OAKL to the Browser
Working in Rmd, here is getting some DMLs into IGV format. TLDR - bedfile
Methylkit-02
Now I need to download the files
curl -O http://owl.fish.washington.edu/halfshell/bu-serine-wd/18-04-29/zr2096_[1-10]_dedup.sorted.bam
These were generated in Jupyter like:
%%bash
find /Volumes/Serine/wd/18-04-27/zr2096_*R1* \
| xargs basename -s _s1_R1_val_1.fq.gz | xargs -I{} /Applications/bioinfo/Bismark_v0.19.0/bismark \
--path_to_bowtie /Applications/bioinfo/bowtie2-2.3.4.1-macos-x86_64 \
--genome /Volumes/Serine/wd/18-03-15/genome \
--score_min L,0,-1.2 \
-p 4 \
--non_directional \
-1 /Volumes/Serine/wd/18-04-27/{}_s1_R1_val_1.fq.gz \
-2 /Volumes/Serine/wd/18-04-27/{}_s1_R2_val_2.fq.gz \
2> bismark.err
%%bash
/Applications/bioinfo/Bismark_v0.19.0/deduplicate_bismark \
--bam -p \
*.bam \
2> dedup.err
%%bash
find *deduplicated.bam \
| xargs basename -s _s1_R1_val_1_bismark_bt2_pe.deduplicated.bam | xargs -I{} /Applications/bioinfo/samtools-1.3.1/samtools \
sort {}_s1_R1_val_1_bismark_bt2_pe.deduplicated.bam -o {}_dedup.sorted.bam
Reading in some files:
file.list=list( '/Users/sr320/Desktop/oakl/zr2096_1_dedup.sorted.bam',
'/Users/sr320/Desktop/oakl/zr2096_2_dedup.sorted.bam',
'/Users/sr320/Desktop/oakl/zr2096_3_dedup.sorted.bam',
'/Users/sr320/Desktop/oakl/zr2096_4_dedup.sorted.bam',
'/Users/sr320/Desktop/oakl/zr2096_5_dedup.sorted.bam',
'/Users/sr320/Desktop/oakl/zr2096_6_dedup.sorted.bam',
'/Users/sr320/Desktop/oakl/zr2096_7_dedup.sorted.bam',
'/Users/sr320/Desktop/oakl/zr2096_8_dedup.sorted.bam',
'/Users/sr320/Desktop/oakl/zr2096_9_dedup.sorted.bam',
'/Users/sr320/Desktop/oakl/zr2096_10_dedup.sorted.bam'
)
Bringing in bam files, setting context, AND coverage
myobj = processBismarkAln(location = file.list, sample.id = list("1","2","3","4","5","6","7","8","9","10"), assembly = "v3", read.context="CpG", mincov=10, treatment = c(0,0,0,0,0,1,1,1,1,1))
save(myobj, file = "../analyses/myobj_180427files")
load("../analyses/myobj_180427files")
getCoverageStats(myobj[[4]],plot=TRUE,both.strands=FALSE)
getMethylationStats(myobj[[1]],plot=FALSE,both.strands=FALSE)
## methylation statistics per base
## summary:
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.00 83.33 93.33 85.11 100.00 100.00
## percentiles:
## 0% 10% 20% 30% 40% 50% 60%
## 0.00000 55.55556 80.00000 85.71429 90.47619 93.33333 96.29630
## 70% 80% 90% 95% 99% 99.5% 99.9%
## 100.00000 100.00000 100.00000 100.00000 100.00000 100.00000 100.00000
## 100%
## 100.00000
getCoverageStats(myobj[[4]],plot=TRUE,both.strands=FALSE)
meth=unite(myobj)
getCorrelation(meth,plot=TRUE)
## 1 2 3 4 5 6 7
## 1 1.0000000 0.4486002 0.4560082 0.4404980 0.4331196 0.4820232 0.4782540
## 2 0.4486002 1.0000000 0.5205769 0.5071152 0.4994732 0.4561182 0.5355796
## 3 0.4560082 0.5205769 1.0000000 0.5078281 0.5042024 0.4610765 0.5485566
## 4 0.4404980 0.5071152 0.5078281 1.0000000 0.4999247 0.4532686 0.5325240
## 5 0.4331196 0.4994732 0.5042024 0.4999247 1.0000000 0.4484705 0.5300285
## 6 0.4820232 0.4561182 0.4610765 0.4532686 0.4484705 1.0000000 0.5713013
## 7 0.4782540 0.5355796 0.5485566 0.5325240 0.5300285 0.5713013 1.0000000
## 8 0.4427913 0.5140576 0.5175793 0.5032337 0.4955144 0.4546524 0.5355500
## 9 0.4579275 0.5216281 0.5311598 0.5135430 0.5025602 0.4660443 0.5469018
## 10 0.4309082 0.5077382 0.5148965 0.5017601 0.4975297 0.4342481 0.5280633
## 8 9 10
## 1 0.4427913 0.4579275 0.4309082
## 2 0.5140576 0.5216281 0.5077382
## 3 0.5175793 0.5311598 0.5148965
## 4 0.5032337 0.5135430 0.5017601
## 5 0.4955144 0.5025602 0.4975297
## 6 0.4546524 0.4660443 0.4342481
## 7 0.5355500 0.5469018 0.5280633
## 8 1.0000000 0.5192701 0.4981650
## 9 0.5192701 1.0000000 0.5222376
## 10 0.4981650 0.5222376 1.0000000
clusterSamples(meth, dist="correlation", method="ward", plot=TRUE)
## The "ward" method has been renamed to "ward.D"; note new "ward.D2"
##
## Call:
## hclust(d = d, method = HCLUST.METHODS[hclust.method])
##
## Cluster method : ward.D
## Distance : pearson
## Number of objects: 10
PCASamples(meth, screeplot=TRUE)
myDiff=calculateDiffMeth(meth)
## two groups detected:
## will calculate methylation difference as the difference of
## treatment (group: 1) - control (group: 0)
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: algorithm did not converge
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: algorithm did not converge
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: algorithm did not converge
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
myDiff50p=getMethylDiff(myDiff,difference=50,qvalue=0.01)
myDiff50p
