drneavin
commented
9 months ago Hi @MrLocuace , this typically means that there aren't any SNPs that are overlapping between the two vcf files. By default, it checks for SNP location and ref and alt alleles to generate unique SNP IDs for each SNP. From the message you posted, it appears that you have location and ref and alt alleles in both files so it's making a SNP ID using all of those parameters. My guess is that the chr encoding for the chromosmes doesn't match between the two files (chr1 in one file and 1 in the other) but it could be a mismatch for the ref and alt alleles as well as something else causing the mismatch. Would you mind sending through a head of each file that includes some of the SNPs?
MrLocuace
Hello @drneavin, I am having a problem running Assign_Indiv_by_Geno.R:
apptainer exec --bind /project/PI/USERS/me/czi/data/scrna/ Demuxafy.sif Assign_Indiv_by_Geno.R -r /project/PI/USERS/me/czi/data/scrna/souporcell/batch1.MAF0.05.vcf.gz -c /project/PI/USERS/me/czi/data/scrna/souporcell/LB-CC-20s-02-LPS-GEX-b1-FC02_souporcell/cluster_genotypes.vcf -o /project/PI/USERS/me/czi/data/scrna/souporcell/LB-CC-20s-02-LPS-GEX-b1-FC02_souporcell
Scanning file to determine attributes. File attributes: meta lines: 33 header_line: 34 variant count: 3804937 column count: 35 Meta line 33 read in. All meta lines processed. gt matrix initialized. Character matrix gt created. Character matrix gt rows: 3804937 Character matrix gt cols: 35 skip: 0 nrows: 3804937 row_num: 0 Processed variant: 3804937 All variants processed Scanning file to determine attributes. File attributes: meta lines: 40 header_line: 41 variant count: 116190 column count: 35 Meta line 40 read in. All meta lines processed. gt matrix initialized. Character matrix gt created. Character matrix gt rows: 116190 Character matrix gt cols: 35 skip: 0 nrows: 116190 row_num: 0 Processed variant: 116190 All variants processed Found GT genotype format in cluster vcf. Will use that metric for cluster correlation. Detected / separator for GT genotype format in cluster vcf Found GT genotype format in reference vcf. Will use that metric for cluster correlation. Detected / separator for GT genotype format in reference vcf Found REF and ALT in both cluster and reference genotype vcfs. Will use chromosome, position, REF and ALT to match SNPs. Joining, by = "ID" Joining, by = "ID" Joining, by = "ID" [1] "AYM-4-071" [1] "0" [1] "1" [1] "2" [1] "3" [1] "4" [1] "5" [1] "6" [1] "7" [1] "8" [1] "9" [1] "10" [1] "11" [1] "12" [1] "13" [1] "14" [1] "15" [1] "16" [1] "17" [1] "18" [1] "19" [1] "20" [1] "21" [1] "22" Error in cor(as.numeric(pull(ref_df, col)), as.numeric(pull(clust_df, : no complete element pairs Calls: pearson_correlation -> cor Execution halted
There should be 26 clusters/individuals/samples. Apparently the program is not matching by sample IDs between reference genotypes and cluster genotypes, since the clusters in cluster_genotypes.vcf are called like:
[1] "0" [1] "1" [1] "2" [1] "3" [1] "4" [1] "5" [1] "6" [1] "7" [1] "8" [1] "9" [1] "10" [1] "11" [1] "12" [1] "13" [1] "14" [1] "15" [1] "16" [1] "17" [1] "18" [1] "19" [1] "20" [1] "21" [1] "22"
What should I do to fix this issue?. Do I need to "manually" replace in the header of cluster_genotypes.vcf file, the "1 2 3 4 5 ..." IDs by the sample IDs from the reference genotype file?. If so, what order of sample IDs do I need to provide?. The same order as in the reference genotype file?
Thank you