SEACR is intended to call peaks and enriched regions from sparse CUT&RUN or chromatin profiling data in which background is dominated by "zeroes" (i.e. regions with no read coverage).

Here we introduce Sparse Enrichment Analysis for CUT&RUN (SEACR), a peak caller designed for the processing of paired-end CUT&RUN data. SEACR is model free and empirically data driven and therefore does not require arbitrary selection of parameters from a statistical model.

In this study, a new approach is proposed for the identification of the optimal cut-point value in ROC analysis. The approach is based on the area under the ROC curve (AUC), sensitivity, and specificity values.

May 1, 2021 · The AUC is highest when the cutoff probability is about 0.11 where as the specificity is highest when the cutoff probability is about 0.8. I observed similar pattern in graphs with other classifiers such as XGB, GBM, Adaboost etc.

Sep 15, 2023 · Brief answer: the AUC is threshold agnostic, it's one of its main selling points. Therefore, it makes no sense to talk about the impact of changing thresholds and AUC, since AUC does not use that information, and is instead derived from …

SEACR is intended to call peaks and enriched regions from sparse Cleavage Under Targets and Release Using Nuclease (CUT&RUN) or chromatin profiling data in which background is dominated by "zeroes" (i.e. regions with no read coverage).

Control (IgG) data bedgraph file to generate an empirical threshold for peak calling. A numeric threshold n between 0 and 1 returns the top n fraction of peaks based on total signal within peaks.

Feb 27, 2025 · When we try to determine the optimal threshold for a continuous predictor variable, we draw a ROC curve and calculate the AUC value. If AUC<0.5 this means that the predictor has an inverse relationship with the outcome. Is that correct?

SEACR: Sparse Enrichment Analysis for CUT&RUN. Contribute to FredHutch/SEACR development by creating an account on GitHub.

Designed as an alternative to ChIP-seq, CUT&RUN is a method for efficiently mapping DNA-protein interactions. The 4DN CUT&RUN processing pipeline consists of trimming, alignment, filtering, visualization, and peak calling.