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Hi, I am trying to conduct motif analysis for scATAC-seq data. However, I am unable to successfully run FindMotifs function, and the error show below. Could you help fix this issue? Thank you very much
Selecting background regions to match input sequence characteristics
Matching GC.percent distribution
Error in density.default(x = query.feature[[featmatch]], kernel = "gaussian", :
'x' contains missing values
This is the GitHub project for the Python package signac - a package for data management. I think you meant to file this issue in another GitHub repository.
Hi, I am trying to conduct motif analysis for scATAC-seq data. However, I am unable to successfully run FindMotifs function, and the error show below. Could you help fix this issue? Thank you very much
Selecting background regions to match input sequence characteristics
Matching GC.percent distribution
Error in density.default(x = query.feature[[featmatch]], kernel = "gaussian", :
'x' contains missing values
"""
Idents(atac) <- atac$cluster_annotation
da_peaks <- FindAllMarkers(
object = atac,
only.pos = TRUE,
test.use = 'LR',
min.pct = 0.05,
latent.vars = 'nCount_peaks'
)
top.da.peak <- rownames(da_peaks[da_peaks$p_val < 0.005 & da_peaks$pct.1 > 0.2, ])
da_peaks <- FindAllMarkers(
object = atac,
only.pos = TRUE,
test.use = 'LR',
min.pct = 0.05,
latent.vars = 'nCount_peaks'
)
top.da.peak <- rownames(da_peaks[da_peaks$p_val < 0.005 & da_peaks$pct.1 > 0.2, ])
enriched.motifs <- FindMotifs(
object = atac,
features = top.da.peak
)
pdf("test_motif.pdf")
MotifPlot(
object = atac,
motifs = head(rownames(enriched.motifs))
)
dev.off()
"""
Below is R session
Matrix products: default
BLAS/LAPACK: /home/cfceConda/miniconda3/envs/seurat5/lib/libopenblasp-r0.3.24.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats4 stats graphics grDevices utils datasets methods
[8] base
other attached packages:
[1] BSgenome.Hsapiens.UCSC.hg38_1.4.4 BSgenome_1.62.0
[3] rtracklayer_1.54.0 Biostrings_2.62.0
[5] XVector_0.34.0 TFBSTools_1.32.0
[7] JASPAR2020_0.99.10 lubridate_1.9.2
[9] forcats_1.0.0 stringr_1.5.0
[11] dplyr_1.1.2 purrr_1.0.1
[13] readr_2.1.4 tidyr_1.3.0
[15] tibble_3.2.1 ggplot2_3.4.2
[17] tidyverse_2.0.0 future_1.32.0
[19] patchwork_1.1.2 EnsDb.Hsapiens.v86_2.99.0
[21] ensembldb_2.18.1 AnnotationFilter_1.18.0
[23] GenomicFeatures_1.46.1 AnnotationDbi_1.56.2
[25] Biobase_2.54.0 GenomicRanges_1.46.1
[27] GenomeInfoDb_1.39.9 IRanges_2.28.0
[29] S4Vectors_0.32.4 BiocGenerics_0.40.0
[31] SeuratWrappers_0.3.2 Seurat_5.0.0
[33] SeuratObject_5.0.0 sp_1.6-1
[35] Signac_1.13.0
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