MixSIAR
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brianstock
Global vs
Hi Brian, I'm trying to use MixSIAR with soil microbiome data. Dataset I'm using is quite simple. I have 13C and 15N isotope values of microbial biomass (mixture) collected from a treatment with 5 replicates. The source 13C and 15N values are from organic matters (4 types) I'm adding in soil for microbial decomposition. I ran MixSIAR with mixture, source and discrimination files, and added sample_id in "sample" column. In summary_statistics, the global estimates of proportion of each source (mean and 50%) is quite different than the individual samples. Model DIC is 3.72, Geweke Chain 1 Chain 2 Chain 3 3 8 3. In my case, do you think my model run was alright? If ok which values global vs individual, should I rely for the proportion of sources used by microbes? #########
[41] " Mean SD 2.5% 5% 25% 50% 75% 95% 97.5%"
[42] "Epsilon.1 12.581 5.018 2.449 3.427 8.688 13.434 16.835 19.344 19.671"
[43] "Epsilon.2 14.821 4.158 4.876 6.410 12.357 15.716 18.213 19.703 19.862"
[44] "Sample.SD 7.853 5.180 1.086 1.517 3.672 6.404 11.477 18.069 19.061"
[45] "p.global.Source1 0.239 0.174 0.013 0.024 0.101 0.202 0.345 0.581 0.643"
[46] "p.global.Source2 0.341 0.216 0.024 0.043 0.170 0.309 0.491 0.734 0.796"
[47] "p.global.Source3 0.261 0.189 0.008 0.018 0.107 0.227 0.381 0.623 0.701"
[48] "p.global.Source4 0.158 0.163 0.001 0.003 0.031 0.101 0.238 0.492 0.600"
[49] "p.Sample 67.Source1 0.177 0.170 0.000 0.000 0.004 0.145 0.260 0.508 0.535"
[50] "p.Sample 79.Source1 0.042 0.088 0.000 0.000 0.000 0.005 0.060 0.150 0.270"
[51] "p.Sample 116.Source1 0.022 0.098 0.000 0.000 0.000 0.000 0.003 0.059 0.384"
[52] "p.Sample 123.Source1 0.194 0.195 0.000 0.000 0.000 0.146 0.388 0.492 0.528"
[53] "p.Sample 67.Source2 0.117 0.188 0.000 0.000 0.000 0.004 0.173 0.492 0.542"
[54] "p.Sample 79.Source2 0.884 0.176 0.112 0.652 0.854 0.925 0.993 1.000 1.000"
[55] "p.Sample 116.Source2 0.957 0.155 0.311 0.856 0.984 0.998 1.000 1.000 1.000"
[56] "p.Sample 123.Source2 0.191 0.235 0.000 0.000 0.000 0.013 0.459 0.576 0.597"
[57] "p.Sample 67.Source3 0.672 0.344 0.000 0.000 0.509 0.802 0.951 1.000 1.000"
[58] "p.Sample 79.Source3 0.069 0.140 0.000 0.000 0.000 0.004 0.085 0.281 0.400"
[59] "p.Sample 116.Source3 0.019 0.082 0.000 0.000 0.000 0.000 0.005 0.078 0.187"
[60] "p.Sample 123.Source3 0.611 0.415 0.000 0.000 0.096 0.813 0.998 1.000 1.000"
[61] "p.Sample 67.Source4 0.034 0.025 0.000 0.000 0.011 0.038 0.050 0.072 0.083"
[62] "p.Sample 79.Source4 0.005 0.013 0.000 0.000 0.000 0.000 0.003 0.031 0.048"
[63] "p.Sample 116.Source4 0.002 0.008 0.000 0.000 0.000 0.000 0.001 0.012 0.022"
[64] "p.Sample 123.Source4 0.004 0.010 0.000 0.000 0.000 0.000 0.002 0.022 0.033"
The "global" proportions are like the population mean, so my guess is that the individuals are just highly variable. Looking at the isospace plot would show this.
