ggplot2 suddenly behaving weird after some tweaks that I did with R

dhyou21 · March 31, 2020, 2:58am

I recently reinstalled my R/Rstudio due to the issue with one of the packages, and during this process, I also (1) downloaded and installed R development tools and libraries (clang and gfortran) from R for macOS - Development Tools and Libraries (2) downloaded and installed gfortran compiler for R from Release gfortran 6.3 for Sierra (macOS 10.12) · fxcoudert/gfortran-for-macOS · GitHub (3) uninstalled Java/JDK 14 and installing Java/JDK 11 version; and (4) ran “R CMD javareconf” comman on the terminal. All of these actions were taken to resolve the error associated with one of the packages requiring Java connection.

However, during theses resolution steps, something else seemed to be messed up because the existing function/package/script started working inappropriately. So the problem is (and this problem is SEPARATE from the package problem that I was trying to solve with the resolution steps mentioned above): I run this script that utilizes several packages including ggplot2, tibble, dplyr, etc. to generate my graphs. Just several days ago when I tried to generate these graphs, the script worked fine (see below picture, on the left labeled as a "good example").

But after all the resolution steps that I took as discussed above, the exact same script no longer works properly (see above picture, on the right side labeled as a "bad example" that I'm getting now). I used the exact same script, same packages to generate these graphs but now the graphs are being generated strangely…It seems like the tickmarks on the y axis are now not getting evenly spaced out throughout the whole y-axis and the problem starts at the stage where I create "Plot."

Does anyone have any idea what might have gone wrong during the resolution that could have damaged R (or its associated packages) to cause this problem? I want to go back to the ggplot2 that used to create that "good example"

The data that I used (which are confidential so I can't really share unfortunately) are basically table of different cell numbers in each well ("Number_of_Objects) in 384-well plate and I tried to depict the data using the heatmap approach as shown in the figure. The figure shows the collection of small rectangles corresponding to each well in 384-well plate and they are colored on gray gradient based on the cell density (darker, the greater density). The code that I used to plot this is:

library("tidyverse")
library("stringr")
library("ggplot2")
library("ggpubr")

#Table corresponds to the data table of 384-well plate that will be analyzed#

Plot=ggplot(Table, aes(x=Column, y=-Row)) + theme_classic()+
    scale_x_discrete(limits=c(1:24), name="") + 
    scale_y_discrete(limits=c(-1:-16), labels=LETTERS[1:16], name="")
  
  
  pShape=Plot + ggtitle("Number of non-border cells") +
    geom_tile(aes(fill=Number_of_Objects)) +
    scale_fill_gradient(low = "black", high = "gray80", name="")

I used the exactly the same script both times and both times the script runs without any error but generates completely different graphs. How can I fix the issue so that I can go back to the "good example" graph state?

I understand that the problem can be anything here. If it is indeed the error due to installing different compilers, do I have to uninstall those as well (how can I figure this out)? I thought that the compilers will also be uninstalled when I uninstall the R but is that not the case? Do I have to go through uninstall/reinstall of Java as well? What are some commands that I can check on terminal to find a potential bug that I'm having with ggplot2?

Thank you!

andresrcs · March 31, 2020, 3:54am

Do you also updated any of these packes? It is very unlikely that the installation of the compilers or Java has anything to do with this, it is more feasible that this is related to a package update with breaking changes.

To give you any specific advice we would need a REPRoducible EXample (reprex), can you try to make one with made up data that resembles your actual data?

dhyou21 · March 31, 2020, 2:05pm

Hi, thank you for the reply.

So during install/reinstall, some of those packages might have been updated as well. I checked the updates on all the packages that were installed and except for "tibble," which is a package that gets called along with those libraries when I load "tidyverse," everything was up-to-date. Here is the exact console output that I get when I call those libraries:

> library("tidyverse")
── Attaching packages ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────── tidyverse 1.3.0 ──
✓ ggplot2 3.3.0     ✓ purrr   0.3.3
✓ tibble  2.1.3     ✓ dplyr   0.8.5
✓ tidyr   1.0.2     ✓ stringr 1.4.0
✓ readr   1.3.1     ✓ forcats 0.5.0
── Conflicts ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────── tidyverse_conflicts() ──
x dplyr::filter() masks stats::filter()
x dplyr::lag()    masks stats::lag()
> library("stringr")
> library("ggplot2")
> library("ggpubr")
Loading required package: magrittr

Attaching package: ‘magrittr’

The following object is masked from ‘package:purrr’:

    set_names

The following object is masked from ‘package:tidyr’:

    extract

As you suggested, I tried to create a reprex and the output is below. The example data is similar to the structure of my actual dataset - I created it using "datapasta" package's paste as tribble function. One thing to note is that on columns "row" "column" and "Number_of_Objects," there is a letter "L" after every number but it is not supposed to be there. The original sample data that I copied from Excel only contain numbers - and I don't know why "L" got added to every single number in the data. Anyhow...the thing that was strange with the reprex was that... in the rendered reprex, the image saving output was 7x5 whereas, when I actually ran the code on my R, the image was saved as 7x7 (see the last line, that says "saving 7x5 in image" - in my console, when the code was actually run, it says "Saving 7x7 in image")

library("tidyverse")
library("stringr")
library("ggplot2")
library("ggpubr")
#> Loading required package: magrittr
#> 
#> Attaching package: 'magrittr'
#> The following object is masked from 'package:purrr':
#> 
#>     set_names
#> The following object is masked from 'package:tidyr':
#> 
#>     extract

