Limitations of ASPEN

  • Paired-End data required: ASPEN necessitates paired-end sequencing libraries, as its current design does not support single-end data. Future updates aim to incorporate single-end data compatibility.

  • Infrastructure limit: Designed primarily for the BIOWULF High-Performance Computing (HPC) system at the National Institutes of Health (NIH), ASPEN's configuration relies on resources specified in the config.yaml file, which are tailored to the BIOWULF file system. Adapting ASPEN for use on other HPC platforms may require adjustments, such as replicating or generating local reference data, modifying code, and accommodating different job schedulers. Plans are underway to deploy ASPEN on the Frederick Research Computing Environment (FRCE) cluster in Frederick.

  • Footprinting analysis: While ASPEN does not perform footprinting analysis, it is compatible with the CCBR-TOBIAS pipeline, a separate tool designed for this purpose. TOBIAS (Transcription factor Occupancy prediction By Investigation of ATAC-seq Signal) analyzes ATAC-seq data to predict transcription factor occupancy but generates a substantial number of small files. ASPEN's output can serve as direct input for the CCBR_TOBIAS pipeline, facilitating integrated analyses.

  • Genomes supported: Genomes supported is limited to:

Genome Assembly Organism Scientific Name
hg38 Human Homo sapiens
hg19 Human Homo sapiens
mm10 Mouse Mus musculus
mmul10 Rhesus Monkey Macaca mulatta
bosTau9 Domestic Cattle Bos taurus
hs1 Human Homo sapiens (T2T-CHM13)
hs1_chrR Human Homo sapiens (T2T-CHM13 + chrR rDNA unit; see note below)

Use hs1_chrR for ribosomal DNA chromatin accessibility studies

Standard genome assemblies mask or collapse ribosomal DNA (rDNA) repeat loci, making it impossible to call ATAC-seq peaks in these regions. hs1_chrR is a customized version of the T2T-CHM13 (hs1) assembly where endogenous rDNA-like sequences are masked throughout the canonical chromosomes, and a single consensus rDNA unit (NCBI KY962518.1, modified) is inserted as an additional chromosome chrR. This design ensures that rDNA-mapping reads are captured unambiguously on chrR rather than being lost to multi-mapping or suppressed by masking.

When to choose hs1_chrR over hs1:

  • Your experiment involves a perturbation that may affect nucleolar chromatin or ribosomal gene accessibility (e.g., RNA Pol I inhibition, nucleolar stress, epigenetic reprogramming).
  • You want to quantify ATAC-seq peaks at rDNA promoters, the transcribed region, or the intergenic spacer (IGS) of the ribosomal repeat unit.
  • You need FRiP scores, TSS enrichment, or differential accessibility analysis specifically for rDNA loci alongside the rest of the genome.

Reference: George SS, Pimkin M, Paralkar VR. "Construction and validation of customized genomes for human and mouse ribosomal DNA mapping." J Biol Chem (2023). https://doi.org/10.1016/j.jbc.2023.105529

Genome files: https://github.com/vikramparalkar/rDNA-Mapping-Genomes

  • Spike-in genomes supported: Spike-in genomes supported is limited to:
Genome Assembly Organism Scientific Name
dmelr6.32 Fruit Fly Drosophila melanogaster
ecoli_k12 E. coli Escherichia coli