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Issue with effsize.y axis #30

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coynie opened this issue Apr 10, 2019 · 13 comments
Open

Issue with effsize.y axis #30

coynie opened this issue Apr 10, 2019 · 13 comments
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@coynie
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coynie commented Apr 10, 2019

Hi

I am having issues with the effsize.y axis. For some reason the mean and 95%CI is not aligning to the swarm plot. Please see attached screenshot and code. I have 5 other dabestr plots that I have created with other variables and they are all fine so I am unsure what is happening here. Have tried restarting R, clearing plots and environment and restarting computer.

changeACWR_est <- dabest(wlSNs_nobeta, group1, change_raACWR, idx=c("s", "ns"))
changeACWR_est_plot <- plot(changeACWR_est, rawplot.ylabel = "Change21 ACWR", effsize.ylabel = "")

Any advice would be much appreciated. Thanks in advance.
Screen Shot 2019-04-10 at 3 27 10 pm

@josesho josesho transferred this issue from ACCLAB/DABEST-python Apr 10, 2019
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josesho commented Apr 10, 2019

Hi @coynie , could you provide a minimally reproducible example? This would help me in trying to debug the issue.

Thanks!

@josesho josesho added bug Something isn't working duplicate This issue or pull request already exists labels Apr 10, 2019
@coynie
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coynie commented Apr 10, 2019

Sure try this. I'm using couplet's plot grid() to put all the plots together but the issue also appears when calling the single plot. Thanks!

`#load required packages
library(tidyverse)
library(dabestr)
library(cowplot)

