# Drop unnecessary QC metrics

**URL:** <https://discuss.hail.is/t/drop-unnecessary-qc-metrics/4194>\
**Category:** Hail Query & hailctl\
**Created:** [August 13, 2025, 4:40pm UTC](https://discuss.hail.is/t/drop-unnecessary-qc-metrics/4194 "2025-08-13T16:40:01Z")\
**Posts on this page:** 4\
**Page:** 1

<div class="post-metadata">

**Author:** ![hyslin](https://avatars.discourse-cdn.com/v4/letter/h/ea666f/32.png) [@hyslin](https://discuss.hail.is/u/hyslin)\
**Post date:** [August 13, 2025, 4:40pm UTC](https://discuss.hail.is/t/drop-unnecessary-qc-metrics/4194/1 "2025-08-13T16:40:01Z")

</div>

Hi,

I’m performing variant QC on a MatrixTable with dimensions (56993186, 414830). The data has already been filtered to include only common variants. The remaining steps are to filter for missingness and retain only biallelic SNPs.

For missingness QC, I’m using `.variant_qc.call_rate >= 0.90`. While `hl.variant_qc()` provides a comprehensive set of QC metrics, I only need the `.call_rate` field, and the rest will be removed when I export the results.

Given the long runtime of `variant_qc()`, is it possible to compute only `.call_rate` without calculating all other metrics, to potentially reduce computation time? Additionally, do you have any suggestions for optimizing these QC steps further? Thank you

---

<div class="post-metadata">

**Author:** ![chrisvittal](https://yyz2.discourse-cdn.com/flex036/user_avatar/discuss.hail.is/chrisvittal/32/327_2.png) [@chrisvittal](https://discuss.hail.is/u/chrisvittal)\
**Post date:** [August 13, 2025, 4:49pm UTC](https://discuss.hail.is/t/drop-unnecessary-qc-metrics/4194/2 "2025-08-13T16:49:57Z")

</div>

As we state in the [`variant_qc` documentation](https://hail.is/docs/0.2/methods/genetics.html#hail.methods.variant_qc), call rate is equivalent to `n_called/count_cols`, so the following will suffice:

```python
mt = mt.annotate_rows(
    call_rate = hl.agg.count_where(hl.is_defined(mt.GT)) / mt.count_cols()
)

```

While we attempt to optimize away (and therefore not compute) fields that are not used in your pipeline, that isn’t perfect. Doing things like this is the best way to optimize QC, making sure you’re only computing metrics you need and only one time. For example, if you don’t even need `call_rate` after filtering, you could simply do:

```python
mt = mt.filter_rows(
    hl.agg.count_where(hl.is_defined(mt.GT)) / mt.count_cols() >= 0.90
)

```

---

<div class="post-metadata">

**Author:** ![hyslin](https://avatars.discourse-cdn.com/v4/letter/h/ea666f/32.png) [@hyslin](https://discuss.hail.is/u/hyslin)\
**Post date:** [August 13, 2025, 8:06pm UTC](https://discuss.hail.is/t/drop-unnecessary-qc-metrics/4194/3 "2025-08-13T20:06:47Z")

</div>

Thank you so much for your suggestion. I wanted to confirm whether using `/ mt.count_cols()` is correct here, or if I should use `/ mt.count_rows()` to keep it consistent with `mt.filter_rows()`?

Also, for sample QC, can I use the following similar code to filter on samples?

```python
mt = mt.filter_cols(         
    hl.agg.count_where(hl.is_defined(mt.GT)) / mt.count_cols() >= 0.90
)

```

---

<div class="post-metadata">

**Author:** ![chrisvittal](https://yyz2.discourse-cdn.com/flex036/user_avatar/discuss.hail.is/chrisvittal/32/327_2.png) [@chrisvittal](https://discuss.hail.is/u/chrisvittal)\
**Post date:** [August 13, 2025, 8:33pm UTC](https://discuss.hail.is/t/drop-unnecessary-qc-metrics/4194/4 "2025-08-13T20:33:47Z")

</div>

You’re going to want `count_rows()` there.