weird MAplot or volcano plot of DESeq2 diff result

Hi, every one.
I find a werid MAplot or volcano plot of DESeq reuslt. I am wondering whether you can give me some advice.

This diff result is from two cell type bulk RNA-seq. I use two specific marker to get these two cell type using Flow cytometer. I alreadly know these cell type have very different RNA composition.

As you can see, the MA-plot is not like DESeq2 manul example. And the volcano plot is more werid, it looks like -log10(padj) is the linear function of log2FoldChange.

I have post same question in Bioconductor support. Here is the link.

If you can not see the picture, Here is the two link



If you want to repeat my data, here is my data link:

And here is my code

# Prepare -----------------------------------------------------------------

# load up the packages


# Set Options
options(stringsAsFactors = F)

# load up the data
data <- read.table("rawdata/count/WFX_count_Rmatrix.txt",
                   header = TRUE,
                   row.names = 1)

coldata <- data.frame(row.names = colnames(data),
                      type = rep(c("Fx593", "Fx600"), each = 2))

# DESeq2 ------------------------------------------------------------------

dds <- DESeqDataSetFromMatrix(countData = data,
                              colData = coldata,
                              design= ~ type)
vsd <- vst(dds)
plotPCA(vsd, intgroup = "type")

dds <- DESeq(dds)

res_lfc <- lfcShrink(dds = dds,
                     type = "ashr",
                     coef = "type_Fx600_vs_Fx593")


as_tibble(res_lfc) %>% 
    mutate(padj = case_when( ~ 1,
        TRUE ~ padj
    )) %>% 
    ggplot(aes(x = log2FoldChange, y = -log10(padj))) +
> sessionInfo()
R version 3.6.1 (2019-07-05)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)

Matrix products: default
BLAS:   /opt/sysoft/R-3.6.1/lib64/R/lib/
LAPACK: /opt/sysoft/R-3.6.1/lib64/R/lib/

 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            

attached base packages:
[1] parallel  stats4    stats     graphics  grDevices utils     datasets  methods  
[9] base     

other attached packages:
 [1] ggplot2_3.3.3               dplyr_1.0.5                
 [3] DESeq2_1.26.0               SummarizedExperiment_1.16.0
 [5] DelayedArray_0.12.0         BiocParallel_1.19.6        
 [7] matrixStats_0.58.0          Biobase_2.46.0             
 [9] GenomicRanges_1.38.0        GenomeInfoDb_1.22.0        
[11] IRanges_2.20.0              S4Vectors_0.24.0           
[13] BiocGenerics_0.32.0        

loaded via a namespace (and not attached):
 [1] bitops_1.0-7           bit64_4.0.5            doParallel_1.0.15     
 [4] RColorBrewer_1.1-2     tools_3.6.1            backports_1.2.1       
 [7] utf8_1.2.1             R6_2.5.0               rpart_4.1-15          
[10] Hmisc_4.5-0            DBI_1.1.1              colorspace_2.0-1      
[13] nnet_7.3-16            withr_2.4.2            tidyselect_1.1.0      
[16] gridExtra_2.3          bit_4.0.4              compiler_3.6.1        
[19] cli_2.5.0              htmlTable_2.1.0        labeling_0.4.2        
[22] scales_1.1.1           checkmate_2.0.0        SQUAREM_2017.10-1     
[25] genefilter_1.68.0      mixsqp_0.2-2           stringr_1.4.0         
[28] digest_0.6.27          foreign_0.8-73         XVector_0.26.0        
[31] pscl_1.5.2             base64enc_0.1-3        jpeg_0.1-8.1          
[34] pkgconfig_2.0.3        htmltools_0.5.1.1      fastmap_1.1.0         
[37] htmlwidgets_1.5.3      rlang_0.4.11           rstudioapi_0.13       
[40] RSQLite_2.2.7          generics_0.1.0         farver_2.1.0          
[43] RCurl_1.98-1.3         magrittr_2.0.1         GenomeInfoDbData_1.2.2
[46] Formula_1.2-4          Matrix_1.3-2           Rcpp_1.0.6            
[49] munsell_0.5.0          fansi_0.4.2            lifecycle_1.0.0       
[52] stringi_1.5.3          MASS_7.3-54            zlibbioc_1.32.0       
[55] grid_3.6.1             blob_1.2.1             crayon_1.4.1          
[58] lattice_0.20-44        splines_3.6.1          annotate_1.64.0       
[61] locfit_1.5-9.4         knitr_1.33             pillar_1.6.0          
[64] geneplotter_1.64.0     codetools_0.2-18       XML_3.99-0.3          
[67] glue_1.4.1             packrat_0.5.0          latticeExtra_0.6-29   
[70] data.table_1.12.6      png_0.1-7              vctrs_0.3.8           
[73] foreach_1.4.7          gtable_0.3.0           purrr_0.3.3           
[76] assertthat_0.2.1       ashr_2.2-39            cachem_1.0.4          
[79] xfun_0.22              xtable_1.8-4           survival_3.2-11       
[82] truncnorm_1.0-8        tibble_3.1.1           iterators_1.0.12      
[85] AnnotationDbi_1.48.0   memoise_2.0.0          cluster_2.1.2         
[88] ellipsis_0.3.2

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