#data for analysis
wlSNs_nobeta <- structure(list(id = c(8, 9, 10, 11, 12, 13, 14, 15, 19, 20, 21,
22, 23, 24, 25, 26, 27, 28), abs_raA = c(117.142857142857, 98.5714285714286,
112.857142857143, 215.714285714286, 377.142857142857, 185.714285714286,
77.1428571428571, 84.2857142857143, 60, 128.571428571429, 168.333333333333,
175, 72.1428571428571, 145.714285714286, 105.714285714286, 288.571428571429,
51.4285714285714, 364.285714285714), abs_raC = c(308.095238095238,
197.142857142857, 170, 424.761904761905, 368.571428571429, 291.904761904762,
312.857142857143, 101.904761904762, 159.52380952381, 212.380952380952,
376, 316.5, 155, 241.428571428571, 198.095238095238, 358.333333333333,
108.571428571429, 420), abs_raCA = c(190.952380952381, 98.5714285714286,
57.1428571428571, 209.047619047619, -8.57142857142861, 106.190476190476,
235.714285714286, 17.6190476190476, 99.5238095238095, 83.8095238095238,
207.666666666667, 141.5, 82.8571428571429, 95.7142857142857,
92.3809523809524, 69.7619047619048, 57.1428571428571, 55.7142857142857
), abs_raACWR = c(0.380216383307573, 0.5, 0.663865546218487,
0.507847533632287, 1.02325581395349, 0.636215334420881, 0.246575342465753,
0.827102803738318, 0.376119402985075, 0.605381165919283, 0.447695035460993,
0.552922590837283, 0.465437788018433, 0.603550295857988, 0.533653846153846,
0.80531561461794, 0.473684210526316, 0.86734693877551), change_raA = c(-288.571428571429,
-201.428571428571, -270, -567.142857142857, -60, -118.571428571429,
-298.571428571429, 21.4285714285714, -212.857142857143, -180,
-298.095238095238, -199.285714285714, -193.571428571429, -91.4285714285714,
-271.428571428571, -118.571428571429, -214.285714285714, 80),
change_raC = c(-95.2380952380952, -51.9047619047619, -112.857142857143,
-104.52380952381, 25.7142857142857, -15.2380952380952, -160.952380952381,
-78.5714285714286, -187.619047619048, -125, -83.7619047619048,
-52.0714285714286, -83.5714285714286, -38.0952380952381,
-271.904761904762, -45.952380952381, -127.142857142857, 18.0952380952381
), change_raCA = c(193.333333333333, 149.52380952381, 157.142857142857,
462.619047619048, 85.7142857142857, 103.333333333333, 137.619047619048,
-100, 25.2380952380952, 54.9999999999999, 214.333333333333,
147.214285714286, 110, 53.3333333333333, -0.476190476190439,
72.6190476190476, 87.1428571428571, -61.9047619047619), change_raACWR = c(-0.625686804413796,
-0.704588910133843, -0.689669807316866, -0.971234787555297,
-0.251744186046512, -0.354482339997724, -0.54638948165485,
0.478817843316154, -0.4098888274676, -0.309227161533081,
-0.566805223472202, -0.462581285131709, -0.648334667071387,
-0.244831305504874, -0.268777764788403, -0.201751523191247,
-0.653588516746411, 0.160000967211529), vol_raA = c(134.400009255403,
54.690755317523, 81.8029940453958, 228.796084324313, 52.1116764473897,
52.17048005635, 114.791863873978, 29.1042160792213, 75.3007252458179,
69.6089312098585, 158.892986495762, 55.996537793849, 60.2162849386883,
56.2372974535452, 89.7174053792704, 41.6757521678502, 54.3074607355673,
83.5213234296735), vol_raC = c(39.2969612156178, 22.5100008967927,
30.3345454109121, 59.7468903635099, 20.3757225154646, 9.31105907969749,
59.6666675715245, 39.2989807875536, 57.4372542068637, 46.8911717595761,
54.6856681207061, 17.7416134330766, 24.929790192568, 12.4435015145565,
89.8737972253737, 28.4832255319214, 34.8864602927696, 24.6249044555942
), vol_raCA = c(97.6690486403154, 38.4977179847517, 63.2065120705485,
204.750336513382, 53.7078987373672, 46.3583456339043, 69.9798974636487,
65.5017101370811, 26.8764575294767, 29.8834253794117, 106.722245198119,
39.8097886075452, 37.8517445059315, 51.7648471002637, 19.8142764227355,
26.9382580002514, 27.9062013512788, 76.8923734958472), vol_raACWR = c(0.28429919291267,
0.171475792832436, 0.244322639207408, 0.373651133819046,
0.145425433431645, 0.155955657305554, 0.215185142559467,
0.431139025365937, 0.176125761252924, 0.126149217953567,
