Open nbutyrate opened 2 years ago
Hi I tried the following
result2<-CDSeq(bulk_data = M2, cell_type_number = 2:10, mcmc_iterations = 5, dilution_factor = 1, block_number = 1, gene_length = as.vector(gene_length), reference_gep = refGEP, # gene expression profile of pure cell lines cpu_number = 1, # use multiple cores to save time. Set the cpu_number = length(cell_type_number) if there is enough cores. print_progress_msg_to_file = 0)
and got the following error
CDSeq is running in non Reduce-Recover mode. To use Reduce-Recover mode, assign a value to block_number that is greater than 1.
Error in CDSeq(bulk_data = M2, cell_type_number = 2:10, mcmc_iterations = 5, : length(gene_length) should be equal to nrow(bulk_data)
my data looks like
head(M2) [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] [,15] [,16] [,17] [,18] [,19] [,20] [1,] 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 [2,] 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 [3,] 94 101 92 126 213 263 515 99 173 107 180 301 109 185 130 52 203 84 118 170 [4,] 8 7 8 10 24 16 20 11 12 7 8 15 9 11 10 13 13 14 6 23 [5,] 25 34 26 27 64 66 114 32 73 46 42 52 38 70 68 43 73 47 40 59 [6,] 2 6 6 7 0 5 6 3 4 4 3 12 2 8 5 4 5 6 3 5 [,21] [,22] [,23] [,24] [,25] [,26] [,27] [,28] [,29] [,30] [,31] [,32] [,33] [,34] [,35] [,36] [,37] [,38] [1,] 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 [2,] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [3,] 188 132 481 173 103 116 163 183 198 149 131 89 225 150 226 160 586 657
Sorry for late response. Is your M2 of dimension gene by sample? Also, mcmc_iterations = 5 won't converge, try 1000 or something.
Hi I tried the following
and got the following error
CDSeq is running in non Reduce-Recover mode. To use Reduce-Recover mode, assign a value to block_number that is greater than 1.
Error in CDSeq(bulk_data = M2, cell_type_number = 2:10, mcmc_iterations = 5, : length(gene_length) should be equal to nrow(bulk_data)
my data looks like
head(M2) [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] [,15] [,16] [,17] [,18] [,19] [,20] [1,] 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 [2,] 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 [3,] 94 101 92 126 213 263 515 99 173 107 180 301 109 185 130 52 203 84 118 170 [4,] 8 7 8 10 24 16 20 11 12 7 8 15 9 11 10 13 13 14 6 23 [5,] 25 34 26 27 64 66 114 32 73 46 42 52 38 70 68 43 73 47 40 59 [6,] 2 6 6 7 0 5 6 3 4 4 3 12 2 8 5 4 5 6 3 5 [,21] [,22] [,23] [,24] [,25] [,26] [,27] [,28] [,29] [,30] [,31] [,32] [,33] [,34] [,35] [,36] [,37] [,38] [1,] 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 [2,] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [3,] 188 132 481 173 103 116 163 183 198 149 131 89 225 150 226 160 586 657