')
+ # Input data
+ w.write(
+ '
Input file:
%s
Number of sequences in input file:
%d
Pattern of the sequence bank:
%s
5\' restriction site:
%s
3\' restriction site:
%s
' % (
+ input_file, len(all_seq), args.pattern, args.site_res_5, args.site_res_3))
+ # Sequence analysis
+ w.write(
+ '
Caption:
- Valid sequences that will be part of the next analysis
- Good sequences but will not be part of the next analysis
- Rejected sequences
| Absence of restriction sites | Incorrect number of nucleotides between the restriction sites | Stop codon inside the area of interest | Mutation in the conserved regions | Valid sequences | Amber codon in the sequence (inside the area of interest) |
|---|
')
+ w.write(
+ '| %d sequence(s) (%.2f%%) | %d sequence(s) (%.2f%%) | %d sequence(s) (%.2f%%) | %d sequence(s) (%.2f%%) | %d sequence(s) (%.2f%%) | %d sequence(s) |
' % (
+ len(no_restric), float(len(no_restric)) / float(len(all_seq)) * 100, len(no_multiple), float(len(no_multiple)) / float(len(all_seq)) * 100, len(stop),
+ float(len(stop)) / float(len(all_seq)) * 100, len(mut), float(len(mut)) / float(len(all_seq)) * 100, len(good_ids), float(len(good_ids)) / float(len(all_seq)) * 100,
+ len(amber)))
+ w.write(
+ '| %s | %s | %s | %s | %s | %s |
' % (
+ '
'.join(no_restric), '
'.join(no_multiple), '
'.join(stop), '
'.join(mut), '
'.join(good_ids), '
'.join(amber)))
+ # Variable regions analysis
+ w.write(
+ '
The following group of sequences are identical clones on the variable regions:
')
+ identical_clones_seq = identical_clones.keys()
+ if identical_clones_seq:
+ for seq in identical_clones_seq:
+ ids = list(set(identical_clones[seq])) # return only one occurrence of each item in the list
+ w.write('
%d sequences (%.2f%% of valid sequences)
%s
' % (
+ len(ids), float(len(ids)) / float(len(good_ids)) * 100, '
'.join(ids)))
+ w.write('
| Variable region | Repeated sequence |
|---|
')
+ for z in range(len(good_seq[ids[0]]['var'])):
+ w.write('%d | %s | ' % (z + 1, good_seq[ids[0]]['var'][z]))
+ w.write('
')
+ else:
+ w.write('
No clone was found.
')
+
+ first = True
+ for i in range(nb_var_part):
+ keys = []
+ for k in (var_seq_common[str(i + 1)].keys()):
+ nb = var_seq_common[str(i + 1)][k]
+ if nb > 1:
+ if first:
+ w.write(
+ '
Here\'s the distribution of the repeated sequences in variable regions:
| Variable region | Repeated sequence | Number of occurrences (percentage of valid sequences) |
|---|
')
+ first = False
+ keys.append(k)
+ else:
+ keys.append(k)
+ nb = len(keys)
+ if nb != 0:
+ w.write('')
+ for z in range(nb):
+ if z == 0:
+ w.write('| %d | ' % (nb, i + 1))
+ w.write('%s | %d (%.2f%%) |
' % (
+ keys[z], var_seq_common[str(i + 1)][keys[z]], float(var_seq_common[str(i + 1)][keys[z]]) / float(len(good_ids)) * 100))
+ w.write('
')
+ # Clustering
+ w.write('
The following clusters were generated by MCL:
')
+ for line in open(mcl_output, 'r'):
+ w.write('
%d sequences (%.2f%% of valid sequences)
%s
' % (
+ len(line.split("\t")), float(len(line.split("\t"))) / float(len(good_ids)) * 100, '
'.join(line.split("\t"))))
+ # Statistics
+ w.write('')
+ w.write('
Here\'s some statistics about the valid sequences:
Mean for the pairwise alignement scores: %.2f
Standard deviation: %.2f
' % (
+ numpy.mean(align_scores), numpy.std(align_scores)))
+ w.write('
' % os.path.basename(graph_pic))
+ w.write('
| Pairwise Alignment Score | Number of occurrences |
|---|
')
+ uniq_scores = sorted(list(set(align_scores)))
+ scores_dic = {}
+ for score in uniq_scores:
+ scores_dic[score] = align_scores.count(score)
+
+ scores_dic = dict(sorted(scores_dic.items()))