0.259407332307541, 0.122717923733346, 0.201250420355636,
0.19919646372914, 0.092689253646399, 0.0672587677321364,
0.168539028726557, 0.192878218038433), abs_ewma1A = c(119.000513795851,
106.643368888931, 111.387428539078, 221.144496813386, 331.567343001678,
160.587893859214, 99.4100466130151, 72.836148777051, 81.6535945857512,
120.177325421192, 124.863369007239, 155.523648087284, 68.8930722842997,
140.583503512754, 80.3738608682444, 201.884482756256, 52.9528674472491,
344.826336948895), abs_ewma1C = c(236.254644679062, 171.464595099452,
160.966248540278, 346.807174449879, 364.692626725041, 240.57877338261,
249.739004607213, 106.537786969847, 143.340274138407, 187.80021906227,
263.03773343222, 269.347489800666, 131.593427322217, 203.508843222624,
181.082468613815, 318.431863584711, 108.695947361405, 399.1155344357
), abs_ewma1CA = c(117.254130883211, 64.8212262105204, 49.5788200011999,
125.662677636493, 33.1252837233632, 79.990879523396, 150.328957994198,
33.7016381927958, 61.6866795526559, 67.6228936410777, 138.17436442498,
113.823841713382, 62.7003550379175, 62.9253397098706, 100.70860774557,
116.547380828455, 55.7430799141559, 54.2891974868048), abs_ewma1ACWR = c(0.503695975829411,
0.621955621958438, 0.691992449033227, 0.6376583678356, 0.90916930780633,
0.667506495279279, 0.398055749318639, 0.683664930994537,
0.569648656503251, 0.639921114156658, 0.474697555282176,
0.577408938180124, 0.523529736144111, 0.690798008020543,
0.443852248555621, 0.633995858591424, 0.487165057508402,
0.863976235443797), change_ewma1A = c(-247.479397574522,
-125.167514727307, -335.116905625623, -619.607631419535,
-193.409486690768, -162.476517568277, -335.985522275293,
-16.3380132047176, -142.139422314612, -160.110506645666,
-380.843476101779, -155.693177478515, -223.513427328224,
-136.188957934618, -296.295982747113, -281.400361905739,
-174.986071577384, 86.615804004321), change_ewma1C = c(-116.573017168172,
-46.9713592153722, -143.105905458055, -241.996771980647,
-13.8303401133433, -50.2130049197111, -199.516425167813,
-37.2557511659476, -115.119654316466, -114.763856232343,
-173.889154977408, -68.1105112142749, -112.847740234337,
-28.4048913522242, -227.175750781799, -82.0837454936471,
-113.96748014844, 93.3714663554437), change_ewma1CA = c(130.906380406349,
78.1961555119344, 192.011000167567, 377.610859438888, 179.579146577424,
112.263512648566, 136.469097107481, -20.9177379612299, 27.0197679981468,
45.346650413323, 206.954321124371, 87.58266626424, 110.665687093886,
107.784066582394, 69.1202319653141, 199.316616412092, 61.0185914289439,
6.75566235112274), change_ewma1ACWR = c(-0.534997842709821,
-0.439274816699738, -0.776423281554021, -0.790239888162458,
-0.477739481579207, -0.443475435893539, -0.571093514177948,
0.0635107631656937, -0.296222576373137, -0.286454007522729,
-0.682719986471191, -0.344829754130568, -0.67269470728918,
-0.502630496568715, -0.478774230766657, -0.572660845186241,
-0.536527704135424, 0.0194446160215185), vol_ewma1A = c(133.058943289248,
58.154376791002, 80.0022899860389, 212.773616734812, 62.2977569777029,
62.5272202473118, 125.880561244335, 24.293102991733, 74.2126805049861,
72.4987165719818, 161.916803259578, 69.3971879944651, 61.2987495871907,
62.9597383731531, 93.9933335554993, 78.6035209207713, 50.4804137523572,
95.8782703975514), vol_ewma1C = c(60.4288474357636, 24.388559079803,
37.4089616754015, 94.3846758176754, 25.5653635138887, 23.6340854545295,
64.9306148275604, 9.80860196770636, 45.7234291416375, 43.8366127829923,
76.2975300783642, 28.0936907267791, 33.2550918223923, 26.2677802163546,
71.5813431589987, 28.1715656161128, 33.8729621637774, 51.0993014129225
), vol_ewma1CA = c(77.1454818672372, 35.8493241401187, 45.9609658264543,
129.249914970496, 43.0094060720612, 41.2228517805564, 62.5939951062421,
21.9830139196358, 30.3658353689791, 31.5750544615464, 91.4483272128544,
42.0565280424247, 29.4425296918994, 43.1850605707931, 26.876612659395,
