Update scripts/variantstore/docs/aou/AOU_DELIVERABLES.md

Co-authored-by: George Grant <[email protected]>

scripts/variantstore/docs/aou/AOU_DELIVERABLES.md

@@ -128,7 +128,7 @@ The pipeline takes in the VDS and outputs a variant annotations table in BigQuer
       - For both PGEN and VCF extracts of ACAF only:
         - Specify an `extract_overhead_memory_override_gib` of 5 (GiB, up from the default of 3 GiB).
         - Specify a `y_bed_weight_scaling` of 8 (up from the default of 4).
-        - When re-running the extract workflow with call caching enabled, it will be necessary to increase memory in the `ExtractTask` / `PgenExtractTask` tasks. Due to the way call caching works in Cromwell (i.e. the `memory` runtime attribute is not part of the call caching hashes), it is possible to edit the value of the `memory` runtime attribute of a task without breaking call caching. However, do *not* alter the value of the `memory_gib` input parameter as changing that absolutely will break call caching and will cause tens of thousands of shards to re-run needlessly! Both VCF and PGEN extracts can have their memory set to `"50 GiB"` for the call-caching re-run. Most extract shards should finish on the first re-run attempt, but a few stragglers will likely OOM and automatically re-run with more memory.
+        - When re-running the extract workflow with call caching enabled, it will be necessary to increase memory in the `ExtractTask` / `PgenExtractTask` tasks. Due to the way call caching works in Cromwell (i.e. the `memory` runtime attribute is not part of the call caching hashes), it is possible to edit the value of the `memory` runtime attribute of a task _in the WDL_ without breaking call caching. However, do *not* alter the value of the `memory_gib` input parameter as changing that absolutely will break call caching and will cause tens of thousands of shards to re-run needlessly! Both VCF and PGEN extracts can have their memory set to `"50 GiB"` for the call-caching re-run. Most extract shards should finish on the first re-run attempt, but a few stragglers will likely OOM and automatically re-run with more memory.
     - If you want to collect the monitoring logs from a large number of `Extract` shards, the `summarize_task_monitor_logs.py` script will not work if the task is scattered too wide.  Use the `summarize_task_monitor_logs_from_file.py` script, instead, which takes a FOFN of GCS paths instead of a space-separated series of localized files.
     - These workflows do not use the Terra Data Entity Model to run, so be sure to select the `Run workflow with inputs defined by file paths` workflow submission option.