iHS calculation in R
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This document provides code to calculate extended haplotype homozygosity (EHH), integrated haplotype score (iHS), and cross-population composite likelihood ratio (XP-CLR) from population genetics data. It loads example data, calculates EHH and iHS for a set of SNPs on chromosome 12, and plots the results. It then loads example results for composite likelihood ratio (CLR) between cattle populations and calculates relative extended haplotype homozygosity (REHH) between the populations, plotting the output. Finally, it calculates iHS for all SNPs on chromosome 1 from one of the cattle populations and plots those results.
![## [1,] "0.05 - 0.075" "60" "0.777287796382857" "0.737413595194812"
## [2,] "0.075 - 0.1" "52" "0.435963216395243" "0.641021685121639"
## [3,] "0.1 - 0.125" "53" "0.332371980508715" "0.494815167465929"
## [4,] "0.125 - 0.15" "56" "0.49169123696354" "0.580781486711665"
## [5,] "0.15 - 0.175" "36" "0.338272919812911" "0.557299171859519"
## [6,] "0.175 - 0.2" "38" "0.18372872314435" "0.450393024202394"
## [7,] "0.2 - 0.225" "37" "0.156221814866492" "0.371917601032433"
## [8,] "0.225 - 0.25" "36" "0.324937638464128" "0.491539213848196"
## [9,] "0.25 - 0.275" "35" "0.198821549387942" "0.53358843127552"
## [10,] "0.275 - 0.3" "30" "0.0277095221301871" "0.549619811280544"
## [11,] "0.3 - 0.325" "42" "0.168813465351846" "0.512617332536968"
## [12,] "0.325 - 0.35" "47" "0.212561823991102" "0.334091037846137"
## [13,] "0.35 - 0.375" "35" "0.0778960787783505" "0.495788198190895"
## [14,] "0.375 - 0.4" "34" "0.0142114538338362" "0.337963648645465"
## [15,] "0.4 - 0.425" "37" "-0.0135618204249136" "0.519292818010164"
## [16,] "0.425 - 0.45" "29" "0.146848067738759" "0.387610402411398"
## [17,] "0.45 - 0.475" "34" "0.023234914963773" "0.462855711456721"
## [18,] "0.475 - 0.5" "22" "-0.0280038381405699" "0.597672428815518"
## [19,] "0.5 - 0.525" "21" "0.0676757215676396" "0.397285061426881"
## [20,] "0.525 - 0.55" "22" "-0.0119346374773765" "0.475444749317303"
## [21,] "0.55 - 0.575" "23" "-0.119650040006845" "0.456309312077108"
## [22,] "0.575 - 0.6" "27" "-0.208393804329524" "0.627878921699334"
## [23,] "0.6 - 0.625" "31" "-0.175432335220113" "0.431580562389071"
## [24,] "0.625 - 0.65" "31" "-0.114913122059472" "0.362470027772815"
## [25,] "0.65 - 0.675" "21" "0.0183870416195869" "0.545114444067057"
## [26,] "0.675 - 0.7" "37" "-0.241776665581487" "0.445729962977197"
## [27,] "0.7 - 0.725" "18" "-0.262633365184881" "0.314960709993038"
## [28,] "0.725 - 0.75" "24" "-0.276070830019936" "0.406614904878564"
## [29,] "0.75 - 0.775" "29" "-0.344832955793417" "0.475726025499208"
## [30,] "0.775 - 0.8" "19" "-0.326154359766926" "0.437583935197108"
## [31,] "0.8 - 0.825" "28" "-0.197815151810967" "0.61906090927441"
## [32,] "0.825 - 0.85" "26" "-0.407636344735006" "0.591045435108097"
## [33,] "0.85 - 0.875" "20" "-0.116549521453988" "0.597016190918244"
## [34,] "0.875 - 0.9" "42" "-0.374897066174067" "0.508197119111094"
## [35,] "0.9 - 0.925" "29" "-0.796408081584825" "0.804739382631854"
## [36,] "0.925 - 0.95" "36" "-0.693833406890539" "0.639986265748046"
ihsplot(ihs_res2$res.ihs) ## iHS plot: y- pvalue, x-bp
