Dear all, I have ~40 very large datasets, and it is probably hard for the HPC (Uppmax) to have enough memory to run the pipeline in one shot. So, I want to divide them, and run through the ChIP-seq pipeline separately (10 datasets/run x 4). My goal is to run the pipeline until step 4 “Create normalised bigWig files scaled to 1 million mapped reads”, and get the bam and bigWig files. And I will do peak calling (MACS3) and differential enrichment analysis (CSAW) outside the pipeline. Now, my question is if there is anything I should make it fixed from the code, so that the output bam and bigWig files produced will be reproducible and all of them can be fairly compared to each other, no matter what combination of datasets I have in each run (bam and bigWig files are identical between Scenario 1 & Scenario 2)? e.g. Scenario 1 Run #1: Dataset 1 to 10 Run #2: Dataset 11 to 20 Run #3: Dataset 21 to 30 Run #4: Dataset 31 to 40 Scenario 2 Run #1: Dataset 1, 3, 5, 7, 9, 11, 13, 15, 17, 19 Run #2: Dataset 2, 4, 6, 8, 10, 12, 14, 16, 18, 20 Run #3: Dataset 21, 23, 25, 27, 29, 31, 33, 35, 37, 39 Run #4: Dataset 22, 24, 26, 28, 30, 32, 34, 36, 38, 40 Thanks in advance! Cheers, Kylie #CFP55NZ5G #CPHN84NQ4