53.3687516047934, 18.4316074100456, 56.6895426827224), vol_ewma1ACWR = c(0.242492105948462,
0.170430303448065, 0.187631910235743, 0.250022163148667,
0.113554041340076, 0.146197862587291, 0.211796915409643,
0.169442352520555, 0.179875896539722, 0.132612179620373,
0.24082518417007, 0.136728182832202, 0.172003262084573, 0.178104515964331,
0.142171539758038, 0.142711407051194, 0.144138813733478,
0.135696948703938), abs_ewma2A = c(183.918560064379, 145.316223039074,
138.263888252649, 287.874401929521, 362.341652014512, 210.088238871599,
181.839209611985, 94.5225575268521, 110.914679311641, 155.20582192806,
200.452696056051, 226.561702973587, 103.090922444334, 179.808512534344,
130.399314875075, 278.376752962211, 82.1927558295064, 389.891222685059
), abs_ewma2C = c(264.478261800536, 175.463960750135, 168.408379962856,
367.934442127866, 326.151827721931, 249.26898853511, 304.60138980156,
110.044141167933, 168.513637455178, 212.444710060945, 299.740057372783,
288.52740139959, 151.622763873964, 201.237797909154, 233.867232870284,
316.960043351866, 131.829932971608, 363.184762572632), abs_ewma2CA = c(80.5597017361575,
30.147737711061, 30.1444917102073, 80.0600401983447, -36.1898242925814,
39.1807496635109, 122.762180189576, 15.5215836410814, 57.5989581435376,
57.2388881328847, 99.2873613167322, 61.9656984260027, 48.5318414296308,
21.4292853748094, 103.467917995209, 38.5832903896554, 49.6371771421013,
-26.7064601124274), abs_ewma2ACWR = c(0.695401424723088,
0.828182735747131, 0.821003612071704, 0.782406779492196,
1.1109600536209, 0.842817392192401, 0.596974326776539, 0.85895129466825,
0.658194084387634, 0.730570424104867, 0.668755113390635,
0.785234615064568, 0.679917182686548, 0.893512622392721,
0.557578388706559, 0.878270806687066, 0.623475670333598,
1.07353408750756), change_ewma2A = c(-188.000572544508, -94.6226948922742,
-229.298043683799, -418.99468462549, -83.7365303248213, -95.7725933788113,
-270.166750080467, -40.0820691450345, -147.823679067487,
-149.727917432235, -275.96458738209, -112.025151782666, -163.736804971735,
-77.4121643981451, -276.491105899767, -171.036917612525,
-150.80131952528, 87.6574442040162), change_ewma2C = c(-15.1298155305186,
13.9508762820792, -43.0710704494082, -43.56604601394, 55.4030645311743,
7.69796429391823, -81.4087723040039, -9.40538004332096, -41.7831354990953,
-42.02682856784, -37.6566517221904, -2.41391140889039, -41.5799021424581,
26.8625634063856, -115.852250689044, 20.3759672019833, -50.9787633626888,
110.157539240527), change_ewma2CA = c(172.870757013989, 108.573571174353,
186.226973234391, 375.42863861155, 139.139594855996, 103.47055767273,
188.757977776463, 30.6766891017135, 106.040543568392, 107.701088864395,
238.3079356599, 109.611240373775, 122.156902829277, 104.274727804531,
160.638855210723, 191.412884814509, 99.8225561625915, 22.5000950365105
), change_ewma2ACWR = c(-0.634743026606677, -0.657386800130337,
-0.917046733812549, -0.935377541364842, -0.536612319683156,
-0.423314724484928, -0.57399474105033, -0.26792326545518,
-0.572154602110695, -0.467731519615144, -0.743283802804114,
-0.378528796490313, -0.701159657078116, -0.581586050110605,
-0.605898168657781, -0.637028586351214, -0.651048354107328,
-0.120937299803811), vol_ewma2A = c(91.9588815840292, 40.3889973556659,
58.7031932372458, 151.729907666619, 35.5185765807231, 38.1794122199367,
90.7060688363441, 13.2144033744877, 61.2996027191368, 58.7724764068333,
115.597176887869, 43.6703483719149, 47.000566130851, 39.6063463849827,
86.5775660333691, 46.7945288566893, 43.9439765525937, 64.9267667721921
), vol_ewma2C = c(27.3896345921318, 12.190312739752, 10.8210057549351,
33.2054696138874, 28.214398546402, 13.6255152657358, 30.2000394227757,
4.2493925930861, 19.9843949810855, 18.7532851476218, 30.9551909492202,
15.5759988448038, 13.4632676578819, 20.3572012564723, 37.3367368630928,
23.1119297729738, 15.6842926104954, 44.1529912478655), vol_ewma2CA = c(72.797721992427,
