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OPENSEQ.org
EttA-vs-TsaB
Genes: A B A+B
Length: 555 337 861
Sequences: 8126 3200 1753
Seq/Len: 14.64 9.5 2.04
MirrorTree (Pazo et al. 2001) 0.32
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 0.01 0.08 0.12
2 0.01 0.08 0.17
5 0.01 0.08 0.22
10 0.01 0.08 0.27
20 0.02 0.08 0.34
100 0.06 0.08 0.63
∞ 0.17 0.09 1.97
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
46_S 63_L 1.07 0.60 0.00
352_V 162_A 0.95 0.48 0.00
343_S 258_T 0.92 0.44 0.00
52_M 14_G 0.84 0.35 0.00
455_L 140_T 0.83 0.35 0.00
222_L 270_S 0.82 0.33 0.00
485_N 128_F 0.76 0.28 0.00
52_M 131_V 0.74 0.26 0.00
497_I 265_M 0.74 0.26 0.00
333_Y 16_A 0.74 0.26 0.00
380_I 218_A 0.74 0.26 0.00
330_R 60_Q 0.71 0.23 0.00
388_L 92_A 0.71 0.23 0.00
215_I 114_G 0.71 0.23 0.00
215_I 87_A 0.70 0.23 0.00
198_V 245_D 0.70 0.22 0.00
148_A 76_V 0.69 0.22 0.00
232_L 99_A 0.69 0.22 0.00
343_S 289_E 0.69 0.21 0.00
215_I 147_G 0.68 0.21 0.00
85_T 69_T 0.68 0.21 0.00
482_A 195_F 0.68 0.21 0.00
490_F 25_L 0.68 0.21 0.00
147_A 108_P 0.67 0.20 0.00
238_I 75_A 0.67 0.20 0.00
229_I 24_L 0.66 0.19 0.00
261_Q 17_I 0.65 0.19 0.00
21_I 170_A 0.65 0.19 0.00
212_V 99_A 0.65 0.19 0.00
340_D 140_T 0.64 0.18 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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