Menganalisis varian dengan BigQuery

Halaman ini menjelaskan cara menganalisis varian dengan BigQuery. Varian adalah wilayah genom yang telah diidentifikasi berbeda dari genom referensi.

Contoh berikut menunjukkan cara menghitung rasio transisi terhadap transversi dalam polimorfisme nukleotida tunggal (SNP) di setiap kromosom untuk setiap sampel.

Menganalisis varian dari set data Genom Platinum Illumina

Contoh berikut menggunakan data dari project Illumina Platinum Genomes. Data tersebut ada di tabel platinum_genomes_deepvariant_variants_20180823 di BigQuery.

Untuk menganalisis varian dalam tabel, selesaikan langkah-langkah berikut:

  1. Buka halaman BigQuery di konsol Google Cloud.

    Buka halaman BigQuery

  2. Klik Compose query.

  3. Salin dan tempel kueri berikut ke area teks Kueri Baru:

     #standardSQL
 --
 -- Compute the transition/transversion ratio per sample and reference name.
 --
 WITH filtered_snp_calls AS (
   SELECT
     reference_name,
     c.name,
     CONCAT(reference_bases, '->', alternate_bases[ORDINAL(1)].alt) AS mutation
   FROM
     `bigquery-public-data.human_genome_variants.platinum_genomes_deepvariant_variants_20180823` AS v, UNNEST(v.call) AS c
   WHERE
     # Only include biallelic SNPs.
     reference_bases IN ('A','C','G','T')
     AND alternate_bases[ORDINAL(1)].alt IN ('A','C','G','T')
     AND (ARRAY_LENGTH(alternate_bases) = 1
       OR (ARRAY_LENGTH(alternate_bases) = 2 AND alternate_bases[ORDINAL(2)].alt = '<*>'))
     # Skip homozygous reference calls and no-calls.
     AND EXISTS (SELECT g FROM UNNEST(c.genotype) AS g WHERE g > 0)
     AND NOT EXISTS (SELECT g FROM UNNEST(c.genotype) AS g WHERE g < 0)
     # Include only high quality calls.
     AND NOT EXISTS (SELECT ft FROM UNNEST(c.filter) ft WHERE ft NOT IN ('PASS', '.'))
 ),

 mutation_type_counts AS (
   SELECT
     reference_name,
     name,
     SUM(CAST(mutation IN ('A->G', 'G->A', 'C->T', 'T->C') AS INT64)) AS transitions,
     SUM(CAST(mutation IN ('A->C', 'C->A', 'G->T', 'T->G',
                           'A->T', 'T->A', 'C->G', 'G->C') AS INT64)) AS transversions
   FROM filtered_snp_calls
   GROUP BY
     reference_name,
     name
 )

 SELECT
   reference_name,
   name,
   transitions,
   transversions,
   transitions/transversions AS titv
 FROM mutation_type_counts
 WHERE
   transversions > 0
 ORDER BY
   titv DESC,
   name

  4. Klik Run query. Kueri menampilkan respons berikut:

    Baris reference_name nama transisi transversi titv
    1 chr22 NA12892 35299 15017 2,3506026503296265
    2 chr22 NA12889 34091 14624 2,331167943107221
    3 chr17 NA12892 67297 28885 2,3298251687727194
    4 chr22 NA12878 33627 14439 2,3289008934136715
    5 chr22 NA12877 34751 14956 2,3235490772933938
    6 chr22 NA12891 33534 14434 2,323264514341139
    7 chr17 NA12877 70600 30404 2,3220628864623074
    8 chr17 NA12878 66010 28475 2,3181738366988585
    9 chr17 NA12890 67242 29057 2,314141170802216
    10 chr17 NA12889 69767 30189 2,311007320547219
    ... ... ... ... ... ...

Kolom titv menampilkan rasio transisi ke transversi.

Langkah selanjutnya