This track is part of the Fiber-seq collection. It shows the fraction of Fiber-seq molecules on which a given position was found to be accessible, in seven cell lines that are widely used in functional genomics. All seven are drawn as a single overlay with one color per cell line, so a position that is open in one cell type and closed in another is easy to spot. A position covered by Fiber-seq molecules but not found accessible on any of them is scored zero; only positions with no molecule coverage at all carry no value.
For the same signal in all 41 samples, along with called peaks and a per-haplotype breakdown, see the Fiber-seq Compendium track.
The vertical axis is percent of molecules accessible, fixed from 0 to 100, and the seven cell lines are overlaid transparently in these colors:
| GM12878, lymphoblastoid | |
| K562, erythroleukemia | |
| HepG2, hepatocyte | |
| H1, embryonic stem cell | |
| Hap1, near-haploid myeloid | |
| Hek293T, embryonic kidney | |
| Jurkat, T-lymphocyte |
Individual cell lines can be turned on and off, and the graph type and windowing function changed, on this configuration page. The default windowing function is maximum, so a narrow accessible element is not averaged away when the view is zoomed out.
Permeabilized cells were treated with the Hia5 N6-adenine methyltransferase, which methylates adenines in DNA that is not protected by a bound protein, and high molecular weight DNA was then prepared into PacBio SMRTbell libraries and sequenced. Adenine methylation was called from the reads with fibertools-rs, and reads were aligned and haplotype-phased. The FIRE pipeline then applied a semi-supervised XGBoost classifier to each read to label methyltransferase-sensitive patches as Fiber-seq Inferred Regulatory Elements (FIRE elements). The classifier was trained on 21 GM12878 experiments spanning 5.8 to 13.3 percent adenine methylation, using DNase I and CTCF ChIP-seq peaks as positive labels, so that it generalizes across samples with different methylation efficiency. The percent-accessible value shown here is the number of reads carrying a FIRE element at a position divided by the number of reads covering it. See Vollger et al. for the full description.
The bigWig files were downloaded from the Stergachis lab data server, one all.percent.accessible.bw per sample, and copied to UCSC without modification. The download and verification steps are documented in the makeDoc, and the scripts that build the track are in the kent source tree.
The data can be explored interactively in table format with the Table Browser or the Data Integrator and exported from there to spreadsheet or tab-sep tables. From scripts, the data can be accessed through our API, one cell line at a time, for example -track=fiberSeqAcc_PM00001 for GM12878. The container name fiberSeqAcc holds no +track=fiberSeqAcc_PM00001 for GM12878. The collection name fiberSeqAcc holds no data of its own and cannot be queried.
For automated download and analysis, the signal is stored in bigWig files that can be downloaded from our download server. There is one directory per sample accession, and the file for this track is called all.percent.accessible.bw. Individual regions or the whole genome can be obtained using our tool bigWigToBedGraph, which can be compiled from the source code or downloaded as a precompiled binary for your system. Instructions for downloading source code and binaries can be found here. The tool can also be used to obtain values within a given range, e.g. bigWigToBedGraph http://hgdownload.soe.ucsc.edu/gbdb/hg38/fiberSeq/PM00001/all.percent.accessible.bw -chrom=chr21 -start=0 -end=100000000 stdout
The original data can be downloaded from the Stergachis lab data server, and the lab maintains its own track hub and documentation at fiberseq.github.io.
Thanks to Mitchell Vollger, Andrew Stergachis and Shane Neph for generating this data and for making it available to the browser.
Vollger MR, Swanson EG, Neph SJ, Ranchalis J, Munson KM, Ho CH, Cheng YHH, Sedeño-Cortés AE, Fondrie WE, Bohaczuk SC et al. A haplotype-resolved view of human gene regulation. bioRxiv. 2025 Jun 2;. PMID: 40501892; PMC: PMC12157683
Stergachis AB, Debo BM, Haugen E, Churchman LS, Stamatoyannopoulos JA. Single-molecule regulatory architectures captured by chromatin fiber sequencing. Science. 2020 Jun 26;368(6498):1449-1454. PMID: 32587015