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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
 <h3>Print motives as list</h3>
Step1:  <h3>Display Sequence logo of unaligned motives</h3>
Step2:  <h3>Multiple Sequence Alignment of motives with Muscle</h3>
Note
Step3:  <h3>Display sequence logo of aligned motives</h3>
Step4:  <h3>Position Weight Matrices of Motives</h3>
Step5:  <h4>Display PWM of a single motif</h4>
Step6:  <h3>Scoring a single sequence w.r.t a motif</h3>
Step7:  <h3> Transform with HMM as scoring criteria</h3>
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Python Code:
#printing motives as lists
for motif in glam2.motives_list:
    for m in motif:
        print m
    print
Explanation: <h3>Print motives as list</h3>
End of explanation
glam2.display_logo(do_alignment=False)
glam2.display_logo(motif_num=1)
Explanation: <h3>Display Sequence logo of unaligned motives</h3>
End of explanation
glam2.align_motives()    #MSA with Muscle
motives1=glam2.aligned_motives_list
for m in motives1:
    for i in m:
        print i
    print
Explanation: <h3>Multiple Sequence Alignment of motives with Muscle</h3>
Note: Motives in this example were already aligned, hence no dashes appear in the alignment
End of explanation
glam2.display_logo(do_alignment=True)
Explanation: <h3>Display sequence logo of aligned motives</h3>
End of explanation
glam2.display()
glam2.matrix()
Explanation: <h3>Position Weight Matrices of Motives</h3>
End of explanation
glam2.display(motif_num=3)
Explanation: <h4>Display PWM of a single motif</h4>
End of explanation
test_seq = 'GGAGAAAATACCGC' * 10
seq_score = glam2.score(motif_num=2, seq=test_seq)
print seq_score
Explanation: <h3>Scoring a single sequence w.r.t a motif</h3>
End of explanation
glam_3 = Glam2(alphabet='dna', gap_in_alphabet=True, scoring_criteria='hmm', alignment_runs=3)
matches = glam_3.fit_transform(fasta_file="seq9.fa", return_match=True)
for m in matches: print m
Explanation: <h3> Transform with HMM as scoring criteria</h3>
End of explanation
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