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manulera committed Oct 3, 2024
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315 changes: 315 additions & 0 deletions readme_example.ipynb
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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Dseqrecord(-60)\n",
"\u001b[48;5;11mATGCAAACAGTAATGATGGATGACATTCAAAGCACTGATTCTATTGCTGAAAAAGATAAT\u001b[0m\n",
"TACGTTTGTCATTACTACCTACTGTAAGTTTCGTGACTAAGATAACGACTTTTTCTATTA"
]
},
"execution_count": null,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from pydna.dseqrecord import Dseqrecord\n",
"# Let's create a DNA sequence record, and add a feature to it\n",
"dsr = Dseqrecord(\"ATGCAAACAGTAATGATGGATGACATTCAAAGCACTGATTCTATTGCTGAAAAAGATAAT\")\n",
"dsr.add_feature(x=0, y=60,type=\"gene\", label=\"my_gene\") # We add a feature to highlight the sequence as a gene\n",
"dsr.figure()\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"LOCUS name 60 bp DNA linear UNK 01-JAN-1980\n",
"DEFINITION description.\n",
"ACCESSION id\n",
"VERSION id\n",
"KEYWORDS .\n",
"SOURCE .\n",
" ORGANISM .\n",
" .\n",
"FEATURES Location/Qualifiers\n",
" misc 1..60\n",
" /type=\"gene\"\n",
" /label=\"my_gene\"\n",
"ORIGIN\n",
" 1 atgcaaacag taatgatgga tgacattcaa agcactgatt ctattgctga aaaagataat\n",
"//\n"
]
}
],
"source": [
"# This is how it would look as a genbank file\n",
"print(dsr.format(\"genbank\"))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"forward primer: ATGCAAACAGTAATGATGGA\n",
"reverse primer: ATTATCTTTTTCAGCAATAGAATCA\n"
]
},
{
"data": {
"text/plain": [
"5ATGCAAACAGTAATGATGGA...TGATTCTATTGCTGAAAAAGATAAT3\n",
" |||||||||||||||||||||||||\n",
" 3ACTAAGATAACGACTTTTTCTATTA5\n",
"5ATGCAAACAGTAATGATGGA3\n",
" ||||||||||||||||||||\n",
"3TACGTTTGTCATTACTACCT...ACTAAGATAACGACTTTTTCTATTA5"
]
},
"execution_count": null,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Now let's design primers to amplify it\n",
"from pydna.design import primer_design\n",
"# limit is the minimum length of the primer, target_tm is the desired melting temperature of the primer\n",
"amplicon = primer_design(dsr, limit=13, target_tm=55)\n",
"# Let's print the primers, and a figure that shows where they align with the template sequence\n",
"print(\"forward primer:\", amplicon.forward_primer.seq)\n",
"print(\"reverse primer:\", amplicon.reverse_primer.seq)\n",
"amplicon.figure()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
" 5ATGCAAACAGTAATGATGGA...TGATTCTATTGCTGAAAAAGATAAT3\n",
" |||||||||||||||||||||||||\n",
" 3ACTAAGATAACGACTTTTTCTATTACCTAGGtttt5\n",
"5ccccGGATCCATGCAAACAGTAATGATGGA3\n",
" ||||||||||||||||||||\n",
" 3TACGTTTGTCATTACTACCT...ACTAAGATAACGACTTTTTCTATTA5"
]
},
"execution_count": null,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Let's say we don't want to just amplify it, but we want to add restriction sites to it!\n",
"\n",
"from pydna.amplify import pcr\n",
"# We add the restriction sites to the primers\n",
"forward_primer = \"ccccGGATCC\" + amplicon.forward_primer\n",
