When I edit a plasmid with Coral and write it to a file, the annotation colors are lost.

When installing pymbt, I get the following error:

error: can't copy 'pymbt/analysis/_sequencing/calign.c': doesn't exist or not a regular file

It goes away after I manually run

cythonize(['pymbt/analysis/_sequencing/calign.pyx'])

and restart the build.

I'm using Python 2.7 and Cython 0.23.

it is not working, I got this error:

error: subprocess-exited-with-error

× python setup.py egg_info did not run successfully.
│ exit code: 1
╰─> [1 lines of output]
Coral is currently compatible only with Python 2.
[end of output]

EG

>>> from coral import DNA
>>> foo = DNA("ATTTTT")
>>> "CCGG" + foo
ATTTTTCCGG
TAAAAAGGCC
>>> "CCGG" + foo.top
ATTTTTCCGG
>>> foo.top + "CCGG"
ATTTTTCCGG

.locate doesn't seem to find all of the sequences that are present in a sequence file that is read in through the .read_sequencing. However when I put in the sequence of the file manually using the .DNA("") command .locate finds all the sequences present. The below code should find three instances of sequences in the targetSequences list but only finds one when the DNA file is uploaded using .read_sequencing.

Here is example code of what I'm referring to:

seqs = cr.seqio.read_sequencing('/Users/milesgander/Desktop/10-317729264_seq')

seq commented out below is the would be manually entered sequence

seq=cr.DNA("NNNNNNNNNNNNNNNGNTTTCNGTATAATGTTACATGCGTACACGCGTCTGTACAGAAAAAAAAGAAAAATTTGAAATATAANTAACGTTCTTAATACTAACATAACTATAAAAAAATAAATAGGGACCTAGACTTCAGGTTGTCTAACTCCTTCCTTTTCGGTTAGAGCGGATGTGGGGGGAGGGCGTGAATGTAAGCGTGACATAACTAATTGACTCGAGGTCGACGGTATCAGTCCCATTCGCCATGCCGAAGCATGTTGCCCAGCCGGCGCCAGCGAGGAGGCTGGGACCATGCCGGCCAAAAGCACCGACTCGGTGCCACTTTTTCAAGTTGATAACGGACTAGCCTTATTTTAACTTGCTATTTCTAGCTCTAAAACAAGTTATTCAATCACGTTCCGACGAGCTTACTCGTTTCGTCCTCACGGACTCATCAGGGAACGTTTGTAGATCCACTAGTTCTAGAATCCAATATCTAGATTAGTGTGTGTATTTGTGTTTGTGTGTCTATAGAAGTATAGTAATTTATGCGGAACGTGATTGAATAACTTAGGAAAGAATATTTAGAGAAAAGAAGAAAACAAGAGTTTTATATACATACAGAGCACATGCATGCCAAAGTTTGAATAGGAAATGCGATACAGTACCCGGGCTGCAGGAATTTACTTATTAGTCAAGTAGGGGAATAATTTCAGGGAACTGGTTTCAACCTTTTTTTTCAGCTTTTTCCAAATCAGAGAGAGCAGAAGGTAATAGAAGGTGTAAGAAAATGAGATAGATACATGCGTGGGTCAATTGCCTTGTGTCATCATTTACTCCAGGCAGGTTGCATCACTCCATTGAGGTTGTGCCCGTTTTTTGCCTGTTTGTGCCCCTGTTCTCTGTAGTTGCGCTAAGAGAATGGACCTATGAACTGATGGTTGGTGAAGAAAACAATATTTTGGTGCTGGGATTCTTTTTTTTTTCTGGATGCCAGCTTAAAAAGCGGGCTCCATTATATTTAGTGGNNGCCAGGGAATAAACTGTNCACCCANACACCTACGATGTTANATATTCTGTGNANCCCNNCCCCCCTNNTTTTGGGGCATGTANNNNNNACANNNNNNNNAAANGNTAANTTTTTNNNCTAAATAAANNNNNAAAATCNNNNNCTNNTTNNNNNTTTACNNNNNNNNNNNANNNNNNNNNNNANNNNNANNNNNNNNNNCTTTTNCNNNNNCTGNNNNAANNNNNNNNN")

targetNames = ["W5", "W8", "W10", "W14", "W17", "W19", "W20", "W22", "W34", "W36", 'F1', "F2", "F3", "F4", "F5", "F6", "F7", "F8", "F9", "F10"]

targetSequences = [cr.DNA('GGAACGTGATTGAATAACTT'), cr.DNA('ACCAACGCAAAAAGATTTAG'), cr.DNA('CATTGCCATACACCTTGAGG'), cr.DNA('GAAAATCACAACTCTACTGA'), cr.DNA('GAAGTCAGTTGACAGAGTCG'), cr.DNA('GTGGTAACTTGCTCCATGTC'), cr.DNA('CTTTACGTATAGGTTTAGAG'), cr.DNA('CGCATTTCCTATTCAAACTT'), cr.DNA('GCAACCCACAAATATCCAGT'), cr.DNA('GTGACATAAACATTCGACTC'), cr.DNA('GGGCAAAGAGACGCTTGTCG'), cr.DNA('GAAGTCATCGCTTCTTGTCG'), cr.DNA('GAGTTGACAAAGTATAACTT'), cr.DNA('GAAGTTTCAGAATCTCGACG'), cr.DNA('GGCTAGGATCCATCTGACTT'), cr.DNA('GCAACCATAGACTCTCCAGG'), cr.DNA('ACCACAACTGAGTCGAACCT'), cr.DNA('GGGTAGCAACACTCGTACTT'), cr.DNA('GTAAAAGATAACTCTGTTGC'), cr.DNA('TCTACCCGAGACTCAAACGG') ]

inds=[]
names=[]

seq=seqs[1]

for x in range(0, 19):
y=seq.locate(targetSequences[x])
if y[0]!=[]:
inds.append(y[0])
names.append(targetNames[x])
if y[1]!=[]:
inds.append(y[1])
names.append(targetNames[x])
print y
print seq.name
print names

Error that arises when implementing a PCR with overlapping primers: "NotImplementedError: Primer dimer amplification unimplemented."

