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OPENSEQ.org
cardiac myosin vs MyBP-C C3
Genes: A B A+B
Length: 800 98 862
Sequences: 2708 8316 188
Seq/Len: 3.38 84.86 0.22
MirrorTree (Pazo et al. 2001) 0.09
Download Alignment
We filter this alignment to remove positions that have > 75% gaps before running GREMLIN.

[Show HHblits results] - Maybe useful in deciding what regions to trim.
Δgene Ratio of paralogs Joined
A B Seq/Len
1 0.06 0.12 0.00
2 0.06 0.14 0.00
5 0.06 0.16 0.01
10 0.06 0.17 0.03
20 0.07 0.19 0.03
100 0.09 0.22 0.13
∞ 0.12 0.23 0.21
Paired alignment generation
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Sequence A E-value:
Iterations:
Sequence B E-value:
Iterations:
Δgene MSA
Figure 1: The effect of Δgene on ratio of paralogs in the genome for each gene, and the number of sequences in the resulting joined alignment. Figure 2: Distribution of Δgene across all genomes. Figure 3: Current parameters. You can use the form to adjust the parameters and resubmit the job!
GREMLIN results (Scaled_score > 1):
Figure 4: The darker and larger the blue dots, the higher strength in coevolution. 		Inter Residue pairs sorted by strength in coevolution signal:
i j Scaled Score Prob I_Prob
344_E 94_L 1.30 0.24 0.00
115_Y 70_I 1.27 0.23 0.00
93_L 81_Y 1.26 0.22 0.00
95_F 41_V 1.22 0.21 0.00
742_A 41_V 1.20 0.20 0.00
563_F 70_I 1.17 0.19 0.00
670_V 62_I 1.17 0.19 0.00
137_E 30_L 1.17 0.18 0.00
742_A 30_L 1.13 0.17 0.00
542_K 96_V 1.07 0.15 0.00
171_N 81_Y 1.06 0.15 0.00
344_E 22_V 1.01 0.13 0.00
339_L 83_C 0.97 0.12 0.00
681_P 70_I 0.97 0.12 0.00
683_V 73_C 0.95 0.12 0.00
443_I 30_L 0.94 0.11 0.00
788_I 16_L 0.93 0.11 0.00
486_Q 22_V 0.93 0.11 0.00
156_S 68_L 0.90 0.10 0.00
432_Y 81_Y 0.88 0.10 0.00
307_P 70_I 0.88 0.10 0.00
377_G 94_L 0.87 0.10 0.00
158_S 16_L 0.87 0.10 0.00
558_G 41_V 0.87 0.10 0.00
229_A 91_S 0.86 0.10 0.00
468_F 47_G 0.84 0.09 0.00
352_L 28_I 0.84 0.09 0.00
76_V 50_I 0.84 0.09 0.00
98_E 77_D 0.83 0.09 0.00
258_L 46_N 0.83 0.09 0.00
Figure 5: The i (protein A) and j (protein B) are positions as given in the query sequences.

Scaled Score = raw_score/average(raw_scores)
Prob = P(contact | scaled_score, seq/len)
I_Prob = P(contact | scaled_score, seq/len, top_inter_score)
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