## chr start end strand pvalue qvalue
## 677 NC_035780.1 346073 346073 - 2.658918e-24 3.403025e-22
## 2364 NC_035780.1 990997 990997 - 2.731237e-29 5.781425e-27
## 2834 NC_035780.1 1959000 1959000 - 3.962712e-85 3.474108e-81
## 3329 NC_035780.1 2541728 2541728 - 1.177599e-26 1.908906e-24
## 3698 NC_035780.1 2584493 2584493 + 6.347756e-56 1.165188e-52
## 3727 NC_035780.1 2586510 2586510 - 1.060224e-35 3.983563e-33
## 3739 NC_035780.1 2588795 2588795 + 1.412833e-74 7.250515e-71
## 3740 NC_035780.1 2588796 2588796 - 2.118407e-43 1.553064e-40
## 3750 NC_035780.1 2589722 2589722 - 2.915792e-14 1.093788e-12
## 4576 NC_035780.1 4286287 4286287 + 1.761183e-82 1.277817e-78
## 4585 NC_035780.1 4288214 4288214 + 2.525530e-25 3.563994e-23
## 7788 NC_035780.1 15389759 15389759 - 1.340609e-25 1.944002e-23
## 8149 NC_035780.1 15534532 15534532 + 1.422063e-56 2.849650e-53
## 9283 NC_035780.1 17500582 17500582 + 2.234699e-57 4.609786e-54
## 10727 NC_035780.1 19482570 19482570 - 1.500898e-53 2.288412e-50
## 13384 NC_035780.1 21941412 21941412 - 6.151680e-77 3.498276e-73
## 14277 NC_035780.1 23288707 23288707 + 1.036531e-25 1.519820e-23
## 15236 NC_035780.1 24245856 24245856 - 5.945674e-30 1.340854e-27
## 16189 NC_035780.1 25201661 25201661 - 5.673392e-36 2.198391e-33
## 16404 NC_035780.1 25437703 25437703 + 1.537943e-41 9.746847e-39
## 16504 NC_035780.1 25858299 25858299 - 1.189348e-26 1.924986e-24
## 18541 NC_035780.1 26637856 26637856 - 1.110870e-64 3.710091e-61
## 19466 NC_035780.1 27396184 27396184 - 4.156354e-28 7.871555e-26
## 20393 NC_035780.1 28493521 28493521 - 1.023069e-27 1.849329e-25
## 20625 NC_035780.1 28739458 28739458 + 4.339304e-48 4.207483e-45
## 20629 NC_035780.1 28739473 28739473 + 3.458688e-59 7.825109e-56
## 20630 NC_035780.1 28739474 28739474 - 8.600582e-50 9.781785e-47
## 22477 NC_035780.1 31303160 31303160 + 9.360813e-28 1.699386e-25
## 22482 NC_035780.1 31303208 31303208 + 8.217262e-42 5.352869e-39
## 23488 NC_035780.1 32447268 32447268 + 1.315527e-27 2.342168e-25
## 23680 NC_035780.1 32698174 32698174 + 4.772501e-28 8.973831e-26
## 23757 NC_035780.1 32704774 32704774 + 6.079553e-18 3.751278e-16
## 23794 NC_035780.1 32717031 32717031 + 4.910371e-28 9.224828e-26
## 23935 NC_035780.1 32781382 32781382 + 4.725453e-33 1.396450e-30
## 23936 NC_035780.1 32781383 32781383 - 4.396936e-27 7.448873e-25
## 24023 NC_035780.1 32787978 32787978 - 1.104950e-40 6.567518e-38
## 24580 NC_035780.1 33209728 33209728 - 1.496176e-22 1.558451e-20
## 26267 NC_035780.1 38085932 38085932 + 7.664890e-25 1.032492e-22
## 26769 NC_035780.1 39872842 39872842 + 4.816855e-55 8.173421e-52
## 26770 NC_035780.1 39872843 39872843 - 2.473306e-31 6.315572e-29
## 26841 NC_035780.1 39890298 39890298 + 5.830127e-27 9.751229e-25
## 30905 NC_035780.1 48579390 48579390 - 2.042457e-42 1.390774e-39
## 31771 NC_035780.1 54211053 54211053 + 3.156324e-34 1.034448e-31
## 31772 NC_035780.1 54211054 54211054 - 1.833263e-32 5.082121e-30
## 32478 NC_035780.1 55378083 55378083 + 2.398040e-21 2.189009e-19
## 34197 NC_035780.1 58135769 58135769 - 3.547089e-37 1.548414e-34
## 35498 NC_035780.1 60359487 60359487 + 5.479159e-87 5.012427e-83
## 35499 NC_035780.1 60359488 60359488 - 5.705224e-54 9.094122e-51
## 36337 NC_035780.1 61420662 61420662 - 3.078850e-19 2.199709e-17
## 36931 NC_035780.1 62750218 62750218 + 4.618934e-37 2.003835e-34
## 37651 NC_035780.1 63619402 63619402 + 1.922326e-35 7.046558e-33
## 39044 NC_035781.1 627421 627421 + 5.652169e-25 7.737546e-23
## 39153 NC_035781.1 631900 631900 + 1.703347e-20 1.413797e-18
## 39154 NC_035781.1 631901 631901 - 2.376178e-28 4.603743e-26
## 40929 NC_035781.1 1680603 1680603 + 4.020120e-23 4.520924e-21
## 41205 NC_035781.1 2277405 2277405 + 1.283425e-57 2.727704e-54
## 43115 NC_035781.1 3401690 3401690 - 6.930542e-45 5.544641e-42
## 46173 NC_035781.1 5648773 5648773 - 3.565842e-64 1.154279e-60
## 46593 NC_035781.1 5855169 5855169 - 1.866491e-63 5.861558e-60
## 48703 NC_035781.1 9369564 9369564 + 3.682392e-27 6.258515e-25
## 49787 NC_035781.1 10383012 10383012 - 7.984320e-37 3.393866e-34
## 49838 NC_035781.1 10426303 10426303 + 2.064579e-115 5.212371e-111
## 49862 NC_035781.1 10427420 10427420 + 7.264465e-53 1.032771e-49
## 49871 NC_035781.1 10427643 10427643 + 5.208414e-56 9.872895e-53
## 50894 NC_035781.1 11919273 11919273 + 7.975521e-22 7.673125e-20
## 50940 NC_035781.1 11960874 11960874 - 3.324978e-68 1.371768e-64
## 51560 NC_035781.1 13033012 13033012 - 8.565343e-53 1.201477e-49
## 52473 NC_035781.1 13841609 13841609 + 1.047258e-41 6.697610e-39
## 53501 NC_035781.1 15604575 15604575 + 1.379211e-66 5.091172e-63
## 54080 NC_035781.1 19453326 19453326 - 1.502676e-26 2.398899e-24
## 55540 NC_035781.1 20620125 20620125 - 1.024992e-24 1.359813e-22
## 57179 NC_035781.1 22901074 22901074 - 2.559524e-47 2.393529e-44
## 57545 NC_035781.1 23710327 23710327 + 4.724519e-24 5.892567e-22
## 57573 NC_035781.1 24047932 24047932 - 2.017265e-19 1.474804e-17
## 58598 NC_035781.1 26609798 26609798 - 2.927812e-61 7.700433e-58
## 59827 NC_035781.1 29401028 29401028 + 1.898658e-18 1.241817e-16
## 60837 NC_035781.1 29991127 29991127 - 3.582980e-40 2.010366e-37
## 61103 NC_035781.1 30153251 30153251 + 4.568087e-43 3.269257e-40
## 61104 NC_035781.1 30153252 30153252 - 5.459769e-96 7.658523e-92
## 61747 NC_035781.1 30488985 30488985 + 1.837270e-41 1.153958e-38
## 63331 NC_035781.1 32146060 32146060 + 1.130574e-34 3.899700e-32
## 66631 NC_035781.1 40747578 40747578 + 6.560384e-40 3.576053e-37
## 68399 NC_035781.1 42529449 42529449 + 3.953855e-21 3.525094e-19
## 68646 NC_035781.1 43054124 43054124 - 4.576343e-25 6.318232e-23
## 68979 NC_035781.1 45110045 45110045 - 1.786608e-54 2.959971e-51
## 68984 NC_035781.1 45110114 45110114 - 2.410425e-91 3.169827e-87
## 68985 NC_035781.1 45110121 45110121 - 3.101970e-76 1.717576e-72
## 70629 NC_035781.1 52592743 52592743 + 1.226566e-35 4.592157e-33
## 70630 NC_035781.1 52592744 52592744 - 6.766249e-118 2.033817e-113
## 70636 NC_035781.1 52592761 52592761 - 1.242581e-79 8.170278e-76
## 71869 NC_035781.1 52956462 52956462 + 1.855078e-68 8.131731e-65
## 72147 NC_035781.1 53358701 53358701 - 7.385927e-36 2.825558e-33
## 72149 NC_035781.1 53358850 53358850 - 1.011204e-22 1.076202e-20
## 72164 NC_035781.1 53361156 53361156 + 2.396023e-26 3.745484e-24
## 72175 NC_035781.1 53364502 53364502 + 3.275649e-21 2.941623e-19
## 72176 NC_035781.1 53364503 53364503 - 7.071914e-36 2.715304e-33
## 72184 NC_035781.1 53364617 53364617 + 1.514379e-29 3.278161e-27
## 72211 NC_035781.1 53371081 53371081 + 6.364924e-17 3.447579e-15
## 72263 NC_035781.1 53385564 53385564 - 6.513187e-29 1.329220e-26
## 74940 NC_035781.1 54799287 54799287 + 6.125355e-50 7.120569e-47
## 74941 NC_035781.1 54799288 54799288 - 2.192895e-39 1.142085e-36
## 75217 NC_035781.1 56296257 56296257 + 8.271508e-24 1.003685e-21
## 75260 NC_035781.1 56595192 56595192 + 8.150144e-21 6.985151e-19
## 76886 NC_035781.1 59274790 59274790 - 2.521672e-33 7.590554e-31
## 76890 NC_035781.1 59274912 59274912 + 3.648696e-36 1.445790e-33
## 77258 NC_035781.1 59602904 59602904 - 1.586418e-107 3.034499e-103
## 77262 NC_035781.1 59604047 59604047 - 1.568595e-36 6.509758e-34
## 77438 NC_035781.1 59696863 59696863 + 2.808784e-25 3.939935e-23
## 77450 NC_035781.1 59697601 59697601 - 6.188878e-21 5.389854e-19
## 77529 NC_035781.1 59716718 59716718 + 1.484761e-44 1.152788e-41
## 77536 NC_035781.1 59717178 59717178 + 8.296425e-49 8.641748e-46
## 79111 NC_035782.1 6260448 6260448 + 5.622319e-31 1.390106e-28
## 79276 NC_035782.1 6686536 6686536 + 3.641807e-42 2.424889e-39
## 79294 NC_035782.1 6690565 6690565 + 2.867549e-87 2.873119e-83
## 80140 NC_035782.1 6897408 6897408 - 7.098967e-25 9.593312e-23
## 80589 NC_035782.1 8707638 8707638 + 1.610468e-35 5.976282e-33
## 81906 NC_035782.1 12237055 12237055 - 5.630672e-19 3.903584e-17
## 82324 NC_035782.1 13869669 13869669 + 2.643766e-45 2.207417e-42
## 82326 NC_035782.1 13869680 13869680 + 2.121359e-48 2.125479e-45
## 82841 NC_035782.1 15148527 15148527 + 5.637013e-19 3.906693e-17
## 84948 NC_035782.1 20856835 20856835 - 2.160229e-35 7.891134e-33
## 88238 NC_035782.1 22559285 22559285 - 6.667144e-49 7.018221e-46
## 88761 NC_035782.1 22960248 22960248 - 3.746399e-30 8.633865e-28
## 90375 NC_035782.1 25062577 25062577 + 3.412038e-18 2.163060e-16
## 90544 NC_035782.1 26645486 26645486 + 1.332142e-21 1.249079e-19
## 91288 NC_035782.1 29947819 29947819 + 2.306597e-20 1.886960e-18
## 92246 NC_035782.1 33020492 33020492 - 1.282104e-35 4.783063e-33
## 94627 NC_035782.1 34498894 34498894 + 1.637500e-29 3.526540e-27
## 94628 NC_035782.1 34498896 34498896 + 2.990900e-44 2.296748e-41
## 97327 NC_035782.1 37370862 37370862 - 3.470606e-57 7.089737e-54
## 97329 NC_035782.1 37370874 37370874 - 2.410235e-40 1.385608e-37
## 97366 NC_035782.1 37843187 37843187 - 4.262797e-40 2.360332e-37
## 98965 NC_035782.1 41156867 41156867 - 3.696514e-20 2.950590e-18
## 99253 NC_035782.1 41847825 41847825 - 3.847490e-36 1.515997e-33
## 99880 NC_035782.1 45857197 45857197 - 5.906739e-24 7.285020e-22
## 100040 NC_035782.1 46212750 46212750 - 9.557692e-35 3.313037e-32
## 100221 NC_035782.1 46475862 46475862 + 3.177230e-30 7.403258e-28
## 102518 NC_035782.1 49575758 49575758 - 6.338053e-28 1.172890e-25
## 103541 NC_035782.1 50620242 50620242 - 1.393761e-20 1.166501e-18
## 104280 NC_035782.1 51594720 51594720 - 1.711929e-48 1.748560e-45
## 106247 NC_035782.1 53681703 53681703 + 4.737861e-108 9.968833e-104
## 106248 NC_035782.1 53681704 53681704 - 4.781056e-47 