To reproduce:

import coral as pbt

t = pbt.DNA("CACCAC")
x3 = pbt.DNA("CATTGCATCTATAAACGAGTCTTAC")
x4= pbt.DNA("CATTGCTTAACATACAGAGTCTTAC")
b = pbt.DNA("CTGTCCTTTATTTCGCTCTTCC")
c = pbt.DNA("CATTGCCACCTCCACCCTCCAG")
a3 = pbt.DNA("CATTGCATATTTCCCAGAGTCTTAC")
a4 = pbt.DNA("CATTGCCAACCCATTCGAGTCTTAC")

JoinX4X3 = b + t + x4 + t + x3 + t + a3 + a3 + c
JoinX4 = b + t + x4 + t + a2 + t + c
template2 = b + t + x4 + t

primer_f2, primer_r2 = pbt.design.primers(template2, tm=74, overhangs=(pbt.DNA(""), (a2 + t + c).reverse_complement()))

rxn2 = pbt.reaction.pcr(JoinX4X3,primer_f2,primer_r2)

Coral does not appear to be Python 3 compatible, but setup.py and pip will allow it to install in a Python 3 environment, only to have it fail on initial import. It might make sense to have a check for this in setup.py.

Upon execution of design.gibson, the coral.DNA objects in the seq_list are altered. Input *seq_list * should remain unchanged following execution of this method. We should investigate the source of this bug.

When trying to digest the vector pENTR223.1 with an SfiI RestrictionSite object from the Rebase.get() method, I noticed that it always returns a single uncut DNA object, when it should cut twice and return two sequences. I tried a few things and it seems like the issue is that the SfiI recognition sequence contains 5 'N' bases, GGCCNNNNNGGCC. I manually created two restriction site objects with the ambiguous N's replaced with the corresponding vector sequences, which worked fine. I also tried the reverse, N-masking the vector sequence at the cut site, which caused weird behavior with the rebase restriction site. That digest output the 2 correct fragments, as well as two empty DNA objects. Below is the script I used for testing.

import coral as cor


# fragment of pENTR223.1
# original seq and N-masked version
vector_seq = 'cccaaataatgattttattttgactgatagtgacctgttcgttgcaacaaattgatgagcaatgcttttttataatgccaactttgtacaaaaaagcaga' \
                  'agggccgtcaaggccagaaggagatataaccatgtaaggcctcatgggcccagctttcttgtacaaagttggcattataaaaaataattgctcatcaatt'
vector_seq_NNNNN = 'cccaaataatgattttattttgactgatagtgacctgttcgttgcaacaaattgatgagcaatgcttttttataatgccaactttgtacaaaaaagcaga' \
                  'agggccNNNNNggccagaaggagatataaccatgtaaggccNNNNNggcccagctttcttgtacaaagttggcattataaaaaataattgctcatcaatt'

vector = cor.DNA(vector_seq, circular=True) # DNA object from original vector sequence
vector_NNNNN = cor.DNA(vector_seq_NNNNN, circular=True) # DNA object from vector sequence with NNNNN to match SfiI cut site

# define restriction sites
# from rebase 
reb = cor.database.Rebase()
sfiI = reb.get('SfiI')
#  make two manually defined sfiI restriction sites
sfiIa = cor.sequence.RestrictionSite(cor.DNA('GGCCgtcaaGGCC'), (8, 5) )
sfiIb = cor.sequence.RestrictionSite(cor.DNA('GGCCtcatgGGCC'), (8, 5) )

# digest original vector with sfiI from rebase
# yields one fragment... does not cut!

digest_one = cor.reaction.digest(vector.copy(), sfiI)
print('Original vector with rebase sfiI digest yields ' + str(len(digest_one)) + ' fragments')

# digest N-masked vector with sfiI from rebase
# yields 4 fragments... 2 empty objects and 2 correct objects

digest_two = cor.reaction.digest(vector_NNNNN.copy(), sfiI)
print('N-masked vector with rebase sfiI digest yields ' + str(len(digest_two)) + ' fragments')
for seq in digest_two:
    print(len(seq))

# digest original vector with manually defined sfiI sites
# yields two fragments... correct!

digest_three = cor.reaction.digest(vector.copy(), sfiIa)
digest_three = cor.reaction.digest(digest_three[0].copy(), sfiIb)
print('Original vector with manually defined sfiI digest yields ' + str(len(digest_three)) + ' fragments')

# digest N-masked vector with manually defined sfiI sites
# yields one fragment... does not cut!

digest_four = cor.reaction.digest(vector_NNNNN.copy(), sfiIa)
digest_four = cor.reaction.digest(digest_three[0].copy(), sfiIb)
print('N-masked vector with manually defined sfiI digest yields ' + str(len(digest_four)) + ' fragments')

Annealing (e.g. when running design.pcr) with a primer that's longer than the template results in this error: ValueError: Search pattern longer than searchable sequence..

To reproduce:
import coral as crl
template = crl.design.random_dna(50)
primer1, primer2 = crl.design.primers(template, overhangs=[crl.design.random_dna(200), crl.DNA('')])
crl.reaction.pcr(template, primer1, primer2)

Suggested solution: limit template search sequence length by both the primer length and the template length.