使用 BigQuery 分析变体

本页介绍如何使用 BigQuery 分析变体。变体是已被确认为与参考基因组不同的基因组区域。

下面的例子说明了如何计算每个样品的每条染色体单核苷酸多态性 (SNP) 中转换到颠换的比率。

分析来自 Illumina Platinum Genomes 数据集的变体

以下示例使用来自 Illumina Platinum Genomes 项目的数据。数据位于 BigQuery 的 platinum_genomes_deepvariant_variants_20180823 表中。

如需分析表中的变体，请完成以下步骤：

  1. 在 Google Cloud 控制台中转到 BigQuery 页面。

    转到 BigQuery 页面

  2. 点击编写查询。

  3. 将下述查询复制粘贴到新查询文本区域中：

     #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. 点击运行查询。查询会返回以下响应：

    行 reference_name 名称 转换 颠换 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
    … … … … … …

titv 列显示了转换到颠换的比率。

后续步骤