
<span><spanclass="co">#><spanstyle="color: #0000BB;">ℹ Using column '</span><spanstyle="color: #0000BB; font-weight: bold;">patient_id</span><spanstyle="color: #0000BB;">' as input for </span><spanstyle="color: #0000BB; background-color: #EEEEEE;">`col_patient_id`</span><spanstyle="color: #0000BB;">.</span></span></span>
<span><spanclass="co">#><spanstyle="color: #BB0000;">ℹ Basing inclusion on all antimicrobial results, using a points threshold</span></span></span>
<span><spanclass="co"><spanstyle="color: #BB0000;">#> of 2</span></span></span>
<span><spanclass="co">#><spanstyle="color: #080808;">=> Found </span><spanstyle="color: #080808; font-weight: bold;">2,724 'phenotype-based' first isolates</span><spanstyle="color: #080808;"> (90.8% of total where a</span></span></span>
<span> mo <spanclass="op">=</span><spanclass="fu"><ahref="https://rdrr.io/r/base/factor.html"class="external-link">as.factor</a></span><spanclass="op">(</span><spanclass="fu"><ahref="../reference/mo_property.html">mo_gramstain</a></span><spanclass="op">(</span><spanclass="va">mo</span><spanclass="op">)</span><spanclass="op">)</span><spanclass="op">)</span><spanclass="op"><ahref="https://magrittr.tidyverse.org/reference/pipe.html"class="external-link">%>%</a></span></span>
<span><spanclass="co"># drop NAs - the ones without a Gramstain (fungi, etc.)</span></span>
<span><spanclass="fu"><ahref="https://dplyr.tidyverse.org/reference/filter.html"class="external-link">filter</a></span><spanclass="op">(</span><spanclass="op">!</span><spanclass="fu"><ahref="https://rdrr.io/r/base/NA.html"class="external-link">is.na</a></span><spanclass="op">(</span><spanclass="va">res_AMX</span><spanclass="op">)</span><spanclass="op">&</span><spanclass="op">!</span><spanclass="fu"><ahref="https://rdrr.io/r/base/NA.html"class="external-link">is.na</a></span><spanclass="op">(</span><spanclass="va">res_AMC</span><spanclass="op">)</span><spanclass="op">&</span><spanclass="op">!</span><spanclass="fu"><ahref="https://rdrr.io/r/base/NA.html"class="external-link">is.na</a></span><spanclass="op">(</span><spanclass="va">res_CIP</span><spanclass="op">)</span><spanclass="op">)</span><spanclass="co"># Drop missing values</span></span>
<span><spanclass="co">#><spanstyle="color: #0000BB;">ℹ Using column '</span><spanstyle="color: #0000BB; font-weight: bold;">mo</span><spanstyle="color: #0000BB;">' as input for </span><spanstyle="color: #0000BB; background-color: #EEEEEE;">col_mo</span><spanstyle="color: #0000BB;">.</span></span></span>
<span><spanclass="co">#><spanstyle="color: #0000BB;">ℹ Using column '</span><spanstyle="color: #0000BB; font-weight: bold;">mo</span><spanstyle="color: #0000BB;">' as input for </span><spanstyle="color: #0000BB; background-color: #EEEEEE;">`col_mo`</span><spanstyle="color: #0000BB;">.</span></span></span>
<span></span>
<span><spanclass="va">data_time</span></span>
<span><spanclass="co">#><spanstyle="color: #949494;"># A tibble: 32 × 5</span></span></span>
Blocking a user prevents them from interacting with repositories, such as opening or commenting on pull requests or issues. Learn more about blocking a user.