3](https://image.slidesharecdn.com/ihs-150922123316-lva1-app6891/85/iHS-calculation-in-R-3-320.jpg)
![−4
−2
0
2
iHS
Chromosome
iHS
12
0
1
2
3
4
Pvalue
Chromosome
−log10[1−2|ΦiHS−0.5|]
12
## Rsb & iHS : using wgscan example's result
data(wgscan.cgu) ; data(wgscan.eut) ## Load example result
head(wgscan.cgu)
## BTA POSITION Freq_1 IHH_1 IHH_2 IES
## F0100190 1 113642 0.5429 319186.5 395166.8 350741.0
## F0100220 1 244699 0.2607 465943.5 377422.8 385189.1
## F0100250 1 369419 0.2964 518137.2 372117.0 396350.0
## F0100270 1 447278 0.1071 742502.6 318958.0 323906.8
## F0100280 1 487654 0.3857 542176.3 364969.2 412955.4
## F0100290 1 524507 0.8429 375305.8 572230.2 380989.9
head(wgscan.eut)
## BTA POSITION Freq_1 IHH_1 IHH_2 IES
## F0100190 1 113642 0.3528 331082.8 340341.6 338224.1
## F0100220 1 244699 0.3264 382078.2 434030.9 424800.2
## F0100250 1 369419 0.1226 416906.0 372273.8 372756.1
## F0100270 1 447278 0.4208 662485.5 337043.8 436346.3
## F0100280 1 487654 0.2321 458545.6 379588.7 386265.6
## F0100290 1 524507 0.8396 393546.0 526026.7 399238.6
res.rsb=ies2rsb(wgscan.cgu,wgscan.eut,"CGU","EUT") ## Rsb: Compare 2 population
head(res.rsb$res.rsb)
## BTA POSITION rSB (CGU vs EUT) Pvalue (bilateral)
## F0100190 1 113642 -0.3653553 0.14578738
4](https://image.slidesharecdn.com/ihs-150922123316-lva1-app6891/85/iHS-calculation-in-R-4-320.jpg)
![## F0100220 1 244699 -0.9188850 0.44592808
## F0100250 1 369419 -0.2621161 0.10059980
## F0100270 1 447278 -1.7440674 1.09072568
## F0100280 1 487654 -0.2396774 0.09120393
## F0100290 1 524507 -0.7081588 0.31980358
rsbplot(res.rsb$res.rsb) ## Rsb plot
−5
0
5
rSB (CGU vs EUT)
Chromosome
rSB
1 4 7 11 17 24
0
2
4
6
8
10
12
14
Pvalue
Chromosome
−log10[1−2|ΦrSB−0.5|]
1 4 7 11 17 24
## all chr iHS plot in wgscan.cgu data
ihs_res3=ihh2ihs(wgscan.cgu)
ihsplot(ihs_res3$res.ihs)
5](https://image.slidesharecdn.com/ihs-150922123316-lva1-app6891/85/iHS-calculation-in-R-5-320.jpg)
![−6
−4
−2
0
2
4
iHS
Chromosome
iHS
1 4 7 11 17 24
0
2
4
6
8
Pvalue
Chromosome
−log10[1−2|ΦiHS−0.5|]
1 4 7 11 17 24
6](https://image.slidesharecdn.com/ihs-150922123316-lva1-app6891/85/iHS-calculation-in-R-6-320.jpg)
iHS calculation in R
- 1. iHS.R secondmath Tue Oct 28 20:23:05 2014 ############## 2014 SNU GEPI population genetics by Jinseob Kim ################### ############## 2. EHH, iHS calculation ################################################## ## Load package & Set directory #install.packages("rehh") library(rehh) ## Loading required package: gplots ## ## Attaching package: 'gplots' ## ## The following object is masked from 'package:stats': ## ## lowess setwd("/home/secondmath/Dropbox/GSPH/myteaching/pop_gene/2012") ## Read example file, chr=12: 1424 SNPs & 280 haplotype a=data2haplohh(hap_file="prac_hap.hap",map_file="prac_map.inp",min_maf=0,chr=12) ## Map file seems OK: 1424 SNPs declared for chromosome 12 ## Standard rehh input file assumed ## Data consists of 280 haplotypes and 1424 SNPs ## EHH par(mfrow=c(1,2)) res1=calc_ehh(a,mrk=456,limhaplo=2,limehh=0.05,plotehh=TRUE,main_leg="EHH plot") res11=calc_ehhs(a,mrk=456,limhaplo=2,limehh=0.05,plotehh=TRUE,main_leg="EHHS plot") # site EHH 1
- 2. 2.6e+07 2.8e+07 3.0e+07 0.00.20.40.60.81.0 EHH plot Position EHH Anc. Allele Der. Allele 2.6e+07 2.8e+07 3.0e+07 0.20.40.60.81.0 EHHS plot Position EHHS ## Integrated EHH res2=scan_hh(a) # a: ancestral, d: derived, IES: average of IHHa & IHHd (squared allele head(res2) ## CHR POSITION FREQ_a IHHa IHHd IES ## F1200140 12 79823 0.1500000 135102.2 68522.91 69777.21 ## F1200150 12 125974 0.4071429 161680.3 107183.15 123610.30 ## F1200170 12 175087 0.3571429 157333.1 155777.56 156094.80 ## F1200180 12 219152 0.2214286 250037.4 159839.73 166333.27 ## F1200190 12 256896 0.1750000 466071.8 173269.33 184501.30 ## F1200210 12 316254 0.3892857 292077.5 228681.21 246790.48 ## iHS ihs_res2=ihh2ihs(res2) head(ihs_res2$res.ihs) ## iHS & pvalue ## CHR POSITION iHS Pvalue ## F1200140 12 79823 0.3222762 0.12653788 ## F1200150 12 125974 0.8177351 0.38351558 ## F1200170 12 175087 -0.1370753 0.05013628 ## F1200180 12 219152 0.7830146 0.36289214 ## F1200190 12 256896 1.7890234 1.13305700 ## F1200210 12 316254 0.6819630 0.30516469 ihs_res2$summary.class ## summary per alle freq bin. ## Freq Class Size Mean iHH SD iHH 2
- 3. ## [1,] "0.05 - 0.075" "60" "0.777287796382857" "0.737413595194812" ## [2,] "0.075 - 0.1" "52" "0.435963216395243" "0.641021685121639" ## [3,] "0.1 - 0.125" "53" "0.332371980508715" "0.494815167465929" ## [4,] "0.125 - 0.15" "56" "0.49169123696354" "0.580781486711665" ## [5,] "0.15 - 0.175" "36" "0.338272919812911" "0.557299171859519" ## [6,] "0.175 - 0.2" "38" "0.18372872314435" "0.450393024202394" ## [7,] "0.2 - 0.225" "37" "0.156221814866492" "0.371917601032433" ## [8,] "0.225 - 0.25" "36" "0.324937638464128" "0.491539213848196" ## [9,] "0.25 - 0.275" "35" "0.198821549387942" "0.53358843127552" ## [10,] "0.275 - 0.3" "30" "0.0277095221301871" "0.549619811280544" ## [11,] "0.3 - 0.325" "42" "0.168813465351846" "0.512617332536968" ## [12,] "0.325 - 0.35" "47" "0.212561823991102" "0.334091037846137" ## [13,] "0.35 - 0.375" "35" "0.0778960787783505" "0.495788198190895" ## [14,] "0.375 - 0.4" "34" "0.0142114538338362" "0.337963648645465" ## [15,] "0.4 - 0.425" "37" "-0.0135618204249136" "0.519292818010164" ## [16,] "0.425 - 0.45" "29" "0.146848067738759" "0.387610402411398" ## [17,] "0.45 - 0.475" "34" "0.023234914963773" "0.462855711456721" ## [18,] "0.475 - 0.5" "22" "-0.0280038381405699" "0.597672428815518" ## [19,] "0.5 - 0.525" "21" "0.0676757215676396" "0.397285061426881" ## [20,] "0.525 - 0.55" "22" "-0.0119346374773765" "0.475444749317303" ## [21,] "0.55 - 0.575" "23" "-0.119650040006845" "0.456309312077108" ## [22,] "0.575 - 0.6" "27" "-0.208393804329524" "0.627878921699334" ## [23,] "0.6 - 0.625" "31" "-0.175432335220113" "0.431580562389071" ## [24,] "0.625 - 0.65" "31" "-0.114913122059472" "0.362470027772815" ## [25,] "0.65 - 0.675" "21" "0.0183870416195869" "0.545114444067057" ## [26,] "0.675 - 0.7" "37" "-0.241776665581487" "0.445729962977197" ## [27,] "0.7 - 0.725" "18" "-0.262633365184881" "0.314960709993038" ## [28,] "0.725 - 0.75" "24" "-0.276070830019936" "0.406614904878564" ## [29,] "0.75 - 0.775" "29" "-0.344832955793417" "0.475726025499208" ## [30,] "0.775 - 0.8" "19" "-0.326154359766926" "0.437583935197108" ## [31,] "0.8 - 0.825" "28" "-0.197815151810967" "0.61906090927441" ## [32,] "0.825 - 0.85" "26" "-0.407636344735006" "0.591045435108097" ## [33,] "0.85 - 0.875" "20" "-0.116549521453988" "0.597016190918244" ## [34,] "0.875 - 0.9" "42" "-0.374897066174067" "0.508197119111094" ## [35,] "0.9 - 0.925" "29" "-0.796408081584825" "0.804739382631854" ## [36,] "0.925 - 0.95" "36" "-0.693833406890539" "0.639986265748046" ihsplot(ihs_res2$res.ihs) ## iHS plot: y- pvalue, x-bp 3
- 4. −4 −2 0 2 iHS Chromosome iHS 12 0 1 2 3 4 Pvalue Chromosome −log10[1−2|ΦiHS−0.5|] 12 ## Rsb & iHS : using wgscan example's result data(wgscan.cgu) ; data(wgscan.eut) ## Load example result head(wgscan.cgu) ## BTA POSITION Freq_1 IHH_1 IHH_2 IES ## F0100190 1 113642 0.5429 319186.5 395166.8 350741.0 ## F0100220 1 244699 0.2607 465943.5 377422.8 385189.1 ## F0100250 1 369419 0.2964 518137.2 372117.0 396350.0 ## F0100270 1 447278 0.1071 742502.6 318958.0 323906.8 ## F0100280 1 487654 0.3857 542176.3 364969.2 412955.4 ## F0100290 1 524507 0.8429 375305.8 572230.2 380989.9 head(wgscan.eut) ## BTA POSITION Freq_1 IHH_1 IHH_2 IES ## F0100190 1 113642 0.3528 331082.8 340341.6 338224.1 ## F0100220 1 244699 0.3264 382078.2 434030.9 424800.2 ## F0100250 1 369419 0.1226 416906.0 372273.8 372756.1 ## F0100270 1 447278 0.4208 662485.5 337043.8 436346.3 ## F0100280 1 487654 0.2321 458545.6 379588.7 386265.6 ## F0100290 1 524507 0.8396 393546.0 526026.7 399238.6 res.rsb=ies2rsb(wgscan.cgu,wgscan.eut,"CGU","EUT") ## Rsb: Compare 2 population head(res.rsb$res.rsb) ## BTA POSITION rSB (CGU vs EUT) Pvalue (bilateral) ## F0100190 1 113642 -0.3653553 0.14578738 4
- 5. ## F0100220 1 244699 -0.9188850 0.44592808 ## F0100250 1 369419 -0.2621161 0.10059980 ## F0100270 1 447278 -1.7440674 1.09072568 ## F0100280 1 487654 -0.2396774 0.09120393 ## F0100290 1 524507 -0.7081588 0.31980358 rsbplot(res.rsb$res.rsb) ## Rsb plot −5 0 5 rSB (CGU vs EUT) Chromosome rSB 1 4 7 11 17 24 0 2 4 6 8 10 12 14 Pvalue Chromosome −log10[1−2|ΦrSB−0.5|] 1 4 7 11 17 24 ## all chr iHS plot in wgscan.cgu data ihs_res3=ihh2ihs(wgscan.cgu) ihsplot(ihs_res3$res.ihs) 5
- 6. −6 −4 −2 0 2 4 iHS Chromosome iHS 1 4 7 11 17 24 0 2 4 6 8 Pvalue Chromosome −log10[1−2|ΦiHS−0.5|] 1 4 7 11 17 24 6