I ran copykat on a large scRNA-seq dataset and the pipeline completed successfully, but the resulting heatmap looks abnormal.
code:
cnv <- copykat(rawmat = count_expr,
ngene.chr = 3,
sam.name = args$group_name,
n.cores = 36,
LOW.DR = 0.01,
KS.cut = 0.01,
plot.genes = FALSE,
genome = '10',
distance = "euclidean")
log：
[1] "running copykat v1.1.0"
[1] "step1: read and filter data ..."
[1] "19623 genes, 38077 cells in raw data"
[1] "filtered out 7 cells with less than min.gene.per.cell; remaining 38070 cells"
Initializing Parquet file with schema.
[1] "13256 genes past LOW.DR filtering"
[1] "step 2: annotations gene coordinates ..."
[1] "start annotation ..."
[1] "step 3: smoothing data with dlm ..."
[1] "step 4: measuring baselines ..."
number of iterations= 202
number of iterations= 453
number of iterations= 365
number of iterations= 283
number of iterations= 795
number of iterations= 156
[1] "low confidence in classification"
[1] "cell: 1"
number of iterations= 298
[1] "cell: 2"
WARNING! NOT CONVERGENT!
number of iterations= 500
[1] "cell: 3"
number of iterations= 320
[1] "cell: 4"
number of iterations= 346
...
...
...
number of iterations= 294
[1] "cell: 607"
number of iterations= 497
[1] "step 5: segmentation..."
[1] "step 8: final prediction ..."
[1] "step 9: saving results..."
[1] "step 10: ploting heatmap ..."
e.g:
I ran copykat on a large scRNA-seq dataset and the pipeline completed successfully, but the resulting heatmap looks abnormal.
code:
cnv <- copykat(rawmat = count_expr,
ngene.chr = 3,
sam.name = args$group_name,
n.cores = 36,
LOW.DR = 0.01,
KS.cut = 0.01,
plot.genes = FALSE,
genome = '10',
distance = "euclidean")
log：
[1] "running copykat v1.1.0"
[1] "step1: read and filter data ..."
[1] "19623 genes, 38077 cells in raw data"
[1] "filtered out 7 cells with less than min.gene.per.cell; remaining 38070 cells"
Initializing Parquet file with schema.
[1] "13256 genes past LOW.DR filtering"
[1] "step 2: annotations gene coordinates ..."
[1] "start annotation ..."
[1] "step 3: smoothing data with dlm ..."
[1] "step 4: measuring baselines ..."
number of iterations= 202
number of iterations= 453
number of iterations= 365
number of iterations= 283
number of iterations= 795
number of iterations= 156
[1] "low confidence in classification"
[1] "cell: 1"
number of iterations= 298
[1] "cell: 2"
WARNING! NOT CONVERGENT!
number of iterations= 500
[1] "cell: 3"
number of iterations= 320
[1] "cell: 4"
number of iterations= 346
...
...
...
number of iterations= 294
[1] "cell: 607"
number of iterations= 497
[1] "step 5: segmentation..."
[1] "step 8: final prediction ..."
[1] "step 9: saving results..."
[1] "step 10: ploting heatmap ..."
e.g: