We downloaded FASTQ files for the BICCN dataset from NeMO (https://nemoarchive.org/) and mapped the reads to the mm10 genome using BWA-MEM69. We created a fragment file from the aligned BAM file using sinto (https://github.com/timoast/sinto) and tabix44. We then identified peaks for each brain region using MACS2 (ref. 46) using the CallPeaks function in Signac, with the parameters effective.genome.size = 1.87 × 109. We filtered out peaks with a score <150 to remove low-confidence peaks, resulting in a total of 263,815 peaks. Code to produce the BICCN fragment file and unified peak set is available at https://github.com/timoast/BICCN.