+ scores = scores_dic.items()
+ # scores.sort()
+
+ for el in scores:
+ w.write('| %.2f | %d |
' % (el[0], el[1]))
+ w.write('
')
+ # Annex
+ w.write('')
+ w.write('
Valid protein sequences in FASTA format:
')
+ aln_out = generate_aln(good_seq, good_ids)
+ print(str(aln_out))
+ w.write(
+ '
Multiple sequence alignment of the valid sequences generated by Clustal Omega:
' % str(
+ aln_out))
+
+ if no_multiple:
+ w.write(
+ '
Protein sequences with an incorrect number of nucleotides between the restriction sites in FASTA format:
')
+
+ if mut:
+ w.write('
Mutated protein sequences in FASTA format:
')
+ aln_out = generate_aln(all_seq_fasta, mut)
+
+ w.write(
+ '
Multiple sequence alignment of the mutated sequences generated by Clustal Omega:
' % str(
+ aln_out))
+
+ if stop:
+ w.write('
Protein sequences with a stop codon in FASTA format:
')
+
+ if amber:
+ w.write('
Protein sequences with an amber codon in FASTA format:
')
+
+ w.write('
Input file:
fibronectin_datatest.fasta
Number of sequences in input file:
36
Pattern of the sequence bank:
AAAGSSVSSVPTKLEVVAATPTSLLISWDA:4-6:V:1:YYRITYGETGGNSPVQEFTVPG:3:TATISGLSPGVDYTITVYA:11-12:PISINYRTGTGGSGGSHHHHHHHHGGSYPYDVPDYAPRVG*GRVGSKDIRAETVESCLAKSHTENSFTNVWKDDKTLDRYANYE
5' restriction site:
GCGGCCGC
3' restriction site:
GGTACC
Caption:
- Valid sequences that will be part of the next analysis
- Good sequences but will not be part of the next analysis
- Rejected sequences
| Absence of restriction sites | Incorrect number of nucleotides between the restriction sites | Stop codon inside the area of interest | Mutation in the conserved regions | Valid sequences | Amber codon in the sequence (inside the area of interest) |
|---|
| 1 sequence(s) (2.78%) | 6 sequence(s) (16.67%) | 25 sequence(s) (69.44%) | 0 sequence(s) (0.00%) | 4 sequence(s) (11.11%) | 0 sequence(s) |
| XL2-3_PSEXSEQ-REV_34 | XL1_22_PSEXSEQ-REV_24
XL1_24_PSEXSEQ-REV_26
XL1_30_PSEXSEQ-REV_30
XL1_4_PSEXSEQ-REV_8
XL2-2_PSEXSEQ-REV_33
XL3-4_PSEXSEQ-REV_40 | XL1_10_PSEXSEQ-REV_13
XL1_11_PSEXSEQ-REV_14
XL1_13_PSEXSEQ-REV_16
XL1_14_PSEXSEQ-REV_17
XL1_15_PSEXSEQ-REV_18
XL1_16_PSEXSEQ-REV_19
XL1_17_PSEXSEQ-REV_20
XL1_1_PSEXSEQ-REV_5
XL1_23_PSEXSEQ-REV_25
XL1_25_PSEXSEQ-REV_27
XL1_26_PSEXSEQ-REV_28
XL1_29_PSEXSEQ-REV_29
XL1_33_PSEXSEQ-REV_23
XL1_3_PSEXSEQ-REV_7
XL1_5_PSEXSEQ-REV_9
XL1_6_PSEXSEQ-REV_10
XL1_8_PSEXSEQ-REV_11
XL1_9_PSEXSEQ-REV_12
XL2-1_PSEXSEQ-REV_32
XL2-4_PSEXSEQ-REV_35
XL2-5_PSEXSEQ-REV_36
XL3-1_PSEXSEQ-REV_37
XL3-2_PSEXSEQ-REV_38
XL3-3_PSEXSEQ-REV_39
XL3-5_PSEXSEQ-REV_41 | | XL1_12_PSEXSEQ-REV_15
XL1_18_PSEXSEQ-REV_21
XL1_19_PSEXSEQ-REV_22
XL1_2_PSEXSEQ-REV_6 | |
The following group of sequences are identical clones on the variable regions:
No clone was found.
Here's the distribution of the repeated sequences in variable regions:
| Variable region | Repeated sequence | Number of occurrences (percentage of valid sequences) |
|---|
| 3 | YSY | 2 (50.00%) |
The following clusters were generated by MCL:
4 sequences (100.00% of valid sequences)
XL1_12_PSEXSEQ-REV_15
XL1_18_PSEXSEQ-REV_21
XL1_19_PSEXSEQ-REV_22
XL1_2_PSEXSEQ-REV_6
+
Here's some statistics about the valid sequences:
Mean for the pairwise alignement scores: 25.92
Standard deviation: 3.89
| Pairwise Alignment Score | Number of occurrences |
|---|
| 19.00 | 1 |
| 23.80 | 1 |
| 26.30 | 1 |
| 27.30 | 2 |
| 31.80 | 1 |
Valid protein sequences in FASTA format:
Multiple sequence alignment of the valid sequences generated by Clustal Omega:
Protein sequences with an incorrect number of nucleotides between the restriction sites in FASTA format:
Protein sequences with a stop codon in FASTA format:
