Discrepancy in DE results from base DESeq2 and tidybulk DESeq2 method

[MSaadfarooq]

Hi, I used following code for DESeq2 workflow but found some differences in results

gse
# A SummarizedExperiment-tibble abstraction: 3,532,606 × 30
# Features=36047 | Samples=98

dds <- DESeqDataSet(gse, design = ~ batch + sex + status) 
dds <- DESeq(dds)
res <- results(dds)
summary(res)
out of 35983 with nonzero total read count
adjusted p-value < 0.1
LFC > 0 (up)       : 188, 0.52%
LFC < 0 (down)     : 62, 0.17%
outliers [1]       : 99, 0.28%
low counts [2]     : 15312, 43%
(mean count < 7)

I also performed same SE object with same variables using tidybulk

da <- gse |> test_differential_abundance(~batch + sex + status, method = "DESeq2")
da_res <- da %>% pivot_transcript()

# to compare results
all.equal(rownames(res), da_res$.feature)
[1] TRUE
sum(da_res$padj < 0.1, na.rm=TRUE)
[1] 321
table(base_sig = res$padj < .1, tidy_sig = da_res$padj < .1)
        tidy_sig
base_sig FALSE  TRUE
   FALSE 20119   255
   TRUE    224    26

Please guide where it went wrong?