Mapping Suggestions

Quantifications from merged transcription segments.

Signal smoothed using wavelet transform to reduce noise while preserving peak structure.

Statistical significance of element-gene interaction associations.

Regulatory activity signal predicted by a DNN trained on MPRA data.

Trained models capturing sequencing bias patterns based on sequence composition.

Signal expressed as the ratio of experimental signal to input/control, highlighting enrichment over background.

Quantification of functional conservation scores.

Variants showing allele-specific behavior in expression or chromatin accessibility.

Genomic regions selected for predicted signal profile interpretation.

Alignments with sensitive genomic positions masked or removed for privacy protection in controlled-access data sharing.

Generic regulatory links associating genomic elements with target features.

Quantification values for regulatory elements.

Peaks from unidirectional transcription signal, typically associated with gene bodies.

Hierarchically nested topological domains showing multi-scale chromatin organization.

Read count quantifications over defined genic regions.

Signal profile across genomic positions.

IDR-thresholded peaks from pseudoreplicates (subsampled reads) when true replicates unavailable.

Low-dimensional coordinates (UMAP, t-SNE, PCA) for single-cell visualization.

Measurements of mRNA or gene expression stability over time.

Reference hotspot calls at lenient threshold (hotspot1 algorithm).

Genomic regions selected for count contribution score analysis.

Peaks using the optimal IDR cutoff balancing sensitivity and reproducibility.

Reference hotspot calls at stringent threshold (hotspot2 algorithm).

Quantifications over discrete transcription segments.

Quantitative enrichment score over background, measuring signal above expected noise level.

Percentage of TF binding sites by TE subfamily ancestral origin.

Matrix of transcription factor peak counts across samples.

Matrix of fold-change values relative to control across features.

RNA stability measurements scaled across samples.

Peaks using a conservative (stricter) IDR cutoff, yielding high-confidence but smaller peak set.

Manually curated and validated single nucleotide variants.

Model-predicted signal after correction for sequence-composition bias.

Large-scale A (active) and B (inactive) chromatin compartments from PCA of Hi-C contact matrices.

Chromatin contact matrix resolved to individual alleles using phased variants.

Gene weights derived from topic modeling of regulatory data.

Transcriptome-level alignments with sensitive positions redacted.

Count data from reporter codes in CRISPR screen readouts.

Mapping of functionally conserved regions across species.

Reference set of annotated enhancer elements.

Allowlist of genomic regions or barcodes included in analysis.

Computationally predicted enhancer elements based on chromatin signatures (H3K4me1, H3K27ac, accessibility).

Evaluation metrics (AUC, correlation, etc.) assessing predictive model performance.

Sequencing bias profile across genomic positions.

Genomic regions removed from analysis after filtering.

Experimental validation data for predicted enhancers.

Contact matrix computed separately for a specific parental haplotype.

Local minima in signal tracks used in footprint detection or nucleosome positioning analysis.

Matrix of signal values across features and samples.

Peak calls from pseudoreplicates created by subsampling reads from a single experiment.

Contact matrix incorporating variant information.

Reads aligned to a diploid personal genome reference including both parental haplotypes, enabling allele-specific analysis.

Sequence motif model (e.g., convolutional filter weights) from deep learning or motif discovery.

A representative set of IDR-thresholded peaks selected for downstream analysis.

Red channel intensity data from Illumina IDAT microarray files.

Abundance quantifications of guide RNAs from screen data.

Signal of read end positions.

Signal computed from base-level read overlap counts at each genomic position.

Matrix of z-score normalized values across features and samples.

Quantitative signal track showing per-base or per-bin values across the genome, typically in bigWig format.

Guide RNAs targeting genomic safe-harbor loci as controls.

Reads that failed quality control filters and were excluded from downstream analysis.

Data generated for experimental validation purposes.

Peaks from divergent transcription where initiation occurs in both directions from a central point.

Quantifications over transcribed genomic regions.

Variants with haplotype phase resolved, indicating which alleles co-occur on the same chromosome.

Manually curated and validated transcription factor binding sites.

Green channel intensity data from Illumina IDAT microarray files.

Peaks located distal (>2-3kb) from transcription start sites, often representing enhancers.

Signal computed as the sum of per-base read densities across the region.

Replication timing signal expressed relative to a reference.

Percentage of TF motif instances with transposable element ancestral origin.

Per-nucleotide importance scores explaining sequence contribution to predicted signal profiles.

Quantifications from UV-crosslinking enriched RNA segments.

Annotation of repetitive element locations and classes.

Associations linking regulatory elements (commonly enhancers) to their putative target genes.

Unprocessed signal from imaging-based experiments.

File listing chromosome/contig names and lengths, required by many genomics tools.

Expression quantifications of microRNAs (miRNAs).

CpG methylation values smoothed across neighboring sites to reduce noise.

Alignments after preprocessing: duplicate marking, base quality score recalibration, or indel realignment.

Reference set of annotated promoter elements.

DNA methylation status at CHG sequence context (H = A, C, or T), common in plant genomes.

Variants identified as likely causal through statistical fine-mapping within associated loci.

Alignment index for the mitochondrial genome.

Mitochondrial regions excluded from nuclear genome analysis.

Per-nucleotide importance scores explaining sequence contribution to predicted counts (e.g., DeepLIFT, integrated gradients).

Annotation tracks for microRNA genes and precursors.

Quantitative measurements of variant functional effects.

Guide RNAs ranked by screen performance or activity.

Combined peak and background signal data formatted as input for IDR analysis.

Track indicating uniqueness of k-mer sequences across the genome.

Model predicting enhancer activity from sequence or chromatin features.

Cell type labels assigned to individual cells based on marker genes or reference mapping.

Computationally predicted ensembles of 3D genomic structures.

Three-dimensional structural model of a genomic region or chromatin domain.

Peptides identified that are absent from reference databases.

Peaks from bidirectional transcription signal, characteristic of active enhancers and promoters.

Signal normalized against a matched control experiment to remove background and technical artifacts.

Peaks located proximal (<2-3kb) to transcription start sites, often representing promoters.