"reverse_primer = \"ttttGGATCC\" + amplicon.reverse_primer\n",
"\n",
"# We do the PCR\n",
"pcr_product = pcr(forward_primer, reverse_primer, dsr)\n",
"# The PCR product is of class `Amplicon`, a subclass of `Dseqrecord`.\n",
"# When doing a figure, it shows where primers anneal.\n",
"pcr_product.figure()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"LOCUS m_y___g_e_n_e 80 bp DNA linear UNK 01-JAN-1980\n",
"DEFINITION pcr_product_f60 id_r60 id.\n",
"ACCESSION m_y___g_e_n_e\n",
"VERSION m_y___g_e_n_e\n",
"KEYWORDS .\n",
"SOURCE .\n",
" ORGANISM .\n",
" .\n",
"FEATURES Location/Qualifiers\n",
" misc 11..70\n",
" /type=\"gene\"\n",
" /label=\"my_gene\"\n",
" primer_bind 11..30\n",
" /label=\"f60\"\n",
" /PCR_conditions=\"primer\n",
" sequence:ccccGGATCCATGCAAACAGTAATGATGGA\"\n",
" /ApEinfo_fwdcolor=\"#baffa3\"\n",
" /ApEinfo_revcolor=\"#ffbaba\"\n",
" primer_bind complement(46..70)\n",
" /label=\"r60\"\n",
" /PCR_conditions=\"primer\n",
" sequence:ttttGGATCCATTATCTTTTTCAGCAATAGAATCA\"\n",
" /ApEinfo_fwdcolor=\"#baffa3\"\n",
" /ApEinfo_revcolor=\"#ffbaba\"\n",
"ORIGIN\n",
" 1 ccccggatcc atgcaaacag taatgatgga tgacattcaa agcactgatt ctattgctga\n",
" 61 aaaagataat ggatccaaaa\n",
"//\n"
]
},
{
"data": {
"text/plain": [
"Dseqrecord(-80)\n",
"ccccGGATCC\u001b[48;5;11mATGCAAACAGTAATGATGGATGACATTCAAAGCACTGATTCTATTGCTGAAAAAGATAAT\u001b[0mGGATCCaaaa\n",
"ggggCCTAGGTACGTTTGTCATTACTACCTACTGTAAGTTTCGTGACTAAGATAACGACTTTTTCTATTACCTAGGtttt"
]
},
"execution_count": null,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# If we want to see the sequence more clearly, we can turn it into a `Dseqrecord`\n",
"pcr_product = Dseqrecord(pcr_product)\n",
"\n",
"print(pcr_product.format(\"genbank\"))\n",
"\n",
"pcr_product.figure()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"ename": "SyntaxError",
"evalue": "invalid decimal literal (861700443.py, line 1)",
"output_type": "error",
"traceback": [
"\u001b[0;36m Cell \u001b[0;32mIn[6], line 1\u001b[0;36m\u001b[0m\n\u001b[0;31m 5atg...taa3 |||\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid decimal literal\n"
]
}
],
"source": [
"\n",
"5atg...taa3 |||\n",
"5ccccGGATCCatg3\n",
"3attCCTAGGtttt5\n",
"|||\n",
"3tac...att5\n",
"In [5]: Dseqrecord (pcr_product).figure()\n",
"Out [5]: Dseqrecord(-29)\n",
"ccccGGATCCatgccctaaGGATCCaaaa ggggCCTAGGtacgggattCCTAGGtttt\n",
"In [6]: from Bio. Restriction import BamHI # cuts GGATCC a, b, c = pcr product.cut (BamHI)\n",
"print(a.figure())\n",
"print()\n",
"print (b.figure())\n",
"print()\n",
"print(c.figure())\n",
"Dseqrecord(-9)\n",
"CCCCG\n",
"ggggCCTAG\n",
"Dseqrecord(-19)\n",
"GATCCatgccctaaG GtacgggattCCTAG\n",
"Dseqrecord(-9)\n",
"GATCCaaaa\n",
"Gtttt\n",
"In [7]: vector = Dseqrecord(\"aatgtttttccctCCCGGGcaaaatAGATCTtgctatgcatcatcgatct\"\n",
"circular=True, name=\"vect\")\n",
"In [8]: vector.figure()\n",
"Out[8]: Dseqrecord (050)\n",
"aatgtttttccctCCCGGGcaaaatAGATCTtgctatgcatcatcgatct ttacaaaaagggaGGGCCCgttttaTCTAGAacgatacgtagtagctaga\n",
