Mercurial > repos > jay > pdaug_tsvtofasta
changeset 6:391e7e836fe9 draft
"planemo upload for repository https://github.com/jaidevjoshi83/pdaug commit 45ebf32dcaa1eed91670d3a2491f9cf3dfb535ef"
author | jay |
---|---|
date | Tue, 12 Jan 2021 18:40:09 +0000 |
parents | f93187136dfb |
children | e9fa3b6346e3 |
files | PDAUG_Merge_Dataframes/PDAUG_Merge_Dataframes.py PDAUG_Merge_Dataframes/test-data/1.tsv PDAUG_Merge_Dataframes/test-data/2.tsv PDAUG_Merge_Dataframes/test-data/3.tsv PDAUG_Merge_Dataframes/test-data/4.tsv PDAUG_Merge_Dataframes/test-data/5.tsv PDAUG_Merge_Dataframes/test-data/6.tsv PDAUG_Merge_Dataframes/test-data/out.tsv PDAUG_Merge_Dataframes/test-data/out1.tsv PDAUG_TSVtoFASTA/PDAUG_TSVtoFASTA.py PDAUG_TSVtoFASTA/PDAUG_TSVtoFASTA.xml PDAUG_TSVtoFASTA/test-data/1.fasta PDAUG_TSVtoFASTA/test-data/2.fasta PDAUG_TSVtoFASTA/test-data/out.fasta PDAUG_TSVtoFASTA/test-data/test.tsv PDAUG_TSVtoFASTA/test-data/test1.tsv PDAUG_TSVtoFASTA/test-data/test2.tsv PDAUG_TSVtoFASTA/test-data/test2/Out.fasta |
diffstat | 18 files changed, 298 insertions(+), 233 deletions(-) [+] |
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--- a/PDAUG_Merge_Dataframes/PDAUG_Merge_Dataframes.py Wed Dec 30 02:42:16 2020 +0000 +++ b/PDAUG_Merge_Dataframes/PDAUG_Merge_Dataframes.py Tue Jan 12 18:40:09 2021 +0000 @@ -2,27 +2,38 @@ import pandas as pd import sys -files = sys.argv[1] -out_file = sys.argv[2] + +def MergeData(infiles, add_class_label, class_label, OutPut): + + data_frame = pd.DataFrame() + if add_class_label == 'True' or add_class_label == 'true': + for i, file in enumerate(infiles.split(',')): + df1 = pd.read_csv(file,sep='\t') + df2 = pd.DataFrame(df1.shape[0]*[i], columns=[class_label]) + df3 = pd.concat([df1,df2], axis=1) + data_frame = pd.concat([data_frame,df3]) + final_DF = data_frame.fillna(0) -data_frame = pd.read_csv(files.split(',')[0],sep='\t') + else: + + for file in infiles.split(','): + df1 = pd.read_csv(file,sep='\t') + data_frame = pd.concat([data_frame,df1]) + final_DF = data_frame.fillna(0) + + final_DF.to_csv(OutPut, sep="\t", index=False) -for file in files.split(',')[1:]: - - df1 = pd.read_csv(file,sep='\t') - data_frame = pd.concat([data_frame,df1]) - -final_DF = data_frame.fillna(0) - -final_DF.to_csv(out_file,sep="\t", index=False) +if __name__=="__main__": - - - + import argparse + parser = argparse.ArgumentParser() + parser.add_argument("-I", "--infiles", required=True, default=None, help=".tsv") + parser.add_argument("-L", "--add_class_label", required=False, default=False, help="Path to target tsv file") + parser.add_argument("-C", "--class_label", required=False, default='class_label', help="Path to target tsv file") + parser.add_argument("-O", "--OutPut", required=False, default='Out.tsv', help="Path to target tsv file") - + args = parser.parse_args() - - + MergeData(args.infiles, args.add_class_label, args.class_label, args.OutPut)
--- a/PDAUG_Merge_Dataframes/test-data/1.tsv Wed Dec 30 02:42:16 2020 +0000 +++ b/PDAUG_Merge_Dataframes/test-data/1.tsv Tue Jan 12 18:40:09 2021 +0000 @@ -1,2 +1,2 @@ -Algo accuracy presision recall f1 mean_auc -SVMC 0.608 0.781 0.608 0.537 0.608 +NAME COL1 COL2 COL3 COL4 COL5 +1 15 10 12 5 3 \ No newline at end of file
--- a/PDAUG_Merge_Dataframes/test-data/2.tsv Wed Dec 30 02:42:16 2020 +0000 +++ b/PDAUG_Merge_Dataframes/test-data/2.tsv Tue Jan 12 18:40:09 2021 +0000 @@ -1,2 +1,2 @@ -Algo accuracy presision recall f1 mean_auc -SVMC 0.608 0.781 0.608 0.537 0.608 +NAME COL1 COL2 COL3 COL4 COL5 +2 15 10 12 5 3 \ No newline at end of file
--- a/PDAUG_Merge_Dataframes/test-data/3.tsv Wed Dec 30 02:42:16 2020 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,2 +0,0 @@ -Algo accuracy presision recall f1 mean_auc -SVMC 0.608 0.781 0.608 0.537 0.608
--- a/PDAUG_Merge_Dataframes/test-data/4.tsv Wed Dec 30 02:42:16 2020 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,2 +0,0 @@ -Algo accuracy presision recall f1 mean_auc -SVMC 0.608 0.781 0.608 0.537 0.608
--- a/PDAUG_Merge_Dataframes/test-data/5.tsv Wed Dec 30 02:42:16 2020 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,2 +0,0 @@ -Algo accuracy presision recall f1 mean_auc -SVMC 0.608 0.781 0.608 0.537 0.608
--- a/PDAUG_Merge_Dataframes/test-data/6.tsv Wed Dec 30 02:42:16 2020 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,2 +0,0 @@ -Algo accuracy presision recall f1 mean_auc -SVMC 0.608 0.781 0.608 0.537 0.608
--- a/PDAUG_Merge_Dataframes/test-data/out.tsv Wed Dec 30 02:42:16 2020 +0000 +++ b/PDAUG_Merge_Dataframes/test-data/out.tsv Tue Jan 12 18:40:09 2021 +0000 @@ -1,7 +1,3 @@ -Algo accuracy presision recall f1 mean_auc -SVMC 0.608 0.7809999999999999 0.608 0.537 0.608 -SVMC 0.608 0.7809999999999999 0.608 0.537 0.608 -SVMC 0.608 0.7809999999999999 0.608 0.537 0.608 -SVMC 0.608 0.7809999999999999 0.608 0.537 0.608 -SVMC 0.608 0.7809999999999999 0.608 0.537 0.608 -SVMC 0.608 0.7809999999999999 0.608 0.537 0.608 +NAME COL1 COL2 COL3 COL4 COL5 +1 15 10 12 5 3 +2 15 10 12 5 3
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/PDAUG_Merge_Dataframes/test-data/out1.tsv Tue Jan 12 18:40:09 2021 +0000 @@ -0,0 +1,3 @@ +NAME COL1 COL2 COL3 COL4 COL5 class_label +1 15 10 12 5 3 0 +2 15 10 12 5 3 1
--- a/PDAUG_TSVtoFASTA/PDAUG_TSVtoFASTA.py Wed Dec 30 02:42:16 2020 +0000 +++ b/PDAUG_TSVtoFASTA/PDAUG_TSVtoFASTA.py Tue Jan 12 18:40:09 2021 +0000 @@ -1,64 +1,72 @@ -import os -import argparse + +import pandas as pd + + +def TSVtoFASTA(infile, method, firstdatafile, seconddatafile, outfile, clmpepid, slcclasslabel, peps): + + + fn = [firstdatafile, seconddatafile] -def TSVtoFASTA(InFile, Method, Positive, Negative, OutFile): - - if Method == 'WithClassLabel': - - f = open(InFile) - lines = f.readlines() - - of1 = open(Positive,'w') - of2 = open(Negative,'w') - - n = 0 - m = 0 - - l = [] - - for line in lines[1:]: - l.append(line.split('\t')[1].strip('\n').strip('\r')) - l = list(set(l)) - - print(l) - - for line in lines: + df = pd.read_csv(infile, sep="\t") + if clmpepid == None: + pass + else: + names = df[clmpepid].tolist() - if l[1] in line.split('\t')[1].strip('\n').strip('\r'): - n= n+1 - of1.write('>peptide_'+str(n)+'_'+str(l[1])+'\n') - of1.write(line.split('\t')[0]+'\n') - - if l[0] in line.split('\t')[1].strip('\n').strip('\r'): - m= m+1 - of2.write('>peptide_'+str(m)+'_'+str(l[0])+'\n') - of2.write(line.split('\t')[0]+'\n') + peps = df[peps].tolist() + + if method == "withoutlabel": + f = open(outfile,'w') + if clmpepid is not None: + for i,n in enumerate(peps): + f.write(">"+names[i]+'\n') + f.write(n+'\n') + f.close() + else: + for i,n in enumerate(peps): + f.write(">"+str(i)+'\n') + f.write(n+'\n') + f.close() + + elif method == "withlabel": + labels = df[slcclasslabel].tolist() - elif Method == 'NoClassLabel': - - f = open(InFile) - lines = f.readlines() - of1 = open(OutFile,'w') - - for i, line in enumerate(lines[1:]): - of1.write('>peptide_'+str(i)+'\n') - of1.write(line.split('\t')[0]+'\n') - - else: - pass + label = list(set(labels)) + + if clmpepid is None: + for i, l in enumerate(label): + f = open(fn[i],'w') + print('ok1') + for i, L in enumerate(labels): + if l == L: + f.write(">"+str(i)+"_"+str(l)+'\n') + f.write(peps[i]+'\n') + f.close() + else: + for i, l in enumerate(label): + f = open(fn[i],'w') + for i, L in enumerate(labels): + if l == L: + f.write(">"+names[i]+"_"+l+'\n') + f.write(peps[i]+'\n') + f.close() if __name__=="__main__": import argparse - parser = argparse.ArgumentParser() - parser.add_argument("-I", "--InFile", required=True, default=None, help=".fasta or .tsv") - parser.add_argument("-P", "--Postvs", required=False, default='FirstDataFile.fasta', help="Path to target tsv file") - parser.add_argument("-N", "--Negtvs", required=False, default='SecondDataFile.fasta', help="Path to target tsv file") + parser.add_argument("-F", "--FirstDataFile", required=False, default='FirstDataFile.fasta', help="Path to target tsv file") + parser.add_argument("-S", "--SecondDataFile", required=False, default='SecondDataFile.fasta', help="Path to target tsv file") parser.add_argument("-O", "--OutFile", required=False, default='OutFile.fasta', help="Path to target tsv file") parser.add_argument("-M", "--Method", required=True, default=None, help="Path to target tsv file") + parser.add_argument("-C", "--ClmPepID", required=False, default=None, help="Peptide Column Name") + parser.add_argument("-L", "--SlcClassLabel", required=False, default="Class_label", help="Class Label Column Name") + parser.add_argument("-P", "--PeptideColumn", required=True, default=None, help="Class Label Column Name") args = parser.parse_args() - TSVtoFASTA(args.InFile, args.Method, args.Postvs, args.Negtvs, args.OutFile) \ No newline at end of file + TSVtoFASTA(args.InFile, args.Method, args.FirstDataFile, args.SecondDataFile, args.OutFile, args.ClmPepID, args.SlcClassLabel, args.PeptideColumn) + + +
--- a/PDAUG_TSVtoFASTA/PDAUG_TSVtoFASTA.xml Wed Dec 30 02:42:16 2020 +0000 +++ b/PDAUG_TSVtoFASTA/PDAUG_TSVtoFASTA.xml Tue Jan 12 18:40:09 2021 +0000 @@ -3,60 +3,110 @@ <description>Converts tabular peptide sequence data into fasta format</description> <requirements> - <requirement type="package" version="0.24.2">pandas</requirement> - <requirement type="package" version="4.1.2">modlamp</requirement> + <requirement type="package" version="1.2.0">pandas</requirement> </requirements> <stdio> <exit_code range="1" level="fatal" /> </stdio> <command detect_errors="exit_code"><![CDATA[ - python '$__tool_directory__/PDAUG_TSVtoFASTA.py' -I '$InFile' -M '$Method' + python '$__tool_directory__/PDAUG_TSVtoFASTA.py' -I '$infile' -P '$peps' + + #if $selmethod.method == 'withlabel' + #if $selmethod.advancefeature.columnselect == 'advancefeature' + --ClmPepID $selmethod.advancefeature.clmname + #end if + --SlcClassLabel '$selmethod.classlabel' + -M '$selmethod.method' + -F '$output2' + -S '$output3' + #end if - #if $Method == 'WithClassLabel' - -P '$OutFile1' - -N '$OutFile2' - #end if + #if $selmethod.method == 'withoutlabel' + #if $selmethod.advancefeature.columnselect == 'advancefeature' + --ClmPepID $selmethod.advancefeature.clmname + #end if + -M '$selmethod.method' + -O '$output1' + #end if - #if $Method == 'NoClassLabel' - -O '$OutFile3' - #end if - + && + + ls + ]]></command> <inputs> - <param name="InFile" type="data" label="Input file" format="tabular" argument= "--InFile1" help="Input tabular file"/> - <param name="Method" type="select" label="Data conversion" argument="--Method" help="Split file if class labels are present" > - <option value="WithClassLabel"> WithClassLabel </option> - <option value="NoClassLabel" selected="true" > NoClassLabel </option> - </param> + <param name="infile" type="data" label="Peptide data" format="tabular" argument= "--InFile1" help="Input tabular file"/> + <param name="peps" type="text" label="Peptide Column" format="tabular" argument= "--InFile1" help="Input tabular file"/> + + <conditional name='selmethod' > + <param name="method" type="select" label="Method to convert data" argument="--Method" help="Split file if class labels are present" > + <option value="withoutlabel"> Convert Without Split </option> + <option value="withlabel" selected="true" >Split Data By Class Label</option> + </param> + + <when value="withlabel"> + <param name="classlabel" type="text" label="Column with the class label" value="Class_label" argument= "--SlcClassLabel" help="Select Class Label"/> + + <conditional name='advancefeature' > + <param name="columnselect" type="select" label="Peptide ID Column" argument="--Method" help="Split file if class labels are present" > + <option value="advancefeature" > Add Peptide ID Column Name </option> + <option value="normalfeature" selected="true"> No Peptide ID Column </option> + </param> + + <when value="advancefeature"> + <param name="clmname" type="text" label="Column name with peptide IDs" argument= "--ClmPepID" help="Select Peptide ID Column"/> + </when> + </conditional> + </when> + + <when value="withoutlabel"> + <conditional name='advancefeature' > + <param name="columnselect" type="select" label="Column name with peptide IDs" argument="--Method" help="Split file if class labels are present" > + <option value="advancefeature" > Add Peptide ID Column Name </option> + <option value="normalfeature" selected="true"> No Peptide ID Column </option> + </param> + + <when value="advancefeature"> + <param name="clmname" type="text" label="Select Peptide ID Column" argument= "--ClmPepID" help="Select Peptide ID Column"/> + </when> + + </conditional> + </when> + </conditional> </inputs> <outputs> - <data name='OutFile1' format='fasta' label="${tool.name} on $on_string - first (fasta)" > - <filter>Method == "WithClassLabel"</filter> + <data name='output1' format='fasta' label="${tool.name} on $on_string - first (fasta)" > + <filter>selmethod['method'] == "withoutlabel"</filter> </data> - <data name='OutFile2' format='fasta' label="${tool.name} on $on_string - second (fasta)"> - <filter>Method == "WithClassLabel"</filter> + <data name='output2' format='fasta' label="${tool.name} on $on_string - second (fasta)"> + <filter>selmethod['method'] == "withlabel"</filter> </data> - <data name='OutFile3' format='fasta' label="${tool.name} on $on_string - (fasta)" > - <filter>Method == "NoClassLabel"</filter> + <data name='output3' format='fasta' label="${tool.name} on $on_string - (fasta)" > + <filter>selmethod['method'] == "withlabel"</filter> </data> </outputs> + <tests> + <test> - <param name="InFile" value="test1.tsv"/> - <param name="Method" value="WithClassLabel"/> - <output name="OutFile1" file="test1/FirstDataFile.fasta"/> - <output name="OutFile2" file="test1/SecondDataFile.fasta"/> + <param name="infile" value="test.tsv"/> + <param name="method" value="withoutlabel" /> + <param name="peps" value="Peptides" /> + <param name="output2" file="out.fasta" /> </test> + <test> - <param name="InFile" value="test2.tsv"/> - <param name="Method" value="NoClassLabel"/> - <output name="OutFile3" file="test2/Out.fasta"/> + <param name="infile" value="test.tsv"/> + <param name="peps" value="Peptides" /> + <param name="output2" file="1.fasta" /> + <param name="output3" file="2.fasta" /> </test> + </tests> <help><![CDATA[ .. class:: infomark @@ -68,7 +118,13 @@ ----- **Inputs** - * **--InFile** Takes input as Tabular file with or without label. + * **Method to convert data** Converts tabular data into fasta with or without splitting based on the availability of class labels. + + * **Column with the class label** Enter the column name with the class labels. + + * **Peptide data** Enter the column name with peptides. + + * **Peptide ID Column** Enter the column name with peptide IDs. -----
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/PDAUG_TSVtoFASTA/test-data/1.fasta Tue Jan 12 18:40:09 2021 +0000 @@ -0,0 +1,22 @@ +>12_AMP +GLFDIVKKVVGALG +>13_AMP +KLLKLLKKKLLK +>14_AMP +KLLLLKLLK +>15_AMP +GLFDIVKKVVGALG +>16_AMP +GLFDIVKKVVGALG +>17_AMP +KLLKLLKKKLLK +>18_AMP +KLLLLKLLK +>19_AMP +GLFDIVKKVVGALG +>20_AMP +KLLKLLKKKLLK +>21_AMP +KLLLLKLLK +>22_AMP +GLFDIVKKVVGALG \ No newline at end of file
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/PDAUG_TSVtoFASTA/test-data/2.fasta Tue Jan 12 18:40:09 2021 +0000 @@ -0,0 +1,24 @@ +>0_TM +GLFDIVKKVVGALG +>1_TM +KLLKLLKKKLLK +>2_TM +KLLLLKLLK +>3_TM +GLFDIVKKVVGALG +>4_TM +GLFDIVKKVVGALG +>5_TM +KLLKLLKKKLLK +>6_TM +KLLLLKLLK +>7_TM +GLFDIVKKVVGALG +>8_TM +GLFDIVKKVVGALG +>9_TM +KLLKLLKKKLLK +>10_TM +KLLLLKLLK +>11_TM +GLFDIVKKVVGALG \ No newline at end of file
