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I can't get prepare_ceres_inputs
to work consistently with my proxy settings and, on the rare occasion I do, I can't get it to work with my bowtie and samtools:
> prepare_ceres_inputs(inputs_dir="ceres_inputs",
+ dep_file="ceres_inputs/ceres_LFC_input.gct",
+ cn_seg_file="ceres_inputs/ceres_CN_input.tsv",
+ gene_annot_file="example_data/CCDS.current.txt",
+ rep_map_file="ceres_inputs/ceres_rep_input.tsv",
+ genome_id="hg19",
+ chromosomes=paste0("chr", 1:22),
+ dep_normalize="zmad")
loading dependency data...
Parsed with column specification:
cols(
Replicate = col_character(),
CellLine = col_character()
)
loading copy number data...
mapping sgRNAs to the genome...
sh: bowtie: command not found
sh: samtools: command not found
Error in value[[3L]](cond) :
failed to open BamFile: file(s) do not exist:
'/tmp/RtmpfQL4OU/guides.bam'
In addition: Warning messages:
1: In system(bowtie_cmd) : error in running command
2: In system(samtools_cmd) : error in running command
As a result, I've tried to put together the correct data and supply it directly to run_ceres
. It fails with error:
> run_ceres(sg_data=sg_data, cn_data=cn_data,
+ guide_locus=guide_locus, locus_gene=locus_gene, replicate_map=repmap)
Error in dimnames(x) <- dn :
length of 'dimnames' [2] not equal to array extent
In addition: There were 50 or more warnings (use warnings() to see the first 50)
and the warnings are:
Warning messages:
1: In mean.default(x, na.rm = T) :
argument is not numeric or logical: returning NA
Obviously I'm using real data, but I thought dummy data would help you to spot what I'm doing wrong:
# log fold change calc from plasmid of each gRNA in each sample
dum_sg_lfc <- as.matrix(sapply(1:6, function(x) rnorm(4)))
rownames(dum_sg_lfc) <- c("ATCGA", "ATCGT", "ATCGC", "ATCGG")
colnames(dum_sg_lfc) <- c("A1", "A2", "B1", "B2", "C1", "C2")
# log2ratio copy number at each gRNA cut site in each cell line given as chr:pos
dum_cn_lr <- as.matrix(sapply(1:3, function(x) rnorm(4)))
rownames(dum_cn_lr) <- c("1:100", "1:200", "1:300", "1:400")
colnames(dum_cn_lr) <- c("A", "B", "C")
# dummy data using chr:pos as locus, entrez gene id as gene and sample to cell line names
dum_gl <- data.frame(Guide=rownames(dum_sg_lfc), Locus=rownames(dum_cn_lr))
dum_lg <- data.frame(Locus=rownames(dum_cn_lr), Gene=paste0("eg", 1:nrow(dum_cn_lr)))
dum_rep <- data.frame(Replicate=colnames(dum_sg_lfc), CellLine=gsub("[[:digit:]]*", "", colnames(dum_sg_lfc)))
run_ceres(sg_data=dum_sg_lfc, cn_data=dum_cn_lr,
guide_locus=dum_gl, locus_gene=dum_lg, replicate_map=dum_rep)
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