Bas

11-19-2017, 02:34 AM

What are the important things to look for in the output of qpAdm? I get this output:

Left:

Iberia_EN

Anatolia_N

Iberia_HG

Hungary_HG

jackknife block size: 0.050

snps: 1151063 indivs: 143

number of blocks for block jackknife: 713

dof (jackknife): 619.341

numsnps used: 379951

codimension 1

f4info:

f4rank: 2 dof: 2 chisq: 0.397 tail: 0.820146509 dofdiff: 4 chisqdiff: -0.397 taildiff: 1

B:

scale 1.000 1.000

Eskimo -0.638 1.425

Mbuti 1.717 0.879

Karitiana -0.796 0.606

Ulchi -0.104 0.911

A:

scale 1109.175 7801.996

Anatolia_N 0.224 0.445

Iberia_HG -1.242 -1.091

Hungary_HG -1.187 1.270

full rank 1

f4info:

f4rank: 3 dof: 0 chisq: 0.000 tail: 1 dofdiff: 2 chisqdiff: 0.397 taildiff: 0.820146509

B:

scale 1.000 1.000 1.000

Eskimo -0.618 1.450 -1.186

Mbuti 1.717 0.875 0.024

Karitiana -0.809 0.609 0.729

Ulchi -0.129 0.873 1.436

A:

scale 1103.742 7689.244 74708.748

Anatolia_N 0.216 0.426 1.665

Iberia_HG -1.245 -1.118 0.447

Hungary_HG -1.184 1.253 -0.167

best coefficients: 0.851 0.241 -0.091

ssres:

-0.000023884 -0.000014637 0.000019307 0.000028112

-1.082349727 -0.663311893 0.874963854 1.273960225

Jackknife mean: 0.850314358 0.176871913 -0.027186271

std. errors: 0.057 0.244 0.242

error covariance (* 1000000)

3194 -1864 -1330

-1864 59296 -57432

-1330 -57432 58762

fixed pat wt dof chisq tail prob

000 0 2 0.397 0 0.851 0.241 -0.091 infeasible

001 1 3 0.583 0.900212 0.848 0.152 0.000

010 1 3 1.710 0.634764 0.859 0.000 0.141

100 1 3 4.460 0 0.000 39.072 -38.072 infeasible

011 2 4 8.854 0.0648513 1.000 -0.000 0.000

101 2 4 52.924 8.84048e-11 0.000 1.000 0.000

110 2 4 55.005 3.2416e-11 0.000 -0.000 1.000

best pat: 000 0 - -

best pat: 001 0.900212 chi(nested): 0.187 p-value for nested model: 0.665509

best pat: 011 0.0648513 chi(nested): 8.271 p-value for nested model: 0.00402907

## end of run

I hear people talk about chisq (as low as poss?) and tail prob (close to 1%?). It gives chi and p-value at the end and a few other places but where do I identify the most important one, the one that will tell me if the model works on these outputs?

Left:

Iberia_EN

Anatolia_N

Iberia_HG

Hungary_HG

jackknife block size: 0.050

snps: 1151063 indivs: 143

number of blocks for block jackknife: 713

dof (jackknife): 619.341

numsnps used: 379951

codimension 1

f4info:

f4rank: 2 dof: 2 chisq: 0.397 tail: 0.820146509 dofdiff: 4 chisqdiff: -0.397 taildiff: 1

B:

scale 1.000 1.000

Eskimo -0.638 1.425

Mbuti 1.717 0.879

Karitiana -0.796 0.606

Ulchi -0.104 0.911

A:

scale 1109.175 7801.996

Anatolia_N 0.224 0.445

Iberia_HG -1.242 -1.091

Hungary_HG -1.187 1.270

full rank 1

f4info:

f4rank: 3 dof: 0 chisq: 0.000 tail: 1 dofdiff: 2 chisqdiff: 0.397 taildiff: 0.820146509

B:

scale 1.000 1.000 1.000

Eskimo -0.618 1.450 -1.186

Mbuti 1.717 0.875 0.024

Karitiana -0.809 0.609 0.729

Ulchi -0.129 0.873 1.436

A:

scale 1103.742 7689.244 74708.748

Anatolia_N 0.216 0.426 1.665

Iberia_HG -1.245 -1.118 0.447

Hungary_HG -1.184 1.253 -0.167

best coefficients: 0.851 0.241 -0.091

ssres:

-0.000023884 -0.000014637 0.000019307 0.000028112

-1.082349727 -0.663311893 0.874963854 1.273960225

Jackknife mean: 0.850314358 0.176871913 -0.027186271

std. errors: 0.057 0.244 0.242

error covariance (* 1000000)

3194 -1864 -1330

-1864 59296 -57432

-1330 -57432 58762

fixed pat wt dof chisq tail prob

000 0 2 0.397 0 0.851 0.241 -0.091 infeasible

001 1 3 0.583 0.900212 0.848 0.152 0.000

010 1 3 1.710 0.634764 0.859 0.000 0.141

100 1 3 4.460 0 0.000 39.072 -38.072 infeasible

011 2 4 8.854 0.0648513 1.000 -0.000 0.000

101 2 4 52.924 8.84048e-11 0.000 1.000 0.000

110 2 4 55.005 3.2416e-11 0.000 -0.000 1.000

best pat: 000 0 - -

best pat: 001 0.900212 chi(nested): 0.187 p-value for nested model: 0.665509

best pat: 011 0.0648513 chi(nested): 8.271 p-value for nested model: 0.00402907

## end of run

I hear people talk about chisq (as low as poss?) and tail prob (close to 1%?). It gives chi and p-value at the end and a few other places but where do I identify the most important one, the one that will tell me if the model works on these outputs?