diff options
Diffstat (limited to 'bin')
| -rw-r--r-- | bin/.htaccess | 2 | ||||
| -rw-r--r-- | bin/SVM_linear_aa_clf.pkl | bin | 0 -> 187597 bytes | |||
| -rw-r--r-- | bin/UniqRepsGemys_6089_StSCALER.pkl | bin | 0 -> 980 bytes | |||
| -rwxr-xr-x | bin/classifier.py | 313 |
4 files changed, 315 insertions, 0 deletions
diff --git a/bin/.htaccess b/bin/.htaccess new file mode 100644 index 0000000..698afb4 --- /dev/null +++ b/bin/.htaccess @@ -0,0 +1,2 @@ +Options +ExecCGI +SetHandler cgi-script diff --git a/bin/SVM_linear_aa_clf.pkl b/bin/SVM_linear_aa_clf.pkl Binary files differnew file mode 100644 index 0000000..1afce0a --- /dev/null +++ b/bin/SVM_linear_aa_clf.pkl diff --git a/bin/UniqRepsGemys_6089_StSCALER.pkl b/bin/UniqRepsGemys_6089_StSCALER.pkl Binary files differnew file mode 100644 index 0000000..3a098bd --- /dev/null +++ b/bin/UniqRepsGemys_6089_StSCALER.pkl diff --git a/bin/classifier.py b/bin/classifier.py new file mode 100755 index 0000000..0ae13b5 --- /dev/null +++ b/bin/classifier.py @@ -0,0 +1,313 @@ +#!/home/erik/bin/python3.6 + +#import packages to be used +from sklearn.svm import SVC +from sklearn.feature_extraction.text import CountVectorizer +from sklearn.preprocessing import StandardScaler +from sklearn.externals import joblib +import cgi, cgitb + +#----------------------------------------------\ +# Parse the web-form information to variables \ +# \_______________________________________________________ +# | +cgitb.enable() +form=cgi.FieldStorage() +alignment = form.getvalue('fasta') +if alignment.startswith(">"): #naive check for FASTA format + list=alignment.split(">") + book={} + for a in list: + tempList=a.splitlines() + nameLine=tempList.pop(0) + name=nameLine.split(" ")[0] + seq="".join(tempList) + book[name]=seq + seqList=[] + lenList=[] + nameList=[] + for i in book: + nameList.append(i) + seqList.append(book[i]) + lenList.append(str(len(book[i]))) + + if len(seqList)==0: #check for empty sequence list + seqList = ["MPSKKSGPQPHKRWVFTLNNPSEEEKNKIRELPISLFDYFVCGEEGLEEGRTAHLQGFANFAKKQTFNKVKWYFGARCHIEKAKGTDQQNKEYCSKEGHILIECGAPRNQGKRSDLSTAYFDYQQSGPPGMVLLNCCPSCRSSLSEDYYFAILEDCWRTINGGTRRPI"] + nameList=['demo'] + lenList=[str(len(alignment[0]))] + +else: + seqList = ["MPSKKSGPQPHKRWVFTLNNPSEEEKNKIRELPISLFDYFVCGEEGLEEGRTAHLQGFANFAKKQTFNKVKWYFGARCHIEKAKGTDQQNKEYCSKEGHILIECGAPRNQGKRSDLSTAYFDYQQSGPPGMVLLNCCPSCRSSLSEDYYFAILEDCWRTINGGTRRPI"] + nameList=['demo'] + lenList=[str(len(alignment[0]))] + +#--------------------------------------------------------------------------------------------------------+ + +#----------------------------------------------\ +# predict genus of input sequences \ +# \_______________________________________________________ +# | +#list of amino acids as vocabulary for the CountVectorizer +AAs=['a','c','d','e','f','g','h','i','k','l','m','n','p','q','r','s','t','v','w','y'] + +#load the classifier and scaler +clf=joblib.load("./cgi-bin/SVM_linear_aa_clf.pkl") +StSc=joblib.load("./cgi-bin/UniqRepsGemys_6089_StSCALER.pkl") +cv=CountVectorizer(analyzer='char',ngram_range=(1,1),vocabulary=AAs) + +#initialize text data vectorizer +dataVect=cv.transform(seqList) + +#Scale the data to the training set +X=StSc.transform(dataVect.astype("float64")) + +#make predictions for the original dataset +predictions=clf.predict(X) + + +#----------------------------------------------\ +# Build HTML table of results \ +# \_______________________________________________________ +# | +results="""""" +for k in len(seqList): + results+="""<tr><td>{0}</td><td>{1}</td><td>{2}</td></tr>""".format(nameList[k],lenList[k],predictions[k]) +if "demo" in nameList: + results+="""<p>There seems to have been an error.<br>If you are expecting more than one prediction or + do not see the name you entered please try the submission form again, making sure that the input is in FASTA format.""" + +#----------------------------------------------\ +# Build output page \ +# \_______________________________________________________ +# | +#build output page parts +#Header and CSS Style bits +header=""" +<!DOCTYPE html> + +<html> +<head> +<style> +* {box-sizing: border-box} +body {font-family: "Lato", sans-serif;} +/* Style the tab */ +div.tab { + float: left; + border: 1px solid #ccc; + background-color: #f1f1f1; + width: 20%; + height: 250px; +} +/* Style the buttons inside the tab */ +div.tab button { + display: block; + background-color: inherit; + color: black; + padding: 22px 16px; + width: 100%; + border: none; + outline: none; + text-align: left; + cursor: pointer; + transition: 0.3s; + font-size: 17px; +} +/* Change background color of buttons