slurm array job, run a specific task only once

I keep overthinking about how can I optimize my pipeline. Essentially, I have multiple tools that will be executed on two haplotypes (**hap1** and **hap2**) for a plant species. The general structure is as follows:

> tree INLUP_00001
INLUP_00001
├── 1.pre_scaff
├── 2.post_scaff
├── INLUP00233.fastq.gz
├── INLUP00233.filt.fastq.gz
├── INLUP00233.meryl
├── hap1
├── hap2
└── hi-c
    ├── INLUP00001_1.fq.gz
    └── INLUP00001_2.fq.gz

(I will have 16 of these INLUP_????? parent directories) So, with this in mind I organized a job array which reads from the following file

path/to/INLUP_00001/hap1
path/to/INLUP_00001/hap2
path/to/INLUP_00002/hap1
path/to/INLUP_00002/hap2
.
.
.

where I have a variable – ${HAP} – that discriminates which haplotype I'm working on, in which sub-directory the data will be written, and eventual names for each output. This seems to best optimize runtime and resource allocation. However, there is a problem with the very first tool I'm using; this application is the one generating both **hap1** and **hap2** and does not accept the ${HAP} variable. In other words, I have no control on the outputs based on my job array list which will redundantly execute this single command 32 times not only causing issues but also wasting time and resources... Is there a way to control for the execution of this command only one time for each INLUP sample while preserving the control on haplotypes with the ${HAP} variable within the job array? I thought about alternatives with for cycles applied to all other tools in the pipeline to accommodate **hap1** and **hap2**, but they ended up making the script overly long in my opinion and more complex... also the resources allocated for the first tool cannot be easily partitioned/assigned to independent tasks for **hap1** and **hap2** for the other tools. Any idea/help is much appreciated, sorry for the long message if more context is needed I can provide a short MWE of the first few commands.