Hi!

I'm interested in using DESeq2 to find features that have low log2FC. For that, I wish to use altHypothesis = "lessAbs" on apeglm-shrunken effect sizes. However, I noticed that lfcShrink removed the lfcThreshold and altHypothesis that I had specified in the results function, providing small s-values for features with high absolute log2FoldChange (code below).

Is there any way of using altHypothesis = "lessAbs" on apeglm-shrunken effect sizes, or this option only supports unshrunken log2FoldChanges?

Thanks!

res <- results(dds, lfcThreshold = .1, altHypothesis = "lessAbs", parallel = TRUE)
res <- lfcShrink(dds, res = res, type = "apeglm", coef = "condition_B_vs_A", svalue = TRUE, parallel = TRUE)

###

R version 4.0.2 (2020-06-22)
Platform: x86_64-conda_cos6-linux-gnu (64-bit)
Running under: SUSE Linux Enterprise Server 15

Matrix products: default
BLAS/LAPACK: /global/cscratch1/sd/acamargo/.environments/deseq2/lib/libopenblasp-r0.3.10.so

locale:
 [1] LC_CTYPE=C.UTF-8       LC_NUMERIC=C           LC_TIME=C.UTF-8       
 [4] LC_COLLATE=C.UTF-8     LC_MONETARY=C.UTF-8    LC_MESSAGES=C.UTF-8   
 [7] LC_PAPER=C.UTF-8       LC_NAME=C              LC_ADDRESS=C          
[10] LC_TELEPHONE=C         LC_MEASUREMENT=C.UTF-8 LC_IDENTIFICATION=C   

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

other attached packages:
 [1] hypeR_1.5.4                 tximport_1.18.0            
 [3] DESeq2_1.30.0               SummarizedExperiment_1.20.0
 [5] Biobase_2.50.0              MatrixGenerics_1.2.0       
 [7] matrixStats_0.57.0          GenomicRanges_1.42.0       
 [9] GenomeInfoDb_1.26.0         IRanges_2.24.0             
[11] S4Vectors_0.28.0            BiocGenerics_0.36.0        
[13] viridis_0.5.1               viridisLite_0.3.0          
[15] pheatmap_1.0.12             data.table_1.13.4          
[17] forcats_0.5.0               stringr_1.4.0              
[19] dplyr_1.0.2                 purrr_0.3.4                
[21] readr_1.4.0                 tidyr_1.1.2                
[23] tibble_3.0.4                ggplot2_3.3.2              
[25] tidyverse_1.3.0

See ?lfcShrink, it does have lfcThreshold.