您可以对每个group_by使用两个any，如下所示：

library(dplyr)
data %>%
  group_by(gene) %>%
  filter(any(group == "Healthy") & any(group == "Light"))
#> # A tibble: 2 × 7
#> # Groups:   gene [1]
#>   gene   id      group   snp             ref total ref_condition
#>   <chr>  <chr>   <chr>   <chr>         <int> <int> <chr>        
#> 1 ZYG11B Healthy Healthy chr1:52769202     1     2 Healthy      
#> 2 ZYG11B Light   Light   chr1:52779185     1     4 Healthy

创建于2023年1月23日，使用reprex v2.0.2

简而言之：

data%>%
  group_by(gene)%>%
  filter(sum(group=="Light")>=1 & sum(group=="Healthy")>=1)%>%
  ungroup

  gene   id      group   snp             ref total ref_condition
  <fct>  <fct>   <fct>   <fct>         <int> <int> <fct>        
1 ZYG11B Healthy Healthy chr1:52769202     1     2 Healthy      
2 ZYG11B Light   Light   chr1:52779185     1     4 Healthy

原答复：如果n_light>=1 & n_healthy>=1，我们可以计算光和健康的数量并过滤行

library(dplyr)
data%>%
  group_by(gene)%>%
  mutate(n_light=sum(group=="Light"),
         n_healthy=sum(group=="Healthy"))%>%
  filter(n_light>=1 & n_healthy>=1)%>%
  ungroup

  gene   id      group   snp             ref total ref_condition n_light n_healthy
  <fct>  <fct>   <fct>   <fct>         <int> <int> <fct>           <int>     <int>
1 ZYG11B Healthy Healthy chr1:52769202     1     2 Healthy             1         1
2 ZYG11B Light   Light   chr1:52779185     1     4 Healthy             1         1

并通过%>%select(-n_light,n_healthy), if needed移除辅助列n_light,n_healthy