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/PDAUG_TSVtoFASTA/test-data/out.fasta Tue Jan 12 18:40:09 2021 +0000 @@ -0,0 +1,46 @@ +>0 +GLFDIVKKVVGALG +>1 +KLLKLLKKKLLK +>2 +KLLLLKLLK +>3 +GLFDIVKKVVGALG +>4 +GLFDIVKKVVGALG +>5 +KLLKLLKKKLLK +>6 +KLLLLKLLK +>7 +GLFDIVKKVVGALG +>8 +GLFDIVKKVVGALG +>9 +KLLKLLKKKLLK +>10 +KLLLLKLLK +>11 +GLFDIVKKVVGALG +>12 +GLFDIVKKVVGALG +>13 +KLLKLLKKKLLK +>14 +KLLLLKLLK +>15 +GLFDIVKKVVGALG +>16 +GLFDIVKKVVGALG +>17 +KLLKLLKKKLLK +>18 +KLLLLKLLK +>19 +GLFDIVKKVVGALG +>20 +KLLKLLKKKLLK +>21 +KLLLLKLLK +>22 +GLFDIVKKVVGALG \ No newline at end of file
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/PDAUG_TSVtoFASTA/test-data/test.tsv Tue Jan 12 18:40:09 2021 +0000 @@ -0,0 +1,24 @@ +Name Peptides Class_label +Pep1 GLFDIVKKVVGALG TM +Pep2 KLLKLLKKKLLK TM +Pep3 KLLLLKLLK TM +Pep4 GLFDIVKKVVGALG TM +Pep5 GLFDIVKKVVGALG TM +Pep6 KLLKLLKKKLLK TM +Pep7 KLLLLKLLK TM +Pep8 GLFDIVKKVVGALG TM +Pep9 GLFDIVKKVVGALG TM +Pep10 KLLKLLKKKLLK TM +Pep11 KLLLLKLLK TM +Pep12 GLFDIVKKVVGALG TM +Pep13 GLFDIVKKVVGALG AMP +Pep14 KLLKLLKKKLLK AMP +Pep15 KLLLLKLLK AMP +Pep16 GLFDIVKKVVGALG AMP +Pep17 GLFDIVKKVVGALG AMP +Pep18 KLLKLLKKKLLK AMP +Pep19 KLLLLKLLK AMP +Pep20 GLFDIVKKVVGALG AMP +Pep21 KLLKLLKKKLLK AMP +Pep22 KLLLLKLLK AMP +Pep23 GLFDIVKKVVGALG AMP \ No newline at end of file
--- a/PDAUG_TSVtoFASTA/test-data/test1.tsv Wed Dec 30 02:42:16 2020 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,24 +0,0 @@ -Peptides Class_label -GLFDIVKKVVGALG 0 -KLLKLLKKKLLK 0 -KLLLLKLLK 0 -GLFDIVKKVVGALG 0 -GLFDIVKKVVGALG 0 -KLLKLLKKKLLK 0 -KLLLLKLLK 0 -GLFDIVKKVVGALG 0 -GLFDIVKKVVGALG 0 -KLLKLLKKKLLK 0 -KLLLLKLLK 0 -GLFDIVKKVVGALG 0 -GLFDIVKKVVGALG 1 -KLLKLLKKKLLK 1 -KLLLLKLLK 1 -GLFDIVKKVVGALG 1 -GLFDIVKKVVGALG 1 -KLLKLLKKKLLK 1 -KLLLLKLLK 1 -GLFDIVKKVVGALG 1 -KLLKLLKKKLLK 1 -KLLLLKLLK 1 -GLFDIVKKVVGALG 1 \ No newline at end of file
--- a/PDAUG_TSVtoFASTA/test-data/test2.tsv Wed Dec 30 02:42:16 2020 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,24 +0,0 @@ -Peptides -GLFDIVKKVVGALG -KLLKLLKKKLLK -KLLLLKLLK -GLFDIVKKVVGALG -GLFDIVKKVVGALG -KLLKLLKKKLLK -KLLLLKLLK -GLFDIVKKVVGALG -GLFDIVKKVVGALG -KLLKLLKKKLLK -KLLLLKLLK -GLFDIVKKVVGALG -GLFDIVKKVVGALG -KLLKLLKKKLLK -KLLLLKLLK -GLFDIVKKVVGALG -GLFDIVKKVVGALG -KLLKLLKKKLLK -KLLLLKLLK -GLFDIVKKVVGALG -KLLKLLKKKLLK -KLLLLKLLK -GLFDIVKKVVGALG \ No newline at end of file
--- a/PDAUG_TSVtoFASTA/test-data/test2/Out.fasta Wed Dec 30 02:42:16 2020 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,69 +0,0 @@ ->peptide_0 -GLFDIVKKVVGALG - ->peptide_1 -KLLKLLKKKLLK - ->peptide_2 -KLLLLKLLK - ->peptide_3 -GLFDIVKKVVGALG - ->peptide_4 -GLFDIVKKVVGALG - ->peptide_5 -KLLKLLKKKLLK - ->peptide_6 -KLLLLKLLK - ->peptide_7 -GLFDIVKKVVGALG - ->peptide_8 -GLFDIVKKVVGALG - ->peptide_9 -KLLKLLKKKLLK - ->peptide_10 -KLLLLKLLK - ->peptide_11 -GLFDIVKKVVGALG - ->peptide_12 -GLFDIVKKVVGALG - ->peptide_13 -KLLKLLKKKLLK - ->peptide_14 -KLLLLKLLK - ->peptide_15 -GLFDIVKKVVGALG - ->peptide_16 -GLFDIVKKVVGALG - ->peptide_17 -KLLKLLKKKLLK - ->peptide_18 -KLLLLKLLK - ->peptide_19 -GLFDIVKKVVGALG - ->peptide_20 -KLLKLLKKKLLK - ->peptide_21 -KLLLLKLLK - ->peptide_22 -GLFDIVKKVVGALG -