How to produce input matrix

[aaannaw]

Hello,Professor
I have produced a .matrix file and a .bed file after running Hic-Pro. Then I runned the R package hicpro2bedpe to convert into the sparse matrices. But when I run the calder.R:

library(CALDER)

contact_mat_file_Ma6 = "1.Chr01.matrix"
CALDER_main(contact_mat_file_Ma6, chr=1, bin_size=40E4, out_dir='./Chr01_Ma', sub_domains=TRUE, save_intermediate_data=FALSE)

The error occurs:

Begin process contact matrix and compute correlation score at: 2022-07-14 22:59:55 
Error in if (nrow(A_oe) < 100) A_oe = remove_blank_cols(mat_oe_sparse,  : 
  argument is of length zero
Calls: CALDER_main -> CALDER_CD_hierarchy -> contact_mat_processing
Execution halted

I am not sure my preparing input is correct? Can you give me any suggestion how to produce the input based on the hicppro results.

[YuanlongLiu]

Can you share your 1.Chr01.matrix to yliueagle@gmail.com?

[aaannaw]

Hello
I am sorry for delayed response. Firstly I have converted the .bed and .matrix file produced by hic-pro to the full-matrix file by running the python script sparseToDense.py. Then I have converted the full-matrix file to sparse upper triangular matrix file by R package HiCcompre full2sparse function. Finally I got upper triangular matrix as the input file ofcalderand I successly run the procedure. But when I run by per chromosome, some chromosomes do not produce the output except log file and the errors occurs:

 >>>> Begin compute compartment domains and their hierachy at: 2022-07-17 01:34:54Error in if (abs(gene_density_cor) < 0.2) warning("correlation between gene density and PC1 is too weak") : 
  missing value where TRUE/FALSE needed
Calls: CALDER_main -> CALDER_CD_hierarchy
In addition: Warning messages:
1: In .Seqinfo.mergexy(x, y) :
  The 2 combined objects have no sequence levels in common. (Use
  suppressWarnings() to suppress this warning.)
2: In .Seqinfo.mergexy(x, y) :
  The 2 combined objects have no sequence levels in common. (Use
  suppressWarnings() to suppress this warning.)
3: In cor(method = "spearman", subset(bin_pc_gene_coverage, (PC1_val <  :
  the standard deviation is zero
Execution halted  

I have carefully read the [README.md (https://github.com/CSOgroup/CALDER2.0#readme), but I have not got the answet of the error. Could you give any suggestions ?

[YuanlongLiu]

Hi,
Can you share one of the input contact matrices which failed for running Calder?

[aaannaw]

Hello
I am sorry for delayed response.
tmp.txt

[YuanlongLiu]

Hi, Can you share one of the input contact matrices which failed for running Calder? Best, Yuanlong

…

On Sun, Jul 17, 2022 at 9:54 AM aaannaw ***@***.***> wrote: Hello I am sorry for delayed response. Firstly I have converted the .bed and .matrix file produced by hic-pro to the full-matrix file by running the python script sparseToDense.py. Then I have converted the full-matrix file to sparse upper triangular matrix file by R package HiCcompre full2sparse function. Finally I got upper triangular matrix as the input file ofcalderand I successly run the procedure. But when I run by per chromosome, some chromosomes do not produce the output except log file and the errors occurs: >>>> Begin compute compartment domains and their hierachy at: 2022-07-17 01:34:54Error in if (abs(gene_density_cor) < 0.2) warning("correlation between gene density and PC1 is too weak") : missing value where TRUE/FALSE needed Calls: CALDER_main -> CALDER_CD_hierarchy In addition: Warning messages: 1: In .Seqinfo.mergexy(x, y) : The 2 combined objects have no sequence levels in common. (Use suppressWarnings() to suppress this warning.) 2: In .Seqinfo.mergexy(x, y) : The 2 combined objects have no sequence levels in common. (Use suppressWarnings() to suppress this warning.) 3: In cor(method = "spearman", subset(bin_pc_gene_coverage, (PC1_val < : the standard deviation is zero Execution halted I have carefully read the [README.md ( https://github.com/CSOgroup/CALDER2.0#readme), but I have not got the answet of the error. Could you give any suggestions ? — Reply to this email directly, view it on GitHub <#7 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AEN35YKZTMWK74T3MIWT3Q3VUO33FANCNFSM53SWVPTA> . You are receiving this because you commented.Message ID: ***@***.***>