Hello,
I am using mothur 1.32.1 to analyze my MiSeq sequencing data, and I just came across an anomaly in running the PCoA command. The R-squared value it is outputting decreases as the number of axes increases. From what I know of statistics I don’t see how this could be possible.
mothur > pcoa(phylip=stability.trim.contigs.good.unique.good.filter.unique.precluster.pick.pick.an.unique_list.0.03.subsample.jclass.0.03.lt.dist)
Processing…
Rsq 1 axis: 0.872513
Rsq 2 axis: 0.862297
Rsq 3 axis: 0.788217
This only happens when I do PCoA analysis using the jclass metric. Using theta YC yields proper values. I don’t see what could be causing this error, my distance file and loadings file both appear correct (see below)
axis loading 1 12.646240 2 6.103441 3 5.101225 4 4.527972 5 3.901018 6 3.834563 7 3.802598 8 3.765227 9 3.761746 10 3.742781 11 3.738690 12 3.721832 13 3.717206 14 3.692692 15 3.675805 16 3.668387 17 3.656325 18 3.637209 19 3.621781 20 3.457425 21 3.294802 22 3.123543 23 2.954787 24 2.852705 25 -0.000000
25 C1 C10 0.895179 C2 0.906309 0.901223 C3 0.895532 0.896568 0.899530 C4 0.897475 0.890709 0.898891 0.892497 C5 0.897674 0.893665 0.903244 0.895513 0.887969 C6 0.904287 0.900797 0.907625 0.900304 0.895502 0.893424 C7 0.893255 0.894303 0.897470 0.893932 0.891812 0.893435 0.901314 C8 0.898518 0.890863 0.905674 0.898937 0.892922 0.890176 0.898662 0.898320 C9 0.899564 0.900178 0.907917 0.899157 0.895840 0.897859 0.901125 0.899037 0.899335 R1 0.894305 0.891548 0.902790 0.894976 0.888939 0.892346 0.897440 0.893944 0.893355 0.894560 R2 0.897671 0.894039 0.908807 0.901602 0.894776 0.894345 0.901369 0.897640 0.897311 0.900117 0.895303 R3 0.898573 0.897206 0.905249 0.901233 0.895109 0.893319 0.898389 0.897357 0.898522 0.899730 0.896291 0.898997 R4 0.897988 0.897122 0.906901 0.897189 0.893977 0.893033 0.899474 0.892813 0.894584 0.899335 0.890726 0.895931 0.897313 R7 0.894646 0.895515 0.902222 0.897460 0.890072 0.893958 0.891880 0.894786 0.893307 0.894400 0.890115 0.894841 0.895866 0.894902 W1 0.978612 0.977810 0.972275 0.977074 0.977883 0.976863 0.979408 0.977329 0.977542 0.978713 0.978246 0.977825 0.977970 0.976358 0.978729 W10 0.982961 0.984395 0.969761 0.980631 0.987295 0.986273 0.988948 0.984304 0.986650 0.986514 0.985835 0.988110 0.988415 0.987420 0.988388 0.955285 W2 0.994429 0.995542 0.990177 0.993174 0.995707 0.996048 0.996154 0.994935 0.995834 0.994161 0.994297 0.996616 0.996229 0.996685 0.995619 0.943872 0.946932 W3 0.997035 0.997101 0.993929 0.995798 0.997040 0.997372 0.997446 0.997304 0.997917 0.996901 0.997230 0.997945 0.998126 0.997278 0.997250 0.981818 0.959459 0.894845 W4 0.997882 0.997929 0.996212 0.996426 0.998415 0.998193 0.998494 0.998412 0.998464 0.997716 0.997771 0.998485 0.998158 0.998397 0.998381 0.983448 0.936170 0.913201 0.797945 W5 0.992387 0.994163 0.983686 0.990670 0.995671 0.994709 0.995892 0.992109 0.996071 0.994020 0.993913 0.996125 0.995960 0.996170 0.996408 0.965354 0.817891 0.912317 0.902834 0.901961 W6 0.974484 0.974267 0.962459 0.971544 0.972026 0.973590 0.974983 0.971972 0.973311 0.971368 0.972012 0.975314 0.973379 0.972488 0.973000 0.859786 0.946365 0.941718 0.976532 0.978365 0.966443 W7 0.990146 0.991153 0.982986 0.988099 0.992038 0.993003 0.992945 0.990679 0.993838 0.991329 0.992292 0.994430 0.994198 0.993567 0.993775 0.949081 0.876847 0.880074 0.884375 0.906736 0.828767 0.950980 W8 0.993498 0.994406 0.989357 0.992173 0.994553 0.995184 0.994572 0.993495 0.995224 0.994264 0.992685 0.995785 0.994575 0.994755 0.995236 0.887534 0.919028 0.878887 0.936430 0.933902 0.882979 0.876053 0.875556 W9 0.991945 0.991401 0.988302 0.991183 0.992433 0.992354 0.991863 0.990985 0.992412 0.992245 0.991514 0.992274 0.992699 0.992115 0.992044 0.931798 0.954494 0.849462 0.969849 0.969732 0.957254 0.924144 0.940547 0.907554
Best,
Amy