Your First Hail Query
We recommend using IPython, a super-powered Python terminal:
pip install ipython
Start an IPython session by copy-pasting the below into your Terminal.
ipython
Let’s randomly generate a dataset according to the Balding-Nichols Model. The dataset has one-hundred variants and ten samples from three populations.
import hail as hl
mt = hl.balding_nichols_model(n_populations=3,
n_samples=10,
n_variants=100)
mt.show()
The last line, mt.show()
, displays the dataset in a tabular form.
2020-05-09 19:08:07 Hail: INFO: Coerced sorted dataset
+---------------+------------+------+------+------+------+
| locus | alleles | 0.GT | 1.GT | 2.GT | 3.GT |
+---------------+------------+------+------+------+------+
| locus<GRCh37> | array<str> | call | call | call | call |
+---------------+------------+------+------+------+------+
| 1:1 | ["A","C"] | 0/1 | 1/1 | 0/1 | 0/1 |
| 1:2 | ["A","C"] | 1/1 | 0/1 | 1/1 | 0/1 |
| 1:3 | ["A","C"] | 0/1 | 1/1 | 1/1 | 1/1 |
| 1:4 | ["A","C"] | 0/0 | 0/0 | 0/1 | 1/1 |
| 1:5 | ["A","C"] | 0/1 | 0/0 | 0/1 | 0/0 |
| 1:6 | ["A","C"] | 1/1 | 0/1 | 0/1 | 0/1 |
| 1:7 | ["A","C"] | 0/0 | 0/1 | 0/1 | 0/0 |
| 1:8 | ["A","C"] | 1/1 | 0/1 | 1/1 | 1/1 |
| 1:9 | ["A","C"] | 1/1 | 1/1 | 1/1 | 1/1 |
| 1:10 | ["A","C"] | 1/1 | 0/1 | 1/1 | 0/1 |
| 1:11 | ["A","C"] | 0/1 | 1/1 | 1/1 | 0/1 |
+---------------+------------+------+------+------+------+
showing top 11 rows
showing the first 4 of 10 columns</code></pre>
Next Steps
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