4.336085e-44
## 108941 NC_035782.1 57058466 57058466 - 1.399815e-19 1.042592e-17
## 109796 NC_035782.1 58675270 58675270 + 1.016514e-32 2.894216e-30
## 110187 NC_035782.1 58948372 58948372 - 3.093130e-33 9.231473e-31
## 113079 NC_035782.1 63514945 63514945 + 6.490132e-52 8.534844e-49
## 114149 NC_035782.1 64758096 64758096 + 1.693195e-35 6.261189e-33
## 114150 NC_035782.1 64758097 64758097 - 1.201373e-27 2.154974e-25
## 114364 NC_035782.1 64881415 64881415 + 6.654709e-34 2.121520e-31
## 121016 NC_035783.1 2891929 2891929 + 8.540456e-22 8.190425e-20
## 121236 NC_035783.1 4336101 4336101 + 2.393075e-25 3.381611e-23
## 121844 NC_035783.1 6430848 6430848 + 9.449201e-42 6.080080e-39
## 123743 NC_035783.1 10907089 10907089 + 3.012784e-91 3.728903e-87
## 127415 NC_035783.1 15005745 15005745 - 6.935163e-65 2.392152e-61
## 128000 NC_035783.1 16217948 16217948 - 3.856933e-21 3.443059e-19
## 128301 NC_035783.1 16810366 16810366 + 3.914332e-45 3.179947e-42
## 130596 NC_035783.1 18125850 18125850 + 1.602881e-62 4.750125e-59
## 130873 NC_035783.1 18412976 18412976 + 8.593488e-20 6.589423e-18
## 132517 NC_035783.1 19526094 19526094 - 2.176185e-39 1.139021e-36
## 132784 NC_035783.1 19556698 19556698 - 4.891592e-34 1.583430e-31
## 136680 NC_035783.1 20719352 20719352 + 2.947383e-34 9.720259e-32
## 136932 NC_035783.1 20753581 20753581 - 2.050854e-24 2.640855e-22
## 137735 NC_035783.1 20844475 20844475 + 6.690171e-50 7.650351e-47
## 137887 NC_035783.1 20856442 20856442 - 7.220329e-36 2.767239e-33
## 138382 NC_035783.1 20908985 20908985 - 1.372066e-47 1.306305e-44
## 138580 NC_035783.1 20953373 20953373 + 2.408166e-126 8.444951e-122
## 138581 NC_035783.1 20953374 20953374 - 1.749637e-48 1.778441e-45
## 138643 NC_035783.1 20963956 20963956 + 1.540060e-17 9.013650e-16
## 138940 NC_035783.1 21066969 21066969 + 1.593623e-71 7.451350e-68
## 138941 NC_035783.1 21066970 21066970 - 4.763548e-41 2.905183e-38
## 138942 NC_035783.1 21066995 21066995 + 2.403478e-97 3.612219e-93
## 138943 NC_035783.1 21066996 21066996 - 3.185999e-49 3.491455e-46
## 139015 NC_035783.1 21071070 21071070 + 3.044965e-62 8.657900e-59
## 139086 NC_035783.1 21073268 21073268 - 1.368385e-48 1.404483e-45
## 139127 NC_035783.1 21076422 21076422 - 3.299692e-29 6.908271e-27
## 139136 NC_035783.1 21076507 21076507 + 1.996555e-60 4.884779e-57
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## 139695 NC_035783.1 23527093 23527093 + 3.180550e-45 2.614112e-42
## 140002 NC_035783.1 23693497 23693497 + 3.430496e-28 6.567821e-26
## 140110 NC_035783.1 23889432 23889432 + 4.252729e-42 2.813861e-39
## 140219 NC_035783.1 23921625 23921625 + 1.183910e-16 6.146164e-15
## 141159 NC_035783.1 25301968 25301968 + 1.325489e-32 3.753611e-30
## 141200 NC_035783.1 25307879 25307879 + 5.345963e-50 6.249070e-47
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## 142908 NC_035783.1 32082627 32082627 + 1.558239e-33 4.800377e-31
## 142963 NC_035783.1 32197766 32197766 - 2.268598e-17 1.299567e-15
## 143044 NC_035783.1 32417240 32417240 - 9.712676e-43 6.812078e-40
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## 147327 NC_035783.1 42295608 42295608 + 4.654966e-52 6.238481e-49
## 148457 NC_035783.1 45068803 45068803 + 6.413415e-32 1.714655e-29
## 148458 NC_035783.1 45068804 45068804 - 4.381474e-19 3.068897e-17
## 148988 NC_035783.1 45436572 45436572 - 2.233416e-65 7.832139e-62
## 150110 NC_035783.1 46125340 46125340 - 8.328756e-35 2.906195e-32
## 150654 NC_035783.1 47273230 47273230 + 4.372906e-18 2.736745e-16
## 150655 NC_035783.1 47273231 47273231 - 8.777753e-45 6.891449e-42
## 151588 NC_035783.1 48434287 48434287 + 2.117680e-22 2.162993e-20
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## 157293 NC_035784.1 1005579 1005579 - 1.156008e-72 5.581151e-69
## 157505 NC_035784.1 1046256 1046256 + 6.536964e-32 1.745468e-29
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## 159355 NC_035784.1 2340024 2340024 + 8.866231e-40 4.783397e-37
## 159439 NC_035784.1 2348439 2348439 + 8.857200e-51 1.083503e-47
## 159485 NC_035784.1 2350203 2350203 - 7.342595e-38 3.373231e-35
## 159695 NC_035784.1 2443681 2443681 - 5.171748e-36 2.011417e-33
## 159959 NC_035784.1 2777423 2777423 + 5.327754e-56 1.000894e-52
## 160330 NC_035784.1 3214006 3214006 + 1.580294e-57 3.325063e-54
## 161194 NC_035784.1 3912437 3912437 - 7.102157e-78 4.150972e-74
## 162080 NC_035784.1 7656221 7656221 + 1.975821e-34 6.641028e-32
## 162626 NC_035784.1 8045506 8045506 + 1.302983e-16 6.724502e-15
## 164573 NC_035784.1 10016146 10016146 - 2.569318e-38 1.251400e-35
## 166794 NC_035784.1 13485221 13485221 + 2.674035e-36 1.077850e-33
## 168963 NC_035784.1 19648288 19648288 - 8.751045e-29 1.767072e-26
## 170678 NC_035784.1 27176372 27176372 + 3.870284e-55 6.674904e-52
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## 173841 NC_035784.1 36650542 36650542 - 4.080723e-28 7.756245e-26