On Mon, Jun 5, 2023, 4:34 AM SMFRabbi @.***> wrote:
Hi Brian, I'm trying to use MixSIAR with soil microbiome data. Dataset I'm using is quite simple. I have 13C and 15N isotope values of microbial biomass (mixture) collected from a treatment with 5 replicates. The source 13C and 15N values are from organic matters (4 types) I'm adding in soil for microbial decomposition. I ran MixSIAR with mixture, source and discrimination files, and added sample_id in "sample" column. In summary_statistics, the global estimates of proportion of each source (mean and 50%) is quite different than the individual samples. Model DIC is 3.72, Geweke Chain 1 Chain 2 Chain 3 3 8 3. In my case, do you think my model run was alright? If ok which values global vs individual, should I rely for the proportion of sources used by microbes? #########
[41] " Mean SD 2.5% 5% 25% 50% 75% 95% 97.5%" [42] "Epsilon.1 12.581 5.018 2.449 3.427 8.688 13.434 16.835 19.344 19.671" [43] "Epsilon.2 14.821 4.158 4.876 6.410 12.357 15.716 18.213 19.703 19.862" [44] "Sample.SD 7.853 5.180 1.086 1.517 3.672 6.404 11.477 18.069 19.061" [45] "p.global.Source1 0.239 0.174 0.013 0.024 0.101 0.202 0.345 0.581 0.643" [46] "p.global.Source2 0.341 0.216 0.024 0.043 0.170 0.309 0.491 0.734 0.796" [47] "p.global.Source3 0.261 0.189 0.008 0.018 0.107 0.227 0.381 0.623 0.701" [48] "p.global.Source4 0.158 0.163 0.001 0.003 0.031 0.101 0.238 0.492 0.600" [49] "p.Sample 67.Source1 0.177 0.170 0.000 0.000 0.004 0.145 0.260 0.508 0.535" [50] "p.Sample 79.Source1 0.042 0.088 0.000 0.000 0.000 0.005 0.060 0.150 0.270" [51] "p.Sample 116.Source1 0.022 0.098 0.000 0.000 0.000 0.000 0.003 0.059 0.384" [52] "p.Sample 123.Source1 0.194 0.195 0.000 0.000 0.000 0.146 0.388 0.492 0.528" [53] "p.Sample 67.Source2 0.117 0.188 0.000 0.000 0.000 0.004 0.173 0.492 0.542" [54] "p.Sample 79.Source2 0.884 0.176 0.112 0.652 0.854 0.925 0.993 1.000 1.000" [55] "p.Sample 116.Source2 0.957 0.155 0.311 0.856 0.984 0.998 1.000 1.000 1.000" [56] "p.Sample 123.Source2 0.191 0.235 0.000 0.000 0.000 0.013 0.459 0.576 0.597" [57] "p.Sample 67.Source3 0.672 0.344 0.000 0.000 0.509 0.802 0.951 1.000 1.000" [58] "p.Sample 79.Source3 0.069 0.140 0.000 0.000 0.000 0.004 0.085 0.281 0.400" [59] "p.Sample 116.Source3 0.019 0.082 0.000 0.000 0.000 0.000 0.005 0.078 0.187" [60] "p.Sample 123.Source3 0.611 0.415 0.000 0.000 0.096 0.813 0.998 1.000 1.000" [61] "p.Sample 67.Source4 0.034 0.025 0.000 0.000 0.011 0.038 0.050 0.072 0.083" [62] "p.Sample 79.Source4 0.005 0.013 0.000 0.000 0.000 0.000 0.003 0.031 0.048" [63] "p.Sample 116.Source4 0.002 0.008 0.000 0.000 0.000 0.000 0.001 0.012 0.022" [64] "p.Sample 123.Source4 0.004 0.010 0.000 0.000 0.000 0.000 0.002 0.022 0.033"
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Thanks Brian. I'll better stick with the population mean and this explains the treatment effect more convincingly.