Steven Roberts 19 July, 2023
We have a couple of merged VCFs (epidiverse, bs-snper)
echo "epidiverse"
tail -2 ../output/51-SNPs/EpiDiv_merged.f.recode.vcf
echo "BS"
tail -2 ../data/Cv_10x_fxmerge_05.recode.vcf## epidiverse
## NC_007175.2 6500 . T A 0.198458 . DPB=199;EPPR=10.6176;GTI=0;MQMR=38.3377;NS=1;NUMALT=1;ODDS=22.6887;PAIREDR=1;PQR=0;PRO=0;QR=4953;RO=151;RPPR=79.6446;SRF=63;SRP=11.9982;SRR=88;DP=8738;AB=0;ABP=0;AF=0;AO=61;CIGAR=1X;DPRA=0;EPP=75.0961;LEN=1;MEANALT=3;MQM=27.6557;PAIRED=1;PAO=0;PQA=0;QA=1307;RPL=41;RPP=18.709;RPR=20;RUN=1;SAF=37;SAP=9.02635;SAR=24;TYPE=snp;AN=42;AC=4 GT:GQ:DP:AD:RO:QR:AO:QA:GL ./.:.:.:.:.:.:.:.:. ./.:.:.:.:.:.:.:.:. 0/1:0:199:151,40:151:4953:40:908:-16.9953,0,-351.675 0/0:99:985:842,128:842:28502:128:3004:0,-47.9328,-2006.41 0/0:99:512:418,74:418:13832:74:1502:0,-23.3187,-984.518 ./.:.:.:.:.:.:.:.:. 0/0:99:232:193,30:193:6401:30:711:0,-9.69112,-454.514 0/1:0:17:13,4:13:469:4:89:-2.12488,0,-34.6904 0/0:99:874:748,93:748:24700:93:2174:0,-77.1869,-1751.28 0/0:99:712:614,80:614:20430:80:1646:0,-67.1339,-1509.98 0/0:99:816:730,66:730:24806:66:1439:0,-125.684,-1822.58 0/0:99:538:443,82:443:15043:82:1781:0,-9.93394,-1016.46 0/0:99:188:160,24:160:5330:24:389:0,-22.6474,-382.217 0/0:99:563:501,50:501:16369:50:1168:0,-73.0384,-1190.91 0/1:0:45:38,7:38:1318:7:161:-0.919608,0,-93.4117 0/0:99:398:333,57:333:10803:57:1068:0,-35.271,-785.276 0/0:99:218:184,23:184:6088:23:513:0,-24.0412,-440.405 0/0:99:728:660,54:660:22018:54:1111:0,-121.784,-1699.24 0/0:99:355:302,43:302:10302:43:826:0,-31.9642,-720.162 0/1:0:8:5,3:5:161:3:48:-2.00574,0,-11.6892 0/0:99:59:49,8:49:1699:8:175:0,-3.87806,-129.594 0/0:72:35:27,6:27:961:6:123:0,-0.202619,-66.9905 0/0:99:641:543,86:543:18095:86:1899:0,-28.1316,-1274.13 0/0:99:615:539,61:539:17857:61:1307:0,-78.2955,-1339.84 ./.:.:.:.:.:.:.:.:. ./.:.:.:.:.:.:.:.:.
## NC_007175.2 10968 . T G 0.000292088 . DPB=30;EPPR=4.45795;GTI=0;MQMR=39.5833;NS=1;NUMALT=1;ODDS=25.755;PAIREDR=1;PQR=0;PRO=0;QR=826;RO=24;RPPR=12.0581;SRF=11;SRP=3.37221;SRR=13;DP=10330;AB=0.25;ABP=9.52472;AF=0.5;AO=3;CIGAR=1X;DPRA=0;EPP=9.52472;LEN=1;MEANALT=1;MQM=41.3333;PAIRED=1;PAO=0;PQA=0;QA=47;RPL=0;RPP=9.52472;RPR=3;RUN=1;SAF=0;SAP=9.52472;SAR=3;TYPE=snp;AN=32;AC=2 GT:GQ:DP:AD:RO:QR:AO:QA:GL 0/0:99:30:24,4:24:826:4:53:0,-3.70077,-63.4378 0/0:99:60:51,7:51:1749:7:133:0,-6.40372,-135.949 ./.:.:.:.:.:.:.:.:. 0/0:99:1723:1610,90:1610:56108:90:1320:0,-398.369,-4702.41 0/0:99:1454:1324,114:1324:45488:114:1617:0,-297.358,-3778.2 0/0:99:50:41,8:41:1417:8:102:0,-5.73793,-114.628 0/0:99:568:521,40:521:17979:40:575:0,-117.94,-1496.11 0/0:99:47:39,6:39:1353:6:127:0,-2.30327,-104.561 0/0:99:1933:1783,132:1783:60625:132:2013:0,-411.397,-5054.5 ./.:.:.:.:.:.:.:.:. ./.:.:.:.:.:.:.:.:. ./.:.:.:.:.:.:.:.:. ./.:.:.:.:.:.:.:.:. ./.:.:.:.:.:.:.:.:. 0/0:99:91:71,20:71:2465:20:257:0,-4.50985,-189.426 ./.:.:.:.:.:.:.:.:. ./.:.:.:.:.:.:.:.:. ./.:.:.:.:.:.:.:.:. 0/0:99:1112:1031,66:1031:35637:66:876:0,-252.949,-2984.74 ./.:.:.:.:.:.:.:.:. 0/0:99:46:41,4:41:1467:4:56:0,-8.6219,-123.072 0/0:99:68:55,12:55:1927:12:212:0,-1.8433,-148.457 0/0:99:1382:1292,72:1292:45198:72:1041:0,-326.041,-3783.22 0/0:99:1701:1571,107:1571:54235:107:1501:0,-375.694,-4546.25 0/1:0:53:41,12:41:1431:12:225:-4.14708,0,-109.171 0/1:0:12:9,3:9:307:3:47:-0.765558,0,-23.4888
## BS
## NC_007175.2 12774 . C T 1000 PASS DP=91497;ADF=0,0;ADR=0,220;AD=0,220;AN=52;AC=26 GT:DP:ADF:ADR:AD:BSD:BSQ:ALFR 0/1:407:0,0:0,407:0,407:0,0,223,0,0,407,0,0:0,0,36,0,0,37,0,0:0,1 0/1:5786:0,0:8,5778:8,5778:0,0,4267,1,3,5778,8,0:0,0,36,25,37,36,36,0:0.001,0.999 0/1:557:0,0:1,556:1,556:0,0,391,0,1,556,1,0:0,0,36,0,37,37,37,0:0.002,0.998 0/1:819:0,0:0,819:0,819:0,0,695,0,0,819,0,0:0,0,36,0,0,36,0,0:0,1 0/1:2838:0,0:6,2832:6,2832:0,0,1829,0,1,2832,6,0:0,0,36,0,37,36,35,0:0.002,0.998 0/1:4256:0,0:9,4247:9,4247:0,0,2781,0,4,4247,9,1:0,0,36,0,34,36,37,37:0.002,0.998 0/1:5216:0,0:9,5207:9,5207:0,0,6064,0,2,5207,9,1:0,0,36,0,31,36,37,37:0.002,0.998 0/1:3184:0,0:2,3182:2,3182:0,0,1748,0,1,3182,2,1:0,0,36,0,37,36,37,25:0.001,0.999 0/1:5953:0,0:7,5946:7,5946:0,0,3806,0,0,5946,7,1:0,0,36,0,0,37,35,25:0.001,0.999 0/1:7521:0,0:10,7511:10,7511:0,0,5104,5,7,7511,10,1:0,0,36,25,35,36,36,25:0.001,0.999 0/1:386:0,0:2,384:2,384:0,0,299,0,0,384,2,0:0,0,36,0,0,37,37,0:0.005,0.995 0/1:4995:0,0:8,4987:8,4987:0,0,3422,1,1,4987,8,1:0,0,36,25,37,36,37,37:0.002,0.998 0/1:2953:0,0:2,2951:2,2951:0,0,2036,0,1,2951,2,0:0,0,36,0,37,36,37,0:0.001,0.999 0/1:288:0,0:2,286:2,286:0,0,167,0,0,286,2,0:0,0,36,0,0,36,37,0:0.007,0.993 0/1:283:0,0:4,279:4,279:0,0,195,0,0,279,4,0:0,0,36,0,0,36,37,0:0.014,0.986 0/1:747:0,0:3,744:3,744:0,0,554,0,0,744,3,0:0,0,36,0,0,37,37,0:0.004,0.996 0/1:8439:0,0:17,8422:17,8422:0,0,6163,3,5,8422,17,0:0,0,36,37,37,36,36,0:0.002,0.998 0/1:597:0,0:0,597:0,597:0,0,494,2,3,597,0,0:0,0,36,25,37,36,0,0:0,1 0/1:6748:0,0:8,6740:8,6740:0,0,5233,1,6,6740,8,0:0,0,36,25,37,36,37,0:0.001,0.999 0/1:6916:0,0:8,6908:8,6908:0,0,6197,1,2,6908,8,0:0,0,36,25,37,37,37,0:0.001,0.999 0/1:7641:0,0:11,7630:11,7630:0,0,6446,2,5,7630,11,0:0,0,36,25,37,36,36,0:0.001,0.999 0/1:7115:0,0:4,7111:4,7111:1,0,6214,1,4,7111,4,0:25,0,36,25,37,36,37,0:0.001,0.999 0/1:5198:0,0:3,5195:3,5195:0,0,4280,0,1,5195,3,1:0,0,36,0,37,36,37,37:0.001,0.999 0/1:521:0,0:2,519:2,519:0,0,287,0,0,519,2,0:0,0,36,0,0,36,37,0:0.004,0.996 0/1:1913:0,0:4,1909:4,1909:0,0,1107,0,0,1909,4,2:0,0,36,0,0,37,37,37:0.002,0.998 0/1:220:0,0:0,220:0,220:0,0,158,0,0,220,0,0:0,0,36,0,0,37,0,0:0,1
## NC_007175.2 15247 . C T 1000 PASS DP=43802;ADF=0,0;ADR=0,57;AD=0,57;AN=52;AC=26 GT:DP:ADF:ADR:AD:BSD:BSQ:ALFR 0/1:112:0,0:0,112:0,112:0,0,322,0,0,112,0,0:0,0,36,0,0,36,0,0:0,1 0/1:2287:0,0:5,2282:5,2282:0,0,3893,1,2,2282,5,1:0,0,36,25,37,36,35,25:0.002,0.998 0/1:174:0,0:0,174:0,174:0,0,408,0,0,174,0,0:0,0,37,0,0,36,0,0:0,1 0/1:312:0,0:0,312:0,312:0,0,805,0,0,312,0,0:0,0,36,0,0,36,0,0:0,1 0/1:1310:0,0:0,1310:0,1310:0,0,1883,0,0,1310,0,0:0,0,36,0,0,36,0,0:0,1 0/1:2014:0,0:8,2006:8,2006:0,0,2965,0,3,2006,8,0:0,0,36,0,33,36,36,0:0.004,0.996 0/1:4017:0,0:7,4010:7,4010:0,0,6081,0,6,4010,7,0:0,0,36,0,37,36,37,0:0.002,0.998 0/1:1398:0,0:2,1396:2,1396:0,0,1817,0,2,1396,2,0:0,0,36,0,37,36,37,0:0.001,0.999 0/1:2263:0,0:2,2261:2,2261:0,0,3922,1,3,2261,2,0:0,0,36,25,33,36,37,0:0.001,0.999 0/1:3506:0,0:2,3504:2,3504:0,0,4504,0,3,3504,2,0:0,0,36,0,37,36,37,0:0.001,0.999 0/1:140:0,0:2,138:2,138:0,0,291,0,0,138,2,0:0,0,36,0,0,36,37,0:0.014,0.986 0/1:2187:0,0:0,2187:0,2187:0,0,3267,0,0,2187,0,1:0,0,36,0,0,36,0,25:0,1 0/1:1099:0,0:3,1096:3,1096:1,0,1999,0,0,1096,3,0:37,0,36,0,0,36,29,0:0.003,0.997 0/1:106:0,0:0,106:0,106:0,0,182,0,0,106,0,0:0,0,36,0,0,36,0,0:0,1 0/1:136:0,0:0,136:0,136:0,0,249,0,0,136,0,0:0,0,36,0,0,36,0,0:0,1 0/1:230:0,0:0,230:0,230:0,0,540,0,0,230,0,0:0,0,36,0,0,36,0,0:0,1 0/1:4059:0,0:9,4050:9,4050:0,0,5635,1,5,4050,9,2:0,0,36,37,37,36,36,31:0.002,0.998 0/1:188:0,0:0,188:0,188:0,0,624,1,0,188,0,0:0,0,36,25,0,36,0,0:0,1 0/1:3105:0,0:3,3102:3,3102:1,0,4920,0,4,3102,3,1:25,0,36,0,34,36,37,25:0.001,0.999 0/1:3066:0,0:3,3063:3,3063:0,0,6416,2,3,3063,3,0:0,0,36,37,33,36,37,0:0.001,0.999 0/1:4533:0,0:6,4527:6,4527:0,0,5452,1,2,4527,6,0:0,0,36,37,37,36,35,0:0.001,0.999 0/1:3451:0,0:5,3446:5,3446:0,0,6195,2,1,3446,5,2:0,0,36,25,37,36,37,37:0.001,0.999 0/1:2841:0,0:0,2841:0,2841:1,0,4298,0,3,2841,0,1:25,0,36,0,33,36,0,25:0,1 0/1:159:0,0:0,159:0,159:0,0,373,0,0,159,0,0:0,0,36,0,0,36,0,0:0,1 0/1:1052:0,0:4,1048:4,1048:0,0,1293,1,0,1048,4,0:0,0,36,25,0,36,37,0:0.004,0.996 0/1:57:0,0:0,57:0,57:0,0,165,0,0,57,0,0:0,0,37,0,0,35,0,0:0,1PLINK is a widely used open-source whole-genome association analysis toolset, which can handle large datasets and perform a variety of analyses including population stratification.
Here’s a general outline of the steps you’d take:
Conversion of VCF to PLINK format: PLINK
operates on a different file format than VCF. You need to convert your
VCF to PLINK format, which generally comprises three separate files:
.bed (binary pedigree), .bim (extended MAP
file), and .fam (family file). You can do this using
PLINK’s --vcf option:
plink --vcf your_merged.vcf --make-bed --out plink_filesThis will create plink_files.bed,
plink_files.bim, and plink_files.fam.
Calculate Identity-by-State (IBS) matrix: You
can calculate the IBS matrix using the --genome option in
PLINK. This gives a measure of the genetic similarity between all pairs
of individuals in your dataset:
plink --bfile plink_files --genome --out ibs_matrixThis will produce a file ibs_matrix.genome which
contains the pairwise IBS matrix.
Create the Genetic Relatedness Matrix (GRM): You can use this IBS matrix to create a GRM. The GRM is a square symmetric matrix that quantifies the degree of genetic variance that can be explained by the genetic markers between each pair of individuals in your samples.
GCTA (Genome-wide Complex Trait Analysis) is a tool that can help to create a GRM from your IBS matrix:
gcta64 --bfile plink_files --make-grm --out grm_filesThis will produce two files (grm_files.grm.bin and
grm_files.grm.N.bin) representing the GRM.
/home/shared/plink_linux_x86_64_20230116/plink \
--vcf ../data/Cv_10x_fxmerge_05.recode.vcf \
--make-bed \
--allow-extra-chr \
--out ../output/52-genetic-relatedness/plink_files/home/shared/plink_linux_x86_64_20230116/plink -help --vcf-half-call <m> : Specify how '0/.' and similar VCF GT values should be
handled. The following four modes are supported:
* 'error'/'e' (default) errors out and reports line #.
* 'haploid'/'h' treats them as haploid calls.
* 'missing'/'m' treats them as missing.
* 'reference'/'r' treats the missing value as 0./home/shared/plink_linux_x86_64_20230116/plink \
--vcf ../output/51-SNPs/EpiDiv_merged.f.recode.vcf \
--make-bed \
--allow-extra-chr \
--vcf-half-call m \
--out ../output/52-genetic-relatedness/plink_files## PLINK v1.90b7 64-bit (16 Jan 2023) www.cog-genomics.org/plink/1.9/
## (C) 2005-2023 Shaun Purcell, Christopher Chang GNU General Public License v3
## Logging to ../output/52-genetic-relatedness/plink_files.log.
## Options in effect:
## --allow-extra-chr
## --make-bed
## --out ../output/52-genetic-relatedness/plink_files
## --vcf ../output/51-SNPs/EpiDiv_merged.f.recode.vcf
## --vcf-half-call m
##
## 253367 MB RAM detected; reserving 126683 MB for main workspace.
## --vcf: 1k variants complete.--vcf: 2k variants complete.--vcf: 3k variants complete.--vcf: 4k variants complete.--vcf: 5k variants complete.--vcf: 6k variants complete.--vcf: 7k variants complete.--vcf: 8k variants complete.--vcf: 9k variants complete.--vcf: 10k variants complete.--vcf: 11k variants complete.--vcf: 12k variants complete.--vcf: 13k variants complete.--vcf: 14k variants complete.--vcf: 15k variants complete.--vcf: 16k variants complete.--vcf: 17k variants complete.--vcf: 18k variants complete.--vcf: 19k variants complete.--vcf: 20k variants complete.--vcf: 21k variants complete.--vcf: 22k variants complete.--vcf: 23k variants complete.--vcf: 24k variants complete.--vcf: 25k variants complete.--vcf: 26k variants complete.--vcf: 27k variants complete.--vcf: 28k variants complete.--vcf: 29k variants complete.--vcf: 30k variants complete.--vcf: 31k variants complete.--vcf: 32k variants complete.--vcf: 33k variants complete.--vcf: 34k variants complete.--vcf: 35k variants 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complete.--vcf: 1251k variants complete.--vcf: 1252k variants complete.--vcf: 1253k variants complete.--vcf: 1254k variants complete.--vcf: 1255k variants complete.--vcf: 1256k variants complete.--vcf: 1257k variants complete.--vcf: 1258k variants complete.--vcf: 1259k variants complete.--vcf: 1260k variants complete.--vcf: 1261k variants complete.--vcf: 1262k variants complete.--vcf: 1263k variants complete.--vcf: 1264k variants complete.--vcf: 1265k variants complete.--vcf: 1266k variants complete.--vcf: 1267k variants complete.--vcf: 1268k variants complete.--vcf: 1269k variants complete.--vcf: 1270k variants complete.--vcf: 1271k variants complete.--vcf: 1272k variants complete.--vcf: 1273k variants complete.--vcf: 1274k variants complete.--vcf: 1275k variants complete.--vcf: 1276k variants complete.--vcf: 1277k variants complete.--vcf: 1278k variants complete.--vcf: 1279k variants complete.--vcf: 1280k variants complete.--vcf: 1281k variants complete.--vcf: 1282k variants 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complete.--vcf: 2339k variants complete.--vcf: 2340k variants complete.--vcf: 2341k variants complete.--vcf: 2342k variants complete.--vcf: 2343k variants complete.--vcf: ../output/52-genetic-relatedness/plink_files-temporary.bed +
## ../output/52-genetic-relatedness/plink_files-temporary.bim +
## ../output/52-genetic-relatedness/plink_files-temporary.fam written.
## 2343637 variants loaded from .bim file.
## 26 people (0 males, 0 females, 26 ambiguous) loaded from .fam.
## Ambiguous sex IDs written to ../output/52-genetic-relatedness/plink_files.nosex
## .
## Using 1 thread (no multithreaded calculations invoked).
## Before main variant filters, 26 founders and 0 nonfounders present.
## Calculating allele frequencies... 0%1%2%3%4%5%6%7%8%9%10%11%12%13%14%15%16%17%18%19%20%21%22%23%24%25%26%27%28%29%30%31%32%33%34%35%36%37%38%39%40%41%42%43%44%45%46%47%48%49%50%51%52%53%54%55%56%57%58%59%60%61%62%63%64%65%66%67%68%69%70%71%72%73%74%75%76%77%78%79%80%81%82%83%84%85%86%87%88%89%90%91%92%93%94%95%96%97%98%99% done.
## Total genotyping rate is 0.688682.
## 2343637 variants and 26 people pass filters and QC.
## Note: No phenotypes present.
## --make-bed to ../output/52-genetic-relatedness/plink_files.bed +
## ../output/52-genetic-relatedness/plink_files.bim +
## ../output/52-genetic-relatedness/plink_files.fam ... 0%1%2%3%4%5%6%7%8%9%10%11%12%13%14%15%16%17%18%19%20%21%22%23%24%25%26%27%28%29%30%31%32%33%34%35%36%37%38%39%40%41%42%43%44%45%46%47%48%49%50%51%52%53%54%55%56%57%58%59%60%61%62%63%64%65%66%67%68%69%70%71%72%73%74%75%76%77%78%79%80%81%82%83%84%85%86%87%88%89%90%91%92%93%94%95%96%97%98%99%done./home/shared/plink_linux_x86_64_20230116/plink \
--bfile ../output/52-genetic-relatedness/plink_files \
--allow-extra-chr \
--genome \
--out ../output/52-genetic-relatedness/ibs_matrix/home/shared/gcta-1.94.1-linux-x86_64-static \
--bfile ../output/52-genetic-relatedness/plink_files \
--make-grm \
--out ../output/52-genetic-relatedness/grm_filesYes, absolutely. The program ANGSD (Analysis of Next Generation Sequencing Data) is a versatile tool for analyzing low depth Next Generation Sequencing data. This is particularly helpful when working with non-model organisms, ancient DNA, or other datasets where high quality reference genomes might not be available.
ANGSD can calculate the genetic relatedness matrix among individuals based on the genotype likelihoods instead of called genotypes, making it a good choice for low depth sequencing data.
Here are the steps you might follow:
Filtering: It’s generally a good idea to filter your VCF files first, based on your research needs. This might include filtering for minor allele frequency, quality scores, or read depth.
Calculate Relatedness: Use the
-doIBS option in ANGSD to calculate the relatedness between
individuals. You would use something like:
angsd -vcf-gl your_merged.vcf -doIBS 1 -out outputCreate genetic relatedness matrix: The previous step will output a file with the pairwise relatedness values. You can then convert this file to a matrix format for easier analysis.
Please note, as with any analysis, you should carefully consider the assumptions and requirements of the method you’re using. Some of these commands might need to be adjusted depending on the specifics of your data and research question.
Finally, remember to adhere to ethical guidelines and regulations when handling genetic data.
/home/shared/ngsTools/angsd/angsd \
-vcf-gl ../output/51-SNPs/EpiDiv_merged.f.recode.vcf \
-doIBS 1 \
-out ../output/52-genetic-relatedness/angsd-output## -> angsd version: 0.929-19-gb2b41b5 (htslib: 1.9-139-gce7daf7) build(May 8 2023 08:13:13)
## -> VCF still beta. Remember that
## 1. indels are are discarded
## 2. will use chrom, pos PL columns
## 3. GL tags are interpreted as log10 and are scaled to ln (NOT USED)
## 4. GP tags are interpreted directly as unscaled post probs (spec says phredscaled...) (NOT USED)
## 5. FILTER column is currently NOT used (not sure what concensus is)
## 6. -sites does NOT work with vcf input but -r does
## 7. vcffilereading is still BETA, please report strange behaviour
## Error: bam or soap input needed for -doIBSa la
https://github.com/RobertsLab/resources/issues/1681#issuecomment-1642557685
chatGPT
First, let’s understand what these tools are.
ngsRelate: This is a software package used for inferring pairwise relatedness from next-generation sequencing (NGS) data. It can calculate different coefficients of relatedness as well as inbreeding coefficients.
spaa: This is an R package that can calculate the genomic relationship matrix (GRM) and genomic kinship matrix (GKM) using SNP array and NGS data.
As of version 2, NgsRelate can parse BCF/VCF files using htslib with the following command:
./ngsrelate -h my.VCF.gz -O vcf.res
By default, NgsRelate will estimate the allele frequencies using the individuals provided in the VCF files. Allele frequencies from the INFO field can used be used instead using -A TAG. The TAG usually take the form of AF or AF1 but can be set to anything. By default the PL data (Phred-scaled likelihoods for genotypes) is parsed, however, the called genotypes can also be used instead with the -T GT option. If called genotypes are being used, the software requires an additional argument (-c 1). If using -c 2, ngsRelate calls genotypes assuming hardy-weinberg./home/shared/ngsRelate/ngsRelate/ngsRelate \
-h ../output/51-SNPs/EpiDiv_merged.f.recode.vcf \
-T GT \
-c 1 \
-O ../output/52-genetic-relatedness/vcf.relatedness/home/shared/ngsRelate/ngsRelate/ngsRelate \
-h ../data/Cv_10x_fxmerge_05.recode.vcf \
-T GT \
-c 1 \
-O ../output/52-genetic-relatedness/vcf.bs.relatednesshead -2 ../output/52-genetic-relatedness/vcf.relatedness## a b nSites J9 J8 J7 J6 J5 J4 J3 J2 J1 rab Fa Fb theta inbred_relatedness_1_2 inbred_relatedness_2_1 fraternity identity zygosity 2of3_IDB FDiff loglh nIter bestoptimll coverage 2dsfs R0 R1 KING 2dsfs_loglike 2dsfsf_niter
## 0 1 1038400 0.799788 0.000000 0.051841 0.000001 0.000000 0.000000 0.000001 0.148369 0.000000 0.051842 0.148370 0.148370 0.025921 0.000001 0.000000 0.200210 0.000000 0.200210 0.200212 -0.000001 -1663336.396774 118 -1 0.493654 6.306127e-02,2.031383e-02,6.122145e-02,2.076443e-02,1.558777e-01,1.402793e-01,5.729258e-02,1.300012e-01,3.511883e-01 0.760301 0.362614 -0.130234 -1948248.937249 10head -2 ../output/52-genetic-relatedness/vcf.bs.relatedness## a b nSites J9 J8 J7 J6 J5 J4 J3 J2 J1 rab Fa Fb theta inbred_relatedness_1_2 inbred_relatedness_2_1 fraternity identity zygosity 2of3_IDB FDiff loglh nIter bestoptimll coverage 2dsfs R0 R1 KING 2dsfs_loglike 2dsfsf_niter
## 0 1 29417 0.000000 0.000000 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 1.000000 0.000000 0.000000 0.500000 0.000000 0.000000 1.000000 0.000000 1.000000 1.000000 -0.000000 -20977.898199 30 -20977.905108 0.948997 1.767981e-14,1.353035e-07,1.870907e-14,3.921403e-08,9.999996e-01,9.307557e-08,1.102319e-14,1.262805e-07,1.887802e-14 0.000000 2538883.855497 0.500000 -588.341649 6df = read.table("../output/52-genetic-relatedness/vcf.relatedness",header = T)
dfrab <- df[,c("ida","idb","rab")]
distrab <- as.matrix(list2dist(dfrab))
write.table(distrab,file="../output/52-genetic-relatedness/epiMATRIX_mbd_rab.txt", col.names = F, row.names = F, sep = "\t")