## 174140 NC_035784.1 36797030 36797030 + 6.963609e-29 1.417019e-26
## 174141 NC_035784.1 36797031 36797031 - 2.198666e-30 5.186286e-28
## 176356 NC_035784.1 38226016 38226016 + 1.008509e-41 6.469461e-39
## 178861 NC_035784.1 42036909 42036909 + 2.669766e-56 5.201294e-53
## 179311 NC_035784.1 43356402 43356402 - 9.449414e-25 1.259969e-22
## 182037 NC_035784.1 45667414 45667414 - 1.562080e-19 1.157710e-17
## 183909 NC_035784.1 47479565 47479565 + 3.297789e-21 2.960243e-19
## 186158 NC_035784.1 50724129 50724129 - 1.030808e-19 7.815860e-18
## 187151 NC_035784.1 52291765 52291765 - 8.234357e-201 1.732574e-195
## 187153 NC_035784.1 52291781 52291781 - 6.102143e-148 6.419695e-143
## 187245 NC_035784.1 52581120 52581120 + 1.460138e-21 1.363019e-19
## 187246 NC_035784.1 52581121 52581121 - 5.937973e-54 9.393957e-51
## 187266 NC_035784.1 52581363 52581363 + 7.967674e-66 2.841460e-62
## 187267 NC_035784.1 52581364 52581364 - 2.309376e-33 7.001597e-31
## 189739 NC_035784.1 53282858 53282858 + 4.418814e-56 8.529846e-53
## 190488 NC_035784.1 53515950 53515950 + 4.932795e-15 2.065470e-13
## 191247 NC_035784.1 53991052 53991052 + 2.423737e-20 1.978942e-18
## 191514 NC_035784.1 54028110 54028110 - 2.326770e-27 4.019464e-25
## 192152 NC_035784.1 54639923 54639923 + 2.301229e-27 3.978609e-25
## 192153 NC_035784.1 54639924 54639924 - 1.301027e-39 6.965554e-37
## 193010 NC_035784.1 55154350 55154350 + 1.145187e-35 4.295122e-33
## 193012 NC_035784.1 55154408 55154408 + 9.472545e-36 3.578273e-33
## 193890 NC_035784.1 57133704 57133704 + 5.700427e-36 2.204807e-33
## 194523 NC_035784.1 57514694 57514694 - 1.661322e-39 8.804916e-37
## 194525 NC_035784.1 57514701 57514701 - 7.577121e-31 1.849520e-28
## 194734 NC_035784.1 57785891 57785891 - 2.224820e-52 3.020127e-49
## 195142 NC_035784.1 58128163 58128163 - 1.667867e-31 4.300642e-29
## 195180 NC_035784.1 58132916 58132916 + 8.116431e-20 6.237257e-18
## 195917 NC_035784.1 58834474 58834474 + 1.529437e-45 1.297604e-42
## 196178 NC_035784.1 59002732 59002732 + 9.217458e-25 1.230600e-22
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## 196810 NC_035784.1 59679679 59679679 + 1.972460e-29 4.221985e-27
## 196811 NC_035784.1 59679680 59679680 - 7.747376e-33 2.242241e-30
## 197684 NC_035784.1 59987571 59987571 + 1.181676e-26 1.914041e-24
## 198015 NC_035784.1 60435135 60435135 + 4.903480e-41 2.981881e-38
## 198053 NC_035784.1 60466859 60466859 + 1.009322e-18 6.797993e-17
## 198542 NC_035784.1 60893577 60893577 - 3.948002e-35 1.412739e-32
## 198670 NC_035784.1 61208184 61208184 + 2.420015e-32 6.656080e-30
## 200203 NC_035784.1 63839519 63839519 - 3.993501e-20 3.172005e-18
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## 206694 NC_035784.1 67991199 67991199 + 8.099492e-88 8.520985e-84
## 206695 NC_035784.1 67991200 67991200 - 7.629984e-58 1.655060e-54
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## 210454 NC_035784.1 74882674 74882674 + 6.652765e-24 8.143073e-22
## 212585 NC_035784.1 79434488 79434488 + 1.223315e-24 1.612946e-22
## 212590 NC_035784.1 79434840 79434840 - 4.927058e-52 6.561340e-49
## 212722 NC_035784.1 79536518 79536518 - 2.919664e-33 8.751001e-31
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## 213126 NC_035784.1 79841227 79841227 + 8.679293e-35 3.023496e-32
## 213127 NC_035784.1 79841228 79841228 - 6.332794e-67 2.379410e-63
## 213328 NC_035784.1 80205206 80205206 - 1.202680e-25 1.753662e-23
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## 215424 NC_035784.1 83406913 83406913 - 1.846599e-35 6.796522e-33
## 215966 NC_035784.1 84939270 84939270 + 9.236344e-39 4.649281e-36
## 215973 NC_035784.1 84951458 84951458 + 6.614667e-29 1.348622e-26
## 218093 NC_035784.1 87733520 87733520 + 1.376148e-84 1.072416e-80
## 218313 NC_035784.1 87914757 87914757 + 5.254276e-15 2.193453e-13
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## 219310 NC_035784.1 90135107 90135107 - 4.689294e-22 4.612737e-20
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## 219795 NC_035784.1 90909623 90909623 + 3.952059e-39 2.023222e-36
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## 222930 NC_035784.1 95099423 95099423 + 7.351917e-22 7.095877e-20
## 223008 NC_035784.1 96023006 96023006 + 3.402437e-59 7.781516e-56
## 223016 NC_035784.1 96023083 96023083 + 1.188683e-78 7.145950e-75
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## 228532 NC_035785.1 31237990 31237990 + 6.185207e-81 4.338055e-77
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## 264431 NC_035787.1 47493411 47493411 + 2.229543e-115 5.212371e-111
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## 267647 NC_035787.1 51474327 51474327 + 1.132755e-36 4.757297e-34
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## 267779 NC_035787.1 52112612 52112612 - 4.486074e-22 4.427323e-20
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## 268770 NC_035787.1 52849924 52849924 + 4.828238e-67 1.881295e-63
## 269671 NC_035787.1 53342425 53342425 + 9.076980e-51 1.103970e-47
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## 270436 NC_035787.1 55940976 55940976 + 4.853901e-17 2.670967e-15
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## 278555 NC_035787.1 72586550 72586550 - 8.597641e-26 1.268591e-23
## 280015 NC_035788.1 11932781 11932781 + 1.174948e-12 3.521629e-11
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## 280520 NC_035788.1 15837301 15837301 + 6.443840e-25 8.724804e-23
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## 285305 NC_035788.1 48509356 48509356 + 7.104725e-21 6.144225e-19
## 285392 NC_035788.1 48520659 48520659 + 2.330249e-53 3.477325e-50
## 285464 NC_035788.1 48523420 48523420 + 4.808241e-56 9.197197e-53
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## 289425 NC_035788.1 56054015 56054015 + 3.015174e-42 2.020434e-39
## 289426 NC_035788.1 56054016 56054016 - 9.376511e-49 9.671039e-46
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## 289670 NC_035788.1 56264622 56264622 + 3.212325e-29 6.732056e-27
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## 289688 NC_035788.1 56266322 56266322 - 4.288615e-39 2.179609e-36
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## 292864 NC_035788.1 65572755 65572755 + 2.936582e-29 6.191182e-27
## 292872 NC_035788.1 65573008 65573008 - 4.304575e-38 2.039902e-35
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## 296213 NC_035788.1 71239591 71239591 + 5.471647e-18 3.388104e-16
## 296242 NC_035788.1 71413851 71413851 - 2.106197e-10 4.383387e-09
## 296253 NC_035788.1 71422115 71422115 + 3.492635e-28 6.680707e-26
## 297650 NC_035788.1 75693191 75693191 - 8.561877e-29 1.730534e-26
## 297801 NC_035788.1 76059470 76059470 + 1.198637e-19 9.016900e-18
## 297802 NC_035788.1 76059473 76059473 + 1.507289e-40 8.809597e-38
## 298238 NC_035788.1 78353401 78353401 + 4.338051e-15 1.830279e-13
## 298838 NC_035788.1 80022878 80022878 - 5.513470e-48 5.297157e-45
## 298839 NC_035788.1 80022880 80022880 - 4.090328e-43 2.947388e-40
## 300204 NC_035788.1 83655136 83655136 - 4.115346e-87 3.935915e-83
## 303134 NC_035788.1 103039424 103039424 + 1.235714e-20 1.039185e-18
## 303145 NC_035788.1 103039558 103039558 - 2.161704e-22 2.202613e-20
## 304820 NC_035789.1 4864681 4864681 + 9.751803e-85 7.891755e-81
## 305346 NC_035789.1 6785228 6785228 - 2.544996e-17 1.447263e-15
## 305517 NC_035789.1 7302118 7302118 + 9.854916e-28 1.784468e-25
## 306681 NC_035789.1 9432287 9432287 + 3.866700e-53 5.689400e-50
## 306682 NC_035789.1 9432288 9432288 - 3.198947e-23 3.638290e-21
## 307034 NC_035789.1 10721394 10721394 + 1.143204e-30 2.752164e-28
## 307391 NC_035789.1 23133846 23133846 + 3.736213e-25 5.192396e-23
## meth.diff
## 677 50.94340
## 2364 -51.04327
## 2834 53.44908
## 3329 -58.87446
## 3698 56.30202
## 3727 -57.98357
## 3739 -51.26142
## 3740 -57.90305
## 3750 50.67921
## 4576 54.72824
## 4585 -56.60468
## 7788 -50.45581
## 8149 54.89699
## 9283 -52.65900
## 10727 73.04668
## 13384 -65.30107
## 14277 50.77611
## 15236 -55.11905
## 16189 59.24065
## 16404 -53.06410
## 16504 -50.89224
## 18541 -54.50835
## 19466 52.73983
## 20393 -53.83827
## 20625 59.61388
## 20629 73.76537
## 20630 64.47744
## 22477 -52.46206
## 22482 -57.45476
## 23488 58.97228
## 23680 51.19351
## 23757 54.45935
## 23794 -54.07179
## 23935 51.84397
## 23936 50.03210
## 24023 -57.16387
## 24580 57.90551
## 26267 51.13010
## 26769 51.99773
## 26770 52.95512
## 26841 52.49685
## 30905 -57.02739
## 31771 -61.19480
## 31772 -64.28571
## 32478 -51.23117
## 34197 74.08800
## 35498 73.46519
## 35499 68.02666
## 36337 51.81395
## 36931 53.24028
## 37651 54.38837
## 39044 -52.78862
## 39153 -51.80766
## 39154 -60.95939
## 40929 51.94070
## 41205 59.78931
## 43115 52.34680
## 46173 -51.50348
## 46593 -61.68569
## 48703 56.56687
## 49787 -56.78422
## 49838 55.80670
## 49862 59.01367
## 49871 63.83230
## 50894 -50.75362
## 50940 52.58382
## 51560 -63.40251
## 52473 54.39605
## 53501 55.02359
## 54080 -52.80849
## 55540 53.86765
## 57179 50.43153
## 57545 -53.07162
## 57573 53.33333
## 58598 -61.26814
## 59827 -55.95238
## 60837 -52.19021
## 61103 53.72999
## 61104 64.08109
## 61747 53.95518
## 63331 52.80055
## 66631 -51.11329
## 68399 -50.69810
## 68646 -64.60926
## 68979 