hotsize: Hotspot size routines.
In qtlhot: Inference for QTL Hotspots
Description
Usage
Arguments
Value
Author(s)
See Also
Examples
Description
Determine hotspot sizes and display. Use individual threshold and
quantile thresholds as provided.
Usage
1
2
3
4
5
6
7
8
9
10
11
12
13
14
hotsize(hotobject, ...)
## S3 method for class 'scanone'
hotsize(hotobject, lod.thr = NULL, drop.lod = 1.5, ...)
## S3 method for class 'highlod'
hotsize(hotobject, lod.thr = NULL, window = NULL,
quant.level = NULL, ...)
## S3 method for class 'hotsize'
print(x, ...)
## S3 method for class 'hotsize'
summary(object, ...)
## S3 method for class 'hotsize'
plot(x, ylab = "counts", quant.axis = pretty(x$max.N),
col = c("black", "red", "blue"), by.chr = FALSE, maps = NULL,
title = "",...)
Arguments
hotobject
object of class scanone or highlod
lod.thr
LOD threshold
drop.lod
LOD drop from max to keep for support intervals
window
window width in cM for smoothing hotspot size; not used
if 0 or NULL
quant.level
vector of LOD levels for 1 up to
length(quant.level) size hotspots
x,object
object of class hotsize
ylab
label for vertical plot axis
quant.axis
hotspot sizes for quantile axis (vertical on right
side of plot)
col
col of hotspot size, smoothed hotspot size, and sliding
hotspot size
by.chr
separate plot by chromosome if TRUE
maps
if not NULL, list of objects of class map
to use for rugs on top and bottom of plot
title
title for plot
...
arguments passed along to scanone methods
Value
hotsize methods return an object of class hotsize, which
is essentially an object of class summary.scanone
with additional attributes for lod.thr, window, and
quant.level.
Author(s)
Brian S Yandell and Elias Chaibub Neto
See Also
Examples
1
2
3
4
Example output
Loading required package: qtl
Loading required package: lattice
Loading required package: corpcor
Loading required package: mnormt
highld> example(include.hotspots)
incld.> ncross1 <- sim.null.cross(chr.len = rep(100, 4),
incld.+ n.mar = 51,
incld.+ n.ind = 100,
incld.+ type = "bc",
incld.+ n.phe = 1000,
incld.+ latent.eff = 3,
incld.+ res.var = 1,
incld.+ init.seed = 123457)
incld.> cross1 <- include.hotspots(cross = ncross1,
incld.+ hchr = c(2, 3, 4),
incld.+ hpos = c(25, 75, 50),
incld.+ hsize = c(100, 50, 20),
incld.+ Q.eff = 2,
incld.+ latent.eff = 3,
incld.+ lod.range.1 = c(2.5, 2.5),
incld.+ lod.range.2 = c(5, 8),
incld.+ lod.range.3 = c(10, 15),
incld.+ res.var = 1,
incld.+ n.phe = 1000,
incld.+ init.seed = 12345)
highld> scan1 <- scanone(cross1, pheno.col = 1:1000, method = "hk")
highld> high1 <- highlod(scan1, lod.thr = 2.11, drop.lod = 1.5)
highld> pull.highlod(high1, chr = 2, pos = 24)
chr pos phenos lod
D2M13 2 24 P2 3.388776
D2M13.1 2 24 P6 3.002020
D2M13.2 2 24 P8 3.430235
D2M13.3 2 24 P18 2.272088
D2M13.4 2 24 P35 2.877761
D2M13.5 2 24 P42 2.627779
D2M13.6 2 24 P45 3.314888
D2M13.7 2 24 P53 3.598085
D2M13.8 2 24 P56 2.460279
D2M13.9 2 24 P58 3.439272
D2M13.10 2 24 P72 3.849090
D2M13.11 2 24 P76 3.381574
D2M13.12 2 24 P87 2.838147
D2M13.13 2 24 P129 2.437061
D2M13.14 2 24 P133 2.792576
D2M13.15 2 24 P139 3.018036
D2M13.16 2 24 P140 2.984040
D2M13.17 2 24 P151 3.040573
D2M13.18 2 24 P166 3.823492
D2M13.19 2 24 P176 2.982420
D2M13.20 2 24 P182 4.150266
D2M13.21 2 24 P202 2.837522
D2M13.22 2 24 P205 2.759836
D2M13.23 2 24 P221 3.514802
D2M13.24 2 24 P223 2.727625
D2M13.25 2 24 P243 3.954829
D2M13.26 2 24 P249 2.750183
D2M13.27 2 24 P280 2.855761
D2M13.28 2 24 P299 3.022717
D2M13.29 2 24 P307 2.971370
D2M13.30 2 24 P312 3.200077
D2M13.31 2 24 P320 2.735781
D2M13.32 2 24 P324 3.263333
D2M13.33 2 24 P347 4.481063
D2M13.34 2 24 P349 3.540741
D2M13.35 2 24 P358 2.915029
D2M13.36 2 24 P359 3.256071
D2M13.37 2 24 P381 3.334650
D2M13.38 2 24 P382 2.636571
D2M13.39 2 24 P386 3.208191
D2M13.40 2 24 P396 2.907832
D2M13.41 2 24 P411 2.760250
D2M13.42 2 24 P412 3.040671
D2M13.43 2 24 P445 2.831598
D2M13.44 2 24 P455 2.815784
D2M13.45 2 24 P456 3.251606
D2M13.46 2 24 P459 3.470346
D2M13.47 2 24 P466 3.444492
D2M13.48 2 24 P470 2.118428
D2M13.49 2 24 P471 2.736852
D2M13.50 2 24 P472 3.314180
D2M13.51 2 24 P473 3.929050
D2M13.52 2 24 P506 3.310885
D2M13.53 2 24 P530 2.944440
D2M13.54 2 24 P546 3.648390
D2M13.55 2 24 P560 3.597727
D2M13.56 2 24 P573 2.796950
D2M13.57 2 24 P594 4.496695
D2M13.58 2 24 P595 2.981309
D2M13.59 2 24 P605 2.462974
D2M13.60 2 24 P630 3.754764
D2M13.61 2 24 P641 3.734657
D2M13.62 2 24 P648 3.321849
D2M13.63 2 24 P651 2.929950
D2M13.64 2 24 P660 3.430068
D2M13.65 2 24 P678 2.899678
D2M13.66 2 24 P681 2.963974
D2M13.67 2 24 P689 3.699696
D2M13.68 2 24 P692 2.831405
D2M13.69 2 24 P693 3.059182
D2M13.70 2 24 P710 2.972535
D2M13.71 2 24 P721 2.437751
D2M13.72 2 24 P722 2.816196
D2M13.73 2 24 P727 2.641131
D2M13.74 2 24 P733 3.236445
D2M13.75 2 24 P735 3.395650
D2M13.76 2 24 P740 3.386157
D2M13.77 2 24 P745 4.043596
D2M13.78 2 24 P751 3.200972
D2M13.79 2 24 P755 3.137649
D2M13.80 2 24 P760 3.107310
D2M13.81 2 24 P770 3.228695
D2M13.82 2 24 P786 3.007986
D2M13.83 2 24 P801 2.829519
D2M13.84 2 24 P838 2.382058
D2M13.85 2 24 P845 2.794768
D2M13.86 2 24 P871 2.746736
D2M13.87 2 24 P875 2.782606
D2M13.88 2 24 P882 3.050230
D2M13.89 2 24 P884 2.646522
D2M13.90 2 24 P887 2.999239
D2M13.91 2 24 P889 3.605486
D2M13.92 2 24 P917 3.511876
D2M13.93 2 24 P918 3.033706
D2M13.94 2 24 P925 3.052736
D2M13.95 2 24 P934 3.630265
D2M13.96 2 24 P945 2.979431
D2M13.97 2 24 P958 3.247551
D2M13.98 2 24 P971 3.571035
D2M13.99 2 24 P981 3.555443
highld> summary(high1, lod.thr = 2.44)
hotsize elements: chr pos max.N
LOD threshold: 2.44
chr pos max.N
D1M48 1 94 41
D2M13 2 24 95
D3M36 3 70 50
D4M25 4 48 20
highld> max(high1, lod.thr = seq(2.11, 3.11, by = .1))
chr pos max.N lod.thr
D1M34 1 66 126 2.11
D2M13 2 24 99 2.21
D2M12 2 22 98 2.31
D2M131 2 24 97 2.41
D2M132 2 24 93 2.51
D2M121 2 22 93 2.61
D2M133 2 24 89 2.71
D2M122 2 22 78 2.81
D2M123 2 22 67 2.91
D2M134 2 24 54 3.01
D3M38 3 74 50 3.11
hotsize elements: chr pos max.N
LOD threshold: 2.11
chr pos max.N
D1M34 1 66 126
D2M12 2 22 100
D3M36 3 70 50
D4M23 4 44 20
qtlhot documentation built on May 2, 2019, 11:06 a.m.
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Description Usage Arguments Value Author(s) See Also Examples
Description
Determine hotspot sizes and display. Use individual threshold and quantile thresholds as provided.
Usage
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | hotsize(hotobject, ...)
## S3 method for class 'scanone'
hotsize(hotobject, lod.thr = NULL, drop.lod = 1.5, ...)
## S3 method for class 'highlod'
hotsize(hotobject, lod.thr = NULL, window = NULL,
quant.level = NULL, ...)
## S3 method for class 'hotsize'
print(x, ...)
## S3 method for class 'hotsize'
summary(object, ...)
## S3 method for class 'hotsize'
plot(x, ylab = "counts", quant.axis = pretty(x$max.N),
col = c("black", "red", "blue"), by.chr = FALSE, maps = NULL,
title = "",...)
|
Arguments
hotobject |
object of class |
lod.thr |
LOD threshold |
drop.lod |
LOD drop from max to keep for support intervals |
window |
window width in cM for smoothing hotspot size; not used
if |
quant.level |
vector of LOD levels for 1 up to
|
x,object |
object of class |
ylab |
label for vertical plot axis |
quant.axis |
hotspot sizes for quantile axis (vertical on right side of plot) |
col |
col of hotspot size, smoothed hotspot size, and sliding hotspot size |
by.chr |
separate plot by chromosome if |
maps |
if not |
title |
title for plot |
... |
arguments passed along to scanone methods |
Value
hotsize methods return an object of class hotsize, which
is essentially an object of class summary.scanone
with additional attributes for lod.thr, window, and
quant.level.
Author(s)
Brian S Yandell and Elias Chaibub Neto
See Also
Examples
1 2 3 4 |
Example output
Loading required package: qtl
Loading required package: lattice
Loading required package: corpcor
Loading required package: mnormt
highld> example(include.hotspots)
incld.> ncross1 <- sim.null.cross(chr.len = rep(100, 4),
incld.+ n.mar = 51,
incld.+ n.ind = 100,
incld.+ type = "bc",
incld.+ n.phe = 1000,
incld.+ latent.eff = 3,
incld.+ res.var = 1,
incld.+ init.seed = 123457)
incld.> cross1 <- include.hotspots(cross = ncross1,
incld.+ hchr = c(2, 3, 4),
incld.+ hpos = c(25, 75, 50),
incld.+ hsize = c(100, 50, 20),
incld.+ Q.eff = 2,
incld.+ latent.eff = 3,
incld.+ lod.range.1 = c(2.5, 2.5),
incld.+ lod.range.2 = c(5, 8),
incld.+ lod.range.3 = c(10, 15),
incld.+ res.var = 1,
incld.+ n.phe = 1000,
incld.+ init.seed = 12345)
highld> scan1 <- scanone(cross1, pheno.col = 1:1000, method = "hk")
highld> high1 <- highlod(scan1, lod.thr = 2.11, drop.lod = 1.5)
highld> pull.highlod(high1, chr = 2, pos = 24)
chr pos phenos lod
D2M13 2 24 P2 3.388776
D2M13.1 2 24 P6 3.002020
D2M13.2 2 24 P8 3.430235
D2M13.3 2 24 P18 2.272088
D2M13.4 2 24 P35 2.877761
D2M13.5 2 24 P42 2.627779
D2M13.6 2 24 P45 3.314888
D2M13.7 2 24 P53 3.598085
D2M13.8 2 24 P56 2.460279
D2M13.9 2 24 P58 3.439272
D2M13.10 2 24 P72 3.849090
D2M13.11 2 24 P76 3.381574
D2M13.12 2 24 P87 2.838147
D2M13.13 2 24 P129 2.437061
D2M13.14 2 24 P133 2.792576
D2M13.15 2 24 P139 3.018036
D2M13.16 2 24 P140 2.984040
D2M13.17 2 24 P151 3.040573
D2M13.18 2 24 P166 3.823492
D2M13.19 2 24 P176 2.982420
D2M13.20 2 24 P182 4.150266
D2M13.21 2 24 P202 2.837522
D2M13.22 2 24 P205 2.759836
D2M13.23 2 24 P221 3.514802
D2M13.24 2 24 P223 2.727625
D2M13.25 2 24 P243 3.954829
D2M13.26 2 24 P249 2.750183
D2M13.27 2 24 P280 2.855761
D2M13.28 2 24 P299 3.022717
D2M13.29 2 24 P307 2.971370
D2M13.30 2 24 P312 3.200077
D2M13.31 2 24 P320 2.735781
D2M13.32 2 24 P324 3.263333
D2M13.33 2 24 P347 4.481063
D2M13.34 2 24 P349 3.540741
D2M13.35 2 24 P358 2.915029
D2M13.36 2 24 P359 3.256071
D2M13.37 2 24 P381 3.334650
D2M13.38 2 24 P382 2.636571
D2M13.39 2 24 P386 3.208191
D2M13.40 2 24 P396 2.907832
D2M13.41 2 24 P411 2.760250
D2M13.42 2 24 P412 3.040671
D2M13.43 2 24 P445 2.831598
D2M13.44 2 24 P455 2.815784
D2M13.45 2 24 P456 3.251606
D2M13.46 2 24 P459 3.470346
D2M13.47 2 24 P466 3.444492
D2M13.48 2 24 P470 2.118428
D2M13.49 2 24 P471 2.736852
D2M13.50 2 24 P472 3.314180
D2M13.51 2 24 P473 3.929050
D2M13.52 2 24 P506 3.310885
D2M13.53 2 24 P530 2.944440
D2M13.54 2 24 P546 3.648390
D2M13.55 2 24 P560 3.597727
D2M13.56 2 24 P573 2.796950
D2M13.57 2 24 P594 4.496695
D2M13.58 2 24 P595 2.981309
D2M13.59 2 24 P605 2.462974
D2M13.60 2 24 P630 3.754764
D2M13.61 2 24 P641 3.734657
D2M13.62 2 24 P648 3.321849
D2M13.63 2 24 P651 2.929950
D2M13.64 2 24 P660 3.430068
D2M13.65 2 24 P678 2.899678
D2M13.66 2 24 P681 2.963974
D2M13.67 2 24 P689 3.699696
D2M13.68 2 24 P692 2.831405
D2M13.69 2 24 P693 3.059182
D2M13.70 2 24 P710 2.972535
D2M13.71 2 24 P721 2.437751
D2M13.72 2 24 P722 2.816196
D2M13.73 2 24 P727 2.641131
D2M13.74 2 24 P733 3.236445
D2M13.75 2 24 P735 3.395650
D2M13.76 2 24 P740 3.386157
D2M13.77 2 24 P745 4.043596
D2M13.78 2 24 P751 3.200972
D2M13.79 2 24 P755 3.137649
D2M13.80 2 24 P760 3.107310
D2M13.81 2 24 P770 3.228695
D2M13.82 2 24 P786 3.007986
D2M13.83 2 24 P801 2.829519
D2M13.84 2 24 P838 2.382058
D2M13.85 2 24 P845 2.794768
D2M13.86 2 24 P871 2.746736
D2M13.87 2 24 P875 2.782606
D2M13.88 2 24 P882 3.050230
D2M13.89 2 24 P884 2.646522
D2M13.90 2 24 P887 2.999239
D2M13.91 2 24 P889 3.605486
D2M13.92 2 24 P917 3.511876
D2M13.93 2 24 P918 3.033706
D2M13.94 2 24 P925 3.052736
D2M13.95 2 24 P934 3.630265
D2M13.96 2 24 P945 2.979431
D2M13.97 2 24 P958 3.247551
D2M13.98 2 24 P971 3.571035
D2M13.99 2 24 P981 3.555443
highld> summary(high1, lod.thr = 2.44)
hotsize elements: chr pos max.N
LOD threshold: 2.44
chr pos max.N
D1M48 1 94 41
D2M13 2 24 95
D3M36 3 70 50
D4M25 4 48 20
highld> max(high1, lod.thr = seq(2.11, 3.11, by = .1))
chr pos max.N lod.thr
D1M34 1 66 126 2.11
D2M13 2 24 99 2.21
D2M12 2 22 98 2.31
D2M131 2 24 97 2.41
D2M132 2 24 93 2.51
D2M121 2 22 93 2.61
D2M133 2 24 89 2.71
D2M122 2 22 78 2.81
D2M123 2 22 67 2.91
D2M134 2 24 54 3.01
D3M38 3 74 50 3.11
hotsize elements: chr pos max.N
LOD threshold: 2.11
chr pos max.N
D1M34 1 66 126
D2M12 2 22 100
D3M36 3 70 50
D4M23 4 44 20
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