"In [9]: from Bio. Restriction import BglII # cuts AGATCT\n",
"linear_vector_bgl vector.linearize (BglII)\n",
"rec_vector= (linear_vector_bgl + b).looped().synced(vector)\n",
"rec_vector.figure()\n",
"Out [9]: Dseqrecord (065)\n",
"aatgtttttccctCCCGGGcaaaatAGATCCatgccctaaGGATCTtgctatgcatcatcgatct ttacaaaaagggaGGGCCCgttttaTCTAGGtacgggattCCTAGAacgatacgtagtagctaga\n",
"In [10]: gene2 = Dseqrecord(\"cctCCCatgaaataaGGGcaa\", name=\"gene2\") gene2.add_feature (6,15)\n",
"gene2.figure()\n",
"Out[10]: Dseqrecord(-21)\n",
"cctCCCatgaaataaGGGcaa\n",
"ggaGGGtactttattCCCgtt\n",
"In [11]: from pydna.assembly import Assembly\n",
"from Bio. Restriction import SmaI # cuts CCCGGG\n",
"linear_vector_sma = vector.linearize(SmaI)\n",
"asm = Assembly ((linear_vector_sma, gene2), limit=6)\n",
"candidate, *rest = asm.assemble_circular()\n",
"In [12]: candidate.figure()\n",
"Out[12] - vect_lin❘ 6\n",
"\\/\n",
"^\\\n",
"6 gene2 6\n",
"V\n",
"ハ\n",
"6-\n",
"In [13]: candidate candidate.synced (vector, limit=10)\n",
"In [14]: Dseqrecord (candidate).figure()\n",
"Out[14]: Dseqrecord(059)\n",
"aatgtttttccctCCCatgaaataaGGGcaaaatAGATCTtgctatgcatcatcgatct ttacaaaaagggaGGGtactttattCCcgttttaTCTAGAacgatacgtagtagctaga\n",
"In [16]: from pydna.gel import gel\n",
"from pydna.ladders import GeneRuler_1kb_plus\n",
"In [17] band Dseqrecord(\"GATC\"*500)\n",
"In [18]: gel([ GeneRuler_1kb_plus,\n",
"Out [18]: 20000 -\n",
"[band, ]])\n",
"10000 -\n",
"7000\n",
"5000\n",
"4000\n",
"-\n",
"3000\n",
"-\n",
"2000\n",
"1500\n",
"1000\n",
"700\n",
"500\n",
"400\n",
"300\n",
"200\n",
"75"
]
}
],
"metadata": {
"kernelspec": {
"display_name": ".venv",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.6"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
4 changes: 3 additions & 1 deletion src/pydna/amplify.py
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Original file line number Diff line number Diff line change
Expand Up @@ -17,7 +17,7 @@
from pydna.utils import flatten as _flatten

# from pydna.utils import memorize as _memorize
from pydna.utils import rc as _rc
from pydna.utils import rc as _rc, shift_feature as _shift_feature
from pydna.amplicon import Amplicon as _Amplicon
from pydna.primer import Primer as _Primer
from pydna.seqrecord import SeqRecord as _SeqRecord
Expand Down Expand Up @@ -351,6 +351,8 @@ def products(self):
feats = self.template[
fp.position - fp._fp : rp.position + rp._fp
].features # Save features covered by primers
shift_amount = len(fp.tail)
feats = [_shift_feature(f, shift_amount, None) for f in feats]
tpl = self.template
else:
continue
Expand Down
2 changes: 2 additions & 0 deletions src/pydna/utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -80,6 +80,8 @@ def shift_location(original_location, shift, lim):
"""docstring."""
newparts = []
strand = original_location.strand
if lim is None:
lim = _sys.maxsize

for part in original_location.parts:
new_start = (part.start + shift) % lim
Expand Down

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