From bc79b74cc397cb2462df3904715887c12d3ee5fa Mon Sep 17 00:00:00 2001 From: Hongxiang Li Date: Fri, 6 Nov 2026 10:55:38 +0800 Subject: [PATCH] docs: clarify empirical E-value audit ceiling and cluster prefetch --- README.md | 26 ++++++++++++++++---------- 1 file changed, 16 insertions(+), 10 deletions(-) diff --git a/README.md b/README.md index 0fe5a8b..8b9530d 100644 --- a/README.md +++ b/README.md @@ -228,16 +228,22 @@ rfoldsearch attach-calibration --db target_nr80.pt \ --output target_calibrated.pt ``` -Fitting audits high-scoring background hits with US-align and can take a -while. An interrupted fit resumes from `--workdir`, and precomputed scores or -TM-scores can be supplied to skip those steps (see `--help`). - -By default, background hits are audited up to an uncorrected E-value of 100. -Above the highest audited value, reported E-values are extrapolated along a -power law and capped at the number of clusters in the database. The parameter -file records the highest E-value that the audit supports directly; if a -database needs reliable E-values beyond it, refit with a larger -`--audit-ceiling`. +Fitting audits high-scoring cluster leaders with US-align. When a leader +needs auditing, eligible unaudited members of the same cluster within the +current `E0` ceiling are checked together. Structurally related members +are excluded, cluster leaders are recomputed, and the model is refitted +until no qualifying unaudited leaders remain. This reduces repeated fitting +for large clusters. An interrupted fit reuses cached audits from `--workdir`, +and precomputed scores or TM-scores can be supplied (see `--help`). + +By default, structural auditing and empirical-map fitting both use an +uncorrected E-value (`E0`) ceiling of 100. Set `--audit-ceiling` to change +both; the parameter file records the actual ceiling in +`audit_raw_evalue_ceiling` and `validation_status` (for example, +`audited-e0-le-400`). Above the largest empirical-map knot, reported E-values +follow an endpoint-anchored power law capped at the number of database +clusters. These are extrapolations, not independently validated estimates; +refit with a larger ceiling to extend the observed calibration range. ### Python API