PCA WITH PLINK
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11 months ago

Hello, good morning, I'm having trouble making a pca with plink, I hope someone can help me, I'm attaching the command and the pca.log

plink --bfile result --allow-extra-chr --pca --out pca
Random number seed: 1692078227
7751 MB RAM detected; reserving 3875 MB for main workspace.
11313 variants loaded from .bim file.
285 people (0 males, 0 females, 285 ambiguous) loaded from .fam.
Ambiguous sex IDs written to pca.nosex .
Using up to 4 threads (change this with --threads).
Before main variant filters, 285 founders and 0 nonfounders present.
Calculating allele frequencies... done.
Total genotyping rate is 0.909743.
11313 variants and 285 people pass filters and QC.
Note: No phenotypes present.
Relationship matrix calculation complete.

Error: Failed to extract eigenvector(s) from GRM.

End time: Mon Aug 14 22:43:48 2023
PLINK • 2.0k views
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Did you quality control (--maf/--geno/--mid/--hwe etc.) your genotype data? What are your input variants: are these all or just independent SNP?

Please see what Christopher Chang recommends here-

https://groups.google.com/g/plink2-users/c/VZw3kUoanHU?pli=1

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These data are snp results for linkage disequilibrium. I used the --maf parameter for the snp call by stacks

Thanks I'll check it out.

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Please check my QC / pre-filtering commands, here: Produce PCA bi-plot for 1000 Genomes Phase III - Version 2

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Hi sir, i have complete --assoc step and view the manhattan plot but i don't know next step sir. what do next step sir ? Kevin Blighe

enter image description here

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Which output files have been produced?

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my final output assoc_result.assoc. this is my output file Kevin Blighe

 CHR                                                                                                 SNP            BP  A1       F_A        F_U  A2    CHISQ           P           OR
1                                                                                                  .    113969   C  0.15    0.2222    T 0.3288  0.5664  0.6176
1                                                                                                  .    118617   T  0.15    0.1667    C 0.01979 0.8881  0.8824
1                                                                                         rs76459066    120458   T  0.05    0.05556   C 0.005864    0.939   0.8947
1                                                                               rs1851943;rs78872916    121009   C  0.15    0.1667    T 0.01979 0.8881  0.8824
1                                                                                         rs77329837    123511   G  0.4 0.3333    A 0.181   0.6706  1.333
1                                                                                          rs3871806    125202   A  0.15    0.2222    G 0.3288  0.5664  0.6176
1                                                                                          rs3871807    125271   C  0.05    0.1667    T 1.369   0.242   0.2632
1                                                                                                  .    127712   A  0.25    0.4444    G 1.591   0.2071  0.4167
1                                                                                          rs6422503    235976   C  0.35    0.5556    A 1.619   0.2032  0.4308
1                                                                                         rs11490246    241369   C  0.2 0.1667    T 0.07005 0.7913  1.25
1                                                                                                  .    604415   G  0.5 0.3889    A 0.4731  0.4916  1.571
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Great, you now need to filter on the P (p-value) column, to identify statistically significant variants.

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The other columns are defined here: https://zzz.bwh.harvard.edu/plink/anal.shtml

 CHR     Chromosome
 SNP     SNP ID
 BP      Physical position (base-pair)
 A1      Minor allele name (based on whole sample)
 F_A     Frequency of this allele in cases
 F_U     Frequency of this allele in controls
 A2      Major allele name
 CHISQ   Basic allelic test chi-square (1df)
 P       Asymptotic p-value for this test
 OR      Estimated odds ratio (for A1, i.e. A2 is reference)
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thank you sir, but I don't any idea for this identify statistically significant variants sir. give me some example sir. any tutorial or reference articles sir. Kevin Blighe

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Great, you now need to filter on the P (p-value) column, to identify statistically significant variants.

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hi sir, i have identify the statistically significant variants .

this is output file sir . next step sir. Kevin Blighe

 CHR                                                                                                 SNP            BP  A1       F_A        F_U  A2    CHISQ           P           OR
5                                                                                           rs261044    169333555    T  0   0.4444    C    11.26    0   0.0007923   0
5                                                                                           rs261002    169335386    C  0   0.4444    T    11.26    0   0.0007923   0
6                                                                                           rs454478    7940858  G  0   0.3889    A 9.534   0.002017    0
8                                                                                         rs11993800    27885843     A  0   0.3889    G 9.534   0.002017    0
9                                                                                          rs1407811    793708   A  0.05    0.5   G 9.894   0.001659    0.05263
9                                                                                          rs9407403    8203344  C  0.45    0     G 10.61   0.001122           NA
9                                                                                          rs9409462    94546619     T  0   0.3889    C 9.534   0.002017    0
10                                                                                        rs34727339    107535543    C  0   0.3889    T 9.534   0.002017    0
12                                                                                        rs77535086    47467735     T  0   0.3889    A 9.534   0.002017    0
13                                                                                         rs7491012    89336675     G  0.45    0     A 10.61   0.001122           NA
15                                                                                        rs10852220    28381469     A  0   0.4444    G    11.26    0   0.0007923   0
19                                                                                         rs2734462    44927757     G  0   0.3889    A 9.534   0.002017    0
22                                                                                         rs3984091    18836601     A  0.1 0.6111    G       11    0   0.0009131   0.07071
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