53.99211
## 68984 64.53065
## 68985 63.59188
## 70629 55.69892
## 70630 56.11490
## 70636 50.22626
## 71869 -55.72453
## 72147 56.98053
## 72149 -57.57821
## 72164 -55.53066
## 72175 -58.25464
## 72176 -59.25373
## 72184 -60.00673
## 72211 -52.86325
## 72263 52.97447
## 74940 54.35520
## 74941 56.02357
## 75217 64.41540
## 75260 51.88079
## 76886 51.51943
## 76890 69.48392
## 77258 58.72517
## 77262 54.20875
## 77438 -53.99993
## 77450 53.36485
## 77529 61.65086
## 77536 54.86797
## 79111 -54.27998
## 79276 -52.52206
## 79294 -65.61384
## 80140 -60.64998
## 80589 50.11623
## 81906 -52.23906
## 82324 51.53972
## 82326 50.32554
## 82841 -63.34688
## 84948 -59.92459
## 88238 55.59165
## 88761 51.50855
## 90375 54.50150
## 90544 -50.79017
## 91288 51.22618
## 92246 55.71336
## 94627 -54.47522
## 94628 -72.11321
## 97327 73.51043
## 97329 74.40246
## 97366 -53.42770
## 98965 -50.46313
## 99253 -52.18182
## 99880 58.00575
## 100040 -53.08333
## 100221 51.31967
## 102518 -66.12882
## 103541 52.81395
## 104280 -59.10714
## 106247 -67.66955
## 106248 -67.85236
## 108941 50.90532
## 109796 51.18566
## 110187 -50.10628
## 113079 57.07200
## 114149 52.60471
## 114150 53.74182
## 114364 -50.40440
## 121016 53.69601
## 121236 63.34808
## 121844 -52.72579
## 123743 -50.12506
## 127415 -55.00503
## 128000 50.18433
## 128301 -62.28902
## 130596 -53.89898
## 130873 51.41973
## 132517 52.27396
## 132784 50.01571
## 136680 58.23718
## 136932 58.22724
## 137735 67.57964
## 137887 51.34173
## 138382 -55.99277
## 138580 53.00408
## 138581 56.57294
## 138643 54.82143
## 138940 57.88700
## 138941 53.47388
## 138942 63.71570
## 138943 58.52923
## 139015 54.31205
## 139086 -58.16191
## 139127 65.64341
## 139136 54.49055
## 139178 56.49756
## 139695 -51.42189
## 140002 -59.11489
## 140110 -61.16667
## 140219 53.00485
## 141159 -57.39008
## 141200 -72.12389
## 142465 54.79571
## 142908 -58.01519
## 142963 55.07003
## 143044 -60.97565
## 146511 50.96154
## 146977 51.07962
## 147327 -59.95403
## 148457 52.16018
## 148458 54.58333
## 148988 53.53083
## 150110 57.12876
## 150654 55.03071
## 150655 57.44298
## 151588 -57.77001
## 156696 -50.11687
## 156816 59.53624
## 156882 -65.24510
## 157293 57.13468
## 157505 -56.65267
## 158415 56.34738
## 158681 -62.49035
## 158710 51.74208
## 159095 -63.00665
## 159325 -59.92498
## 159355 -60.62009
## 159439 -60.03490
## 159485 -57.16685
## 159695 -54.94580
## 159959 -57.80114
## 160330 56.17387
## 161194 -64.35295
## 162080 53.40161
## 162626 -50.65524
## 164573 -56.68699
## 166794 55.94747
## 168963 57.35119
## 170678 -58.13427
## 172233 53.37813
## 172428 59.78534
## 173841 -55.53708
## 174140 -52.19282
## 174141 -59.73063
## 176356 62.07729
## 178861 51.88324
## 179311 -61.47751
## 182037 55.94429
## 183909 -50.37594
## 186158 52.28198
## 187151 64.14072
## 187153 54.28599
## 187245 -52.38961
## 187246 -52.80148
## 187266 -75.65022
## 187267 -68.59023
## 189739 50.68619
## 190488 50.56497
## 191247 -51.76288
## 191514 60.63987
## 192152 -51.73233
## 192153 -51.52164
## 193010 -58.81369
## 193012 -51.17107
## 193890 59.81555
## 194523 57.35516
## 194525 51.08881
## 194734 -55.89721
## 195142 -51.41949
## 195180 -51.45025
## 195917 -50.27778
## 196178 61.70722
## 196229 67.86164
## 196810 60.32476
## 196811 63.04585
## 197684 -51.55383
## 198015 -64.92072
## 198053 53.39217
## 198542 56.37678
## 198670 52.98686
## 200203 52.30589
## 206634 -57.16717
## 206694 56.34287
## 206695 69.20753
## 207194 -59.67169
## 210454 55.34894
## 212585 -57.63158
## 212590 -50.85063
## 212722 50.21400
## 213122 55.94705
## 213126 -55.31673
## 213127 -53.54567
## 213328 -50.54348
## 214512 -51.20690
## 215424 -51.52653
## 215966 50.05769
## 215973 -53.73411
## 218093 -61.34221
## 218313 51.49551
## 218712 -64.13814
## 219310 -52.67291
## 219311 -54.81687
## 219617 -65.16353
## 219795 -74.76383
## 219796 -59.77553
## 220702 -50.00878
## 222930 54.76629
## 223008 -56.62279
## 223016 60.73899
## 223140 51.38274
## 224050 -63.63636
## 224656 -51.10902
## 225413 63.56600
## 226313 60.07357
## 228349 53.88140
## 228532 55.32544
## 230118 -59.63069
## 230299 59.87403
## 231895 52.15686
## 231961 -54.58120
## 236412 52.17918
## 236413 57.15486
## 236419 50.20635
## 239594 -60.78519
## 240401 -61.36364
## 242255 55.10723
## 242494 -59.20379
## 243041 -50.34792
## 243083 55.94937
## 243084 58.80736
## 243143 71.45428
## 243256 -58.04344
## 243258 -52.05639
## 243283 50.70286
## 244169 -51.36836
## 245336 -56.40271
## 245337 63.66714
## 245718 -50.67791
## 245838 -59.91674
## 246107 53.03618
## 246252 51.44439
## 252748 59.01624
## 253880 55.82944
## 254551 -51.94497
## 255133 54.69086
## 255525 53.21802
## 255584 -51.65707
## 255991 -55.16576
## 256275 -71.37716
## 257871 52.38176
## 259029 54.29802
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## 260543 60.84991
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## 278206 -64.27277
## 278555 50.22791
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## 280078 53.14266
## 280106 -63.33333
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## 281413 -53.39553
## 281964 56.03104
## 282796 50.46366
## 283584 -56.74397
## 284622 63.79478
## 284623 52.00219
## 284666 56.50932
## 285305 -54.51744
## 285392 53.57011
## 285464 66.37443
## 285812 55.14231
## 285827 54.06351
## 286208 -53.25819
## 286209 51.24229
## 286757 57.96778
## 286928 -50.83367
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## 289688 52.07270
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## 289960 -50.63495
## 291622 61.28207
## 292344 -68.16093
## 292864 52.24431
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## 293396 59.95917
## 293564 55.66343
## 294054 -51.66667
## 295274 -50.99469
## 295277 63.55876
## 295295 54.88445
## 295696 50.21260
## 295783 67.52190
## 296213 54.01989
## 296242 -50.22260
## 296253 -64.40139
## 297650 51.34788
## 297801 -50.97781
## 297802 -69.32515
## 298238 -52.51647
## 298838 56.15201
## 298839 54.99525
## 300204 60.75166
## 303134 -52.40113
## 303145 53.88199
## 304820 66.54924
## 305346 52.17822
## 305517 -54.94260
## 306681 -56.70921
## 306682 -53.53965
## 307034 56.24641
## 307391 -52.61376
write.table(myDiff50p, file = "../analyses/myDiff50p.tab", sep = "\t")
Taking the DMLs to a bed
library(readr)
myDiff50p <- read_csv("../analyses/myDiff50p.csv")
## Warning: Missing column names filled in: 'X1' [1]
## Parsed with column specification:
## cols(
## X1 = col_integer(),
## chr = col_character(),
## start = col_integer(),
## end = col_integer(),
## strand = col_character(),
## pvalue = col_double(),
## qvalue = col_double(),
## meth.diff = col_double()
## )
head(myDiff50p)
## # A tibble: 6 x 8
## X1 chr start end strand pvalue qvalue meth.diff
## <int> <chr> <int> <int> <chr> <dbl> <dbl> <dbl>
## 1 677 NC_035780.1 346073 346073 - 2.66e-24 3.40e-22 50.9
## 2 2364 NC_035780.1 990997 990997 - 2.73e-29 5.78e-27 -51.0
## 3 2834 NC_035780.1 1959000 1959000 - 3.96e-85 3.47e-81 53.4
## 4 3329 NC_035780.1 2541728 2541728 - 1.18e-26 1.91e-24 -58.9
## 5 3698 NC_035780.1 2584493 2584493 + 6.35e-56 1.17e-52 56.3
## 6 3727 NC_035780.1 2586510 2586510 - 1.06e-35 3.98e-33 -58.0
library(tidyverse)
## ── Attaching packages ──────────────────────────────────────────────────────────────────────────────────────────── tidyverse 1.2.1 ──
## ✔ ggplot2 2.2.1 ✔ purrr 0.2.4
## ✔ tibble 1.4.2 ✔ dplyr 0.7.4
## ✔ tidyr 0.8.0 ✔ stringr 1.3.1
## ✔ ggplot2 2.2.1 ✔ forcats 0.3.0
## ── Conflicts ─────────────────────────────────────────────────────────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::collapse() masks IRanges::collapse()
## ✖ dplyr::combine() masks BiocGenerics::combine()
## ✖ dplyr::desc() masks IRanges::desc()
## ✖ tidyr::expand() masks S4Vectors::expand()
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::first() masks S4Vectors::first()
## ✖ dplyr::lag() masks stats::lag()
## ✖ ggplot2::Position() masks BiocGenerics::Position(), base::Position()
## ✖ purrr::reduce() masks GenomicRanges::reduce(), IRanges::reduce()
## ✖ dplyr::rename() masks S4Vectors::rename()
## ✖ dplyr::select() masks methylKit::select()
## ✖ dplyr::slice() masks IRanges::slice()
## ✖ tidyr::unite() masks methylKit::unite()
dml05251200plus <- filter(myDiff50p, strand == "+") %>% mutate(start = start -1, end = end + 1) %>% select(chr, start, end, strand, meth.diff)
## Warning: package 'bindrcpp' was built under R version 3.4.4
dml05251200minus <- filter(myDiff50p, strand == "-") %>% mutate(start = start -2) %>% select(chr, start, end, strand, meth.diff)
dml05251200.bed <- bind_rows(dml05251200plus, dml05251200minus) %>% arrange(chr, start) %>%
mutate_if(is.numeric, as.integer)
#latter was done to refrain from writing as scientific notation
dml05251200.bed
## # A tibble: 422 x 5
## chr start end strand meth.diff
## <chr> <int> <int> <chr> <int>
## 1 NC_035780.1 346071 346073 - 50
## 2 NC_035780.1 990995 990997 - -51
## 3 NC_035780.1 1958998 1959000 - 53
## 4 NC_035780.1 2541726 2541728 - -58
## 5 NC_035780.1 2584492 2584494 + 56
## 6 NC_035780.1 2586508 2586510 - -57
## 7 NC_035780.1 2588794 2588796 + -51
## 8 NC_035780.1 2588794 2588796 - -57
## 9 NC_035780.1 2589720 2589722 - 50
## 10 NC_035780.1 4286286 4286288 + 54
## # ... with 412 more rows
write_delim(dml05251200.bed, "../analyses/dml05251200.bed", delim = '\t', col_names = FALSE)
Written on May 25, 2018