39.0432587430069, 48.9816314175276, 129.128658513725, 31.4404883631809,
34.0948100828694, 62.1521421762724, 9.15903819874985, 42.7990028743541,
41.2571869728855, 91.8596997717577, 35.6112233031997, 34.9199698346061,
35.5389201374803, 50.2181685846357, 47.793724733221, 28.8803401893618,
32.7914500440276), vol_ewma2ACWR = c(0.236116019346408, 0.214246094117512,
0.243540782254956, 0.299051175368149, 0.123183014043921,
0.130683044094494, 0.179752325510558, 0.0787023792160263,
0.214621895529561, 0.165285357463659, 0.255045062275643,
0.11530832512659, 0.194289221069225, 0.176818437082674, 0.179778338641324,
0.154943630723732, 0.181602058178967, 0.0864283357820412),
abs_strain = c(0.511624724594905, 0.994996841658075, 1.25990774607263,
1.69506063680318, 1.29697240783637, 1.39741867551076, 0.764184950247154,
0.850175866113747, 1.40129809949074, 1.32510649335428, 1.59225995946228,
0.862267768891004, 1.01531042371759, 1.10059838295304, 0.98886659507597,
0.775364737520656, 0.952661023244934, 1.30078340653854),
abs_mono = c(419.532274167822, 686.547820744072, 995.327119397379,
2559.54156157281, 3424.00715668802, 1816.64427816399, 412.659873133463,
501.60376100711, 588.545201786111, 1192.59584401885, 1608.1825590569,
905.381157335554, 512.731763977381, 1122.6103506121, 731.761280356218,
1566.23676979173, 342.957968368176, 3316.99768667326), change_strain = c(-1.10999736698528,
-0.39621984562243, -0.0104817580762235, -0.18843453838751,
-0.37869001293898, 0.0437478983708457, -0.869428950673985,
-0.444501883826553, -0.0729132754098638, 0.358051099170145,
0.414966526317288, -1.15198489235101, -0.424417536845587,
-0.909100593161162, -0.202035447545743, -0.769121974221751,
-0.360752885519826, -0.334323770175296), change_mono = c(-4185.8744659199,
-2235.00722254499, -2409.31675172155, -7762.0119984722, -1703.51985088455,
-1066.67447714403, -3883.74468628913, -68.0544489666212,
-2227.19852427404, -896.243807418881, -2235.68050016149,
-4371.96081511852, -2165.16224267012, -2213.48994973748,
-2412.2201121651, -2835.55035867414, -2099.99190193428, 63.1344050127409
), mean_strain = c(1.13412228876208, 1.49497808625493, 1.15429109715176,
1.60326658292368, 1.54470490693682, 1.61892543027148, 1.38253058775848,
1.35411560994399, 1.39945225046909, 1.26553641440904, 1.24798656167442,
1.75790781276539, 1.5025664464122, 1.6108887263159, 1.21263893160127,
1.35062809319368, 1.34258148984896, 1.41025386531569), mean_mono = c(3048.22250604434,
2459.2726656218, 1719.06076210491, 5772.58813124984, 4240.70963346739,
3518.79534807063, 3639.60137244606, 972.012259299196, 1890.705860162,
2050.14883234255, 3395.44461984326, 4409.41285323894, 1916.59787912395,
2983.34692677836, 2088.77161757183, 3903.0625690138, 1332.57561844879,
4098.10619089067), group1 = c("ns", "ns", "ns", "ns", "ns",
"ns", "ns", "ns", "s", "s", "s", "s", "s", "s", "s", "s",
"s", "s"), group2 = c("bot5", "bot5", "bot5", "bot5", "bot5",
"na", "na", "na", "na", "na", "na", "na", "na", "top5", "top5",
"top5", "top5", "top5"), pb = c(0.933099, 0.945946, 0.95122,
0.961538, 0.965368, 0.96962, 0.976798, 0.983333, 0.997167,
1, 1, 1.006289, 1.006711, 1.0131, 1.018041, 1.029412, 1.02973,
1.051793), wr = c(0.960144927536232, 0.921052631578947, 0.898617511520737,
0.921658986175115, 0.957081545064378, 0.928484848484848,
0.891005291005291, 0.986072423398329, 0.98050139275766, 0.926773455377574,
0.94047619047619, 0.960960960960961, 0.983606557377049, 0.995708154506438,
1.00253807106599, 0.967741935483871, 1.00263157894737, 1.00763358778626
), inj42 = c(0.0238095238095238, 1, 0, 0.880952380952381,
0, 0.928571428571429, 0.857142857142857, 0, 1, 1, 0, 0, 0,
0, 0.261904761904762, 0.0714285714285714, 0.476190476190476,
0), inj14 = c(0, 1, 0, 0.785714285714286, 0, 0.785714285714286,
0.571428571428571, 0, 1, 1, 0, 0, 0, 0, 0.785714285714286,
0, 0.0714285714285714, 0)), row.names = c(NA, -18L), class = c("tbl_df",
"tbl", "data.frame"))

