Find and work with ENCODE single-cell genomics data including scRNA-seq and scATAC-seq. Use when the user asks about single-cell experiments, cell type resolution, clustering from ENCODE data, deconvolution of bulk signals using single-cell references, or comparing single-cell vs bulk profiles. Covers platform differences (10X Chromium, Smart-seq2, Drop-seq), quality limitations of single-cell data, multimodal integration (RNA+ATAC), and cross-study reproducibility concerns. Also use for cell type annotation, gene detection limits, dropout artifacts, and single-cell data structure in ENCODE.
$npx -y skills add ammawla/encode-toolkit --skill single-cell-encodeInstalls into the current project.
Run `npx skills use "https://github.com/ammawla/encode-toolkit" --skill "ammawla/encode-toolkit/single-cell-encode"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/ammawla/encode-toolkit" that are relevant to the current task. Run `npx skills add "https://github.com/ammawla/encode-toolkit"` and select the relevant skills, then follow their instructions.