on hover */ +div.tab button:hover { + background-color: #ddd; +} +/* Create an active/current "tab button" class */ +div.tab button.active { + background-color: #1acefc; +} +/* Style the tab content */ +.tabcontent { + float: left; + padding: 0px 12px; + border: 1px solid #ccc; + width: 80%; + min-height: 250px; +} +table { + border-collapse: collapse; + width: 80%; +} + +th, td { + text-align: left; + padding: 8px; +} + +tr:nth-child(even){background-color: #f2f2f2} + +th { + background-color: #ff0000; + color: white; +} + +</style> +</head> +""" + +#Page contents, first part +body1=""" +<body> + +<p>Welcome to CRESSdna.org</p> + +<div class="tab"> + <button class="tablinks" onclick="openTab(event, 'Home')" >Home</button> + <button class="tablinks" onclick="openTab(event, 'Taxonomy')">Taxonomy</button> + <button class="tablinks" onclick="openTab(event, 'Contact')">Contact</button> + <button class="tablinks" onclick="openTab(event, 'Results')"id="defaultOpen">Results</button> + </div> + +<div id="Home" class="tabcontent"> + <h3>Home</h3> + <p>Part of the <a href='http://www.nsf.gov/pubs/2010/nsf10513/nsf10513.htm'>National Science Foundation's Assembling the Tree of Life</a>.</p> + <img src='nsf1.jpg' alt='Sponsored with a Grant from the National Science Foundation'> +</div> + +<div id="Taxonomy" class="tabcontent"> + <h3>Taxonomy</h3> + <p>Please enter only one word as the name(no space) and only one Rep sequence</p> + <form action="./cgi-bin/classifier.py" method="post"><br> + <input type="text" name="seqname" value="seqID"><br> + <textarea rows="4" cols="50" name="fasta" input type="submit"> +Enter ONE Rep protein sequence here...</textarea> + <br> + <input type="reset"> + <input type="submit"> +</form> + <p> + <ul> + <li>This classifier requires Rep protein sequence to be:</li> + <ul> + <li>Complete</li> + <li>Unaligned</li> + <li>in FASTA format</li> + </ul> + <p>And has been trained on the following Genera:</p> + <li>Circoviridae</li> + <ul> + <li>Circovirus</li> + <li>Cyclovirus</li> + </ul> + <li>Nanoviridae</li> + <ul> + <li>Babuvirus</li> + <li>Nanovirus</li> + </ul> + <li>Genomoviridae</li> + <ul> + <li>Gemycircularvirus</li> + <li>Gemygorvirus</li> + <li>Gemykibivirus</li> + <li>Gemykolovirus</li> + <li>Gemykrogvirus</li> + <li>Gemyvongvirus</li> + </ul> + <li>Geminiviridae</li> + <ul> + <li>Becurtovirus</li> + <li>Begomovirus</li> + <li>Capulavirus</li> + <li>Curtovirus</li> + <li>Eragrovirus</li> + <li>Grablovirus</li> + <li>Mastrevirus</li> + <li>Turncurtovirus</li> + </ul> + <li>Smacovirus</li> +</ul> </p> +</div> +<div id="Contact" class="tabcontent"> + <h3>Contact</h3> + <p>Questions or comments? Send us an email:</p> + <p>email At domain Dot something</p> +</div> + +<div id="Results" class="tabcontent"> + <h3>Results</h3> + <p>Results from Taxonomy prediction</p> + <table> + <tr> + <th>Sequence Name</th> + <th>Length</th> + <th>Prediction</th> + </tr> +""" + +#Page contents, second part (results fit between body1 and body2) +body2=""" +</table> + <p>This classifier will return the best fit of the submitted sequence to the training data.<br> +Currently included in the training data:<br> +<li>Circoviridae</li> + <ul> + <li>Circovirus</li> + <li>Cyclovirus</li> + </ul> + <li>Nanoviridae</li> + <ul> + <li>Babuvirus</li> + <li>Nanovirus</li> + </ul> + <li>Genomoviridae</li> + <ul> + <li>Gemycircularvirus</li> + <li>Gemygorvirus</li> + <li>Gemykibivirus</li> + <li>Gemykolovirus</li> + <li>Gemykrogvirus</li> + <li>Gemyvongvirus</li> + </ul> + <li>Geminiviridae</li> + <ul> + <li>Becurtovirus</li> + <li>Begomovirus</li> + <li>Capulavirus</li> + <li>Curtovirus</li> + <li>Eragrovirus</li> + <li>Grablovirus</li> + <li>Mastrevirus</li> + <li>Turncurtovirus</li> + </ul> + <li>Smacovirus</li> +<br><br> +</p> +</div> + +<script> +function openTab(evt, tabTitle) { + var i, tabcontent, tablinks; + tabcontent = document.getElementsByClassName("tabcontent"); + for (i = 0; i < tabcontent.length; i++) { + tabcontent[i].style.display = "none"; + } + tablinks = document.getElementsByClassName("tablinks"); + for (i = 0; i < tablinks.length; i++) { + tablinks[i].className = tablinks[i].className.replace(" active", ""); + } + document.getElementById(tabTitle).style.display = "block"; + evt.currentTarget.className += " active"; +} +// Get the element with id="defaultOpen" and click on it +document.getElementById("defaultOpen").click(); +</script> +</body> +""" + +#close the Page +footer=""" +</html> +""" + +#build the output page +page=header+body1+results+body2+footer + +#send the output as html +output = page.format() +print (output) + +quit() |