#Cumming estimation plots for differences in rolling average C-A and ACWR
absCA_est <- dabest(wlSNs_nobeta, group1, abs_raCA, idx=c("s", "ns"))
changeCA_est <- dabest(wlSNs_nobeta, group1, change_raCA, idx=c("s", "ns"))
volCA_est <- dabest(wlSNs_nobeta, group1, vol_raCA, idx=c("s", "ns"))

absCA_est_plot <- plot(absCA_est, rawplot.ylabel = "Absolute C-A", effsize.ylabel = "")
changeCA_est_plot <- plot(changeCA_est, rawplot.ylabel = "Change21 C-A", effsize.ylabel = "")
volCA_est_plot <- plot(volCA_est, rawplot.ylabel = "Vol21 C-A", effsize.ylabel = "")
plot_grid(absCA_est_plot, changeCA_est_plot, volCA_est_plot, nrow=1, labels = "auto")

absACWR_est <- dabest(wlSNs_nobeta, group1, abs_raACWR, idx=c("s", "ns"))
changeACWR_est <- dabest(wlSNs_nobeta, group1, change_raACWR, idx=c("s", "ns"))
volACWR_est <- dabest(wlSNs_nobeta, group1, vol_raACWR, idx=c("s", "ns"))

absACWR_est_plot <- plot(absACWR_est, rawplot.ylabel = "Absolute ACWR", effsize.ylabel = "")
changeACWR_est_plot <- plot(changeACWR_est, rawplot.ylabel = "Change21 ACWR", effsize.ylabel = "")
volACWR_est_plot <- plot(volACWR_est, rawplot.ylabel = "Vol21 ACWR", effsize.ylabel = "")
plot_grid(absACWR_est_plot, changeACWR_est_plot, volACWR_est_plot, nrow=1, labels = "auto")`

@josesho josesho added this to the v0.3.0 milestone May 28, 2019
@josesho josesho self-assigned this May 28, 2019
@josesho josesho removed the duplicate This issue or pull request already exists label Jun 26, 2019
@josesho josesho modified the milestones: v0.3.0, v0.2.2 Jun 26, 2019
@josesho josesho mentioned this issue Jun 27, 2019
@josesho josesho closed this as completed Sep 6, 2019
@coynie
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coynie commented Sep 13, 2019 via email

@josesho josesho reopened this Sep 17, 2019
@josesho
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josesho commented Sep 17, 2019

Hi sorry, this issue has not been resolved yet. It is very curious that only the change_raACWR column in your dataset produces a misaligned plot....

@josesho josesho modified the milestones: v0.2.2, v0.3.0 Sep 18, 2019
@coynie
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coynie commented Sep 18, 2019 via email

@mick42-star
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Hi I met the sample problem with v0.2.5. I wonder whether this problem been solved

@faustovrz
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faustovrz commented Oct 5, 2020

I think the misalignment problem is due to differences of negative values.
I ran on the same issue with a dataset like this:

library(dplyr)
library(dabestr)

flowering <- data.frame(
  genotype = c(rep("wt", 300), rep("mutant", 100)), 
  anthesis = c(50 + rbinom(300, 7, 1/20), 50 + rbinom(100, 7, 1/5)), 
  silking  = c(50 + rbinom(300, 7, 1/4),  50 + rbinom(100, 7, 3/5))
) %>%
  dplyr::mutate(ASI = anthesis - silking,
                SAI = silking - anthesis) 


unpaired_mean_diff <-  flowering %>%
  dabestr::dabest(genotype, ASI,
                  idx = c("wt", "mutant"),
                  paired = FALSE) %>% 
  dabestr::mean_diff()

unpaired_mean_diff 

plot(unpaired_mean_diff)

Screen Shot 2020-10-05 at 12 19 22 PM

It disappears when I use the positive quantities:

unpaired_mean_diff <-  flowering %>%
  dabestr::dabest(genotype, SAI,
                  idx = c("wt", "mutant"),
                  paired = FALSE) %>% 
  dabestr::mean_diff()

unpaired_mean_diff 

plot(unpaired_mean_diff)

Screen Shot 2020-10-05 at 12 32 58 PM

@josesho
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josesho commented Oct 6, 2020

Hi @faustovrz, thanks for this key bit of debugging! I'll see how to mitigate this.

@faustovrz
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faustovrz commented Nov 20, 2020

Hi @josesho, you are welcome, these plots are neat, except for this bug. Any update on this issue?

@josesho
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josesho commented Nov 21, 2020

@faustovrz apologies for the delay, will aim to update by end of next week!

@roey-angel
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Hi, any progress with fixing this bug?
My current workaround is either to recreate the plot using ggplot from mean_diff() output or add a large positive value before computing mean_diff() and then subtract it manually from the plots using a vector manipulation software

@SamRPJRoss
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SamRPJRoss commented Jun 3, 2022

Hi all, anyone found a solution to this? I'm using 0.3.0 and encountered the same issue with negative numbers. I have a variable whose sign is important, and thus should be conserved. Would be great to know how to fix this.

@roey-angel how did you find reproducing the plot in ggplot. Was it successful? Cheers!

@roey-angel
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@SamRPJRoss Sorry I cannot find my ggplot code right now.
I mostly use my trick to convert values to positive and then subtract them in Inkscape.
That's a real shame that such an important package isn't maintained.

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