Fig. 4: Optimization of P-value estimation algorithm using fitted Beta distribution. | Nature Communications

Fig. 4: Optimization of P-value estimation algorithm using fitted Beta distribution.

From: Improved in situ characterization of protein complex dynamics at scale with thermal proximity co-aggregation

Fig. 4: Optimization of P-value estimation algorithm using fitted Beta distribution.

The algorithm with small number of samples combined with the fitted Beta distribution can simulate the distribution of large number of samples very well as observed for Manhattan distance (a), Δ absolute distance (b) and Δ relative distance (c). d, e Number and functional class of convergent protein complexes identified based on new P-value estimation algorithm. Beta distribution fitting algorithm identifies more dynamically modulated complexes with higher percentage associated with cell cycle and DNA processing generally. The result of virus replication-related complexes with TPCA signatures and TPCA Modulation Signature obtained by the new algorithm maintain a good agreement with those obtained by the traditional algorithm with massive sampling based on Manhattan distance (f), Δ absolute distance (g) and Δ relative distance (h). Source data are provided as a Source Data file.

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