Similar Datasets
Project description:GoPeaks: histone modification peak calling for CUT&Tag
| PRJNA788483 | ENA
Project description:Cleavage Under Targets and Release Using Nuclease (CUT&RUN) has rapidly gained prominence as an effective approach for mapping protein-DNA interactions, especially histone modifications, offering substantial improvements over conventional chromatin immunoprecipitation sequencing (ChIP-seq). However, the effectiveness of this technique is contingent upon accurate peak identification, necessitating the use of optimal peak calling methods tailored to the unique characteristics of CUT&RUN data. Here, we benchmark four prominent peak calling tools - MACS2, SEACR, GoPeaks, and LanceOtron - evaluating their performance in identifying peaks from CUT&RUN datasets. Our analysis utilizes in-house data of three histone marks (H3K4me3, H3K27ac, and H3K27me3) from mouse brain tissue, as well as samples from the 4DNucleome database. We systematically assess these tools based on parameters such as the number of peaks called, peak length distribution, signal enrichment, and reproducibility across biological replicates. Our findings reveal substantial variability in peak calling efficacy, with each method demonstrating distinct strengths in sensitivity, precision, and applicability depending on the histone mark in question. These insights provide a comprehensive evaluation that will assist in selecting the most suitable peak caller for high-confidence identification of regions of interest in CUT&RUN experiments, ultimately enhancing the study of chromatin dynamics and transcriptional regulation.
2025-06-02 | GSE282809 | GEO
Project description:Benchmarking Peak Calling Methods for CUT&RUN
| PRJNA1190453 | ENA
Project description:Genome-wide mapping of histone modifications is critical to understanding transcriptional regulation. CUT&Tag is a new method for profiling histone modifications, offering improved sensitivity and decreased cost compared with ChIP-seq. Here, we present GoPeaks, a peak calling method specifically designed for histone modification CUT&Tag data. We compare the performance of GoPeaks against commonly used peak calling algorithms to detect histone modifications that display a range of peak profiles and are frequently used in epigenetic studies. We find that GoPeaks robustly detects genome-wide histone modifications and, notably, identifies a substantial number of H3K27ac peaks with improved sensitivity compared to other standard algorithms.
| S-EPMC9252088 | biostudies-literature
Project description:We comprehensively benchmarked CUT&Tag for H3K27ac and H3K27me3 against published ChIP-seq profiles from ENCODE in K562 cells. Combining multiple new and published CUT&Tag datasets, there was an average recall of 54% known ENCODE peaks for both histone modifications. To optimize data analysis steps, we tested peak callers MACS2 and SEACR and identified optimal peak calling parameters. Considering both precision and recall of known ENCODE peaks, the peak callers were comparable in their performance, although peaks produced by MACS2 match ENCODE peak width distributions more closely. We found that reducing PCR cycles during library preparation lowered duplication rates at the expense of ENCODE peak recovery. Despite the moderate ENCODE peak recovery, peaks identified by CUT&Tag represent the strongest ENCODE peaks and show the same functional and biological enrichments as ChIP-seq peaks identified by ENCODE. Our workflow systematically evaluates the merits of methodological adjustments, providing a benchmarking framework for the experimental design and analysis of CUT&Tag studies, and will facilitate future efforts to apply CUT&Tag in human tissues and single cells.
2025-01-14 | GSE286492 | GEO
Project description:We comprehensively benchmarked CUT&Tag for H3K27ac and H3K27me3 against published ChIP-seq profiles from ENCODE in K562 cells. Across a total of 30 new and 6 published CUT&Tag datasets we found that no experiment recovers more than 50% of known ENCODE peaks, regardless of the histone mark. We tested peak callers MACS2 and SEACR, identifying optimal peak calling parameters. Balancing both precision and recall of known ENCODE peaks, SEACR without retention of duplicates showed the best performance. We found that reducing PCR cycles during library preparation lowered duplication rates at the expense of ENCODE peak recovery. Despite the moderate ENCODE peak recovery, peaks identified by CUT&Tag represent the strongest ENCODE peaks and show the same functional and biological enrichments as ChIP-seq peaks identified by ENCODE. Our workflow systematically evaluates the merits of methodological adjustments and will facilitate future efforts to apply CUT&Tag in human tissues and single cells.
2022-03-31 | GSE199611 | GEO
Project description:We developed scNanoSeq-CUT&Tag, a streamlined method by adapting a modified CUT&Tag protocol to Oxford Nanopore sequencing platform for efficient chromatin modification profiling at single-cell resolution. We firstly tested the performance of scNanoSeq-CUT&Tag on six human cell lines: K562, 293T, GM12878, HG002, H9, HFF1 and adult mouse blood cells, it showed that scNanoSeq-CUT&Tag can accurately distinguish different cell types in vitro and in vivo. Moreover, scNanoSeq-CUT&Tag enables to effectively map the allele-specific epigenomic modifications in the human genome andallows to analyze co-occupancy of histone modifications. Taking advantage of long-read sequencing,scNanoSeq-CUT&Tag can sensitively detect epigenomic state of repetitive elements. In addition, by applying scNanoSeq-CUT&Tag to testicular cells of adult mouse B6D2F1, we demonstrated that scNanoSeq-CUT&Tag maps dynamic epigenetic state changes during mouse spermatogenesis. Finally, we exploited the epigenetic changes of human leukemia cell line K562 during DNA demethylation, it showed that NanoSeq-CUT&Tag can capture H3K27ac signals changes along DNA demethylation. Overall, we prove that scNanoSeq-CUT&Tag is a valuable tool for efficiently probing chromatin state changes within individual cells.
2024-09-06 | GSE249799 | GEO
Project description:To understand how Pou4f1 functions in RGC lineage specification and subtype formation, we performed “Cleavage Under Targets & Tagmentation” (CUT&Tag) analysis using a rabbit anti-Pou4f1 antibody and embryonic 16.5 (E16.5) retinal cells to generate barcoded PCR libraries that are enriched for Pou4f1-mediated binding. In parallel, rabbit IgG was used as a negative control for peak calling analysis, and rabbit anti-H3K9ac antibody was used to mark active enhancers and promoters.
2023-04-30 | GSE221209 | GEO
Project description:To map the chromatin binding sites for SMC1 in OE19 cells, we performed CUT&TAG.
2024-09-25 | E-MTAB-14090 | biostudies-arrayexpress