ExampleTable <- tibble::tribble(
                  ~Well, ~Row, ~Column, ~Number_of_Objects,
                  "A01",   1L,      1L,               532L,
                  "A02",   1L,      2L,               400L,
                  "A03",   1L,      3L,               875L,
                  "A04",   1L,      4L,               573L,
                  "A05",   1L,      5L,               970L,
                  "A06",   1L,      6L,               626L,
                  "A07",   1L,      7L,              1330L,
                  "A08",   1L,      8L,               623L,
                  "A09",   1L,      9L,               657L,
                  "A10",   1L,     10L,               964L,
                  "A11",   1L,     11L,               905L,
                  "A12",   1L,     12L,                80L,
                  "A13",   1L,     13L,               650L,
                  "A14",   1L,     14L,               250L,
                  "A15",   1L,     15L,               484L,
                  "A16",   1L,     16L,               493L,
                  "A17",   1L,     17L,               550L,
                  "A18",   1L,     18L,               401L,
                  "A19",   1L,     19L,               841L,
                  "A20",   1L,     20L,               410L,
                  "A21",   1L,     21L,              1166L,
                  "A22",   1L,     22L,                74L,
                  "A23",   1L,     23L,                54L,
                  "A24",   1L,     24L,               882L,
                  "B01",   2L,      1L,               113L,
                  "B02",   2L,      2L,                90L,
                  "B03",   2L,      3L,               682L,
                  "B04",   2L,      4L,               567L,
                  "B05",   2L,      5L,               949L,
                  "B06",   2L,      6L,               749L,
                  "B07",   2L,      7L,               771L,
                  "B08",   2L,      8L,               494L,
                  "B09",   2L,      9L,               806L,
                  "B10",   2L,     10L,               616L,
                  "B11",   2L,     11L,               865L,
                  "B12",   2L,     12L,                44L,
                  "B13",   2L,     13L,                65L,
                  "B14",   2L,     14L,               416L,
                  "B15",   2L,     15L,                51L,
                  "B16",   2L,     16L,              1279L,
                  "B17",   2L,     17L,               519L,
                  "B18",   2L,     18L,              1017L,
                  "B19",   2L,     19L,               763L,
                  "B20",   2L,     20L,               212L,
                  "B21",   2L,     21L,               763L,
                  "B22",   2L,     22L,               435L,
                  "B23",   2L,     23L,               532L,
                  "B24",   2L,     24L,               227L,
                  "C01",   3L,      1L,               714L,
                  "C02",   3L,      2L,               851L,
                  "C03",   3L,      3L,               530L,
                  "C04",   3L,      4L,              1296L,
                  "C05",   3L,      5L,               564L,
                  "C06",   3L,      6L,               979L,
                  "C07",   3L,      7L,               801L,
                  "C08",   3L,      8L,               680L,
                  "C09",   3L,      9L,               137L,
                  "C10",   3L,     10L,               655L,
                  "C11",   3L,     11L,               735L,
                  "C12",   3L,     12L,               855L,
                  "C13",   3L,     13L,              1374L,
                  "C14",   3L,     14L,              1380L,
                  "C15",   3L,     15L,               612L,
                  "C16",   3L,     16L,               475L,
                  "C17",   3L,     17L,              1241L,
                  "C18",   3L,     18L,               358L,
                  "C19",   3L,     19L,               731L,
                  "C20",   3L,     20L,               666L,
                  "C21",   3L,     21L,               943L,
                  "C22",   3L,     22L,              1056L,
                  "C23",   3L,     23L,               891L,
                  "C24",   3L,     24L,               738L,
                  "D01",   4L,      1L,               769L,
                  "D02",   4L,      2L,               556L,
                  "D03",   4L,      3L,               598L,
                  "D04",   4L,      4L,                95L,
                  "D05",   4L,      5L,               201L,
                  "D06",   4L,      6L,               912L,
                  "D07",   4L,      7L,               908L,
                  "D08",   4L,      8L,               865L,
                  "D09",   4L,      9L,               990L,
                  "D10",   4L,     10L,               859L,
                  "D11",   4L,     11L,              1439L,
                  "D12",   4L,     12L,               711L,
                  "D13",   4L,     13L,               812L,
                  "D14",   4L,     14L,               533L,
                  "D15",   4L,     15L,               572L,
                  "D16",   4L,     16L,              1056L,
                  "D17",   4L,     17L,                61L,
                  "D18",   4L,     18L,               293L,
                  "D19",   4L,     19L,              1071L,
                  "D20",   4L,     20L,               839L,
                  "D21",   4L,     21L,               830L,
                  "D22",   4L,     22L,               562L,
                  "D23",   4L,     23L,                75L,
                  "D24",   4L,     24L,                 5L,
                  "E01",   5L,      1L,               585L,
                  "E02",   5L,      2L,               751L,
                  "E03",   5L,      3L,               134L,
                  "E04",   5L,      4L,              1368L,
                  "E05",   5L,      5L,               991L,
                  "E06",   5L,      6L,               875L,
                  "E07",   5L,      7L,               617L,
                  "E08",   5L,      8L,               936L,
                  "E09",   5L,      9L,              1337L,
                  "E10",   5L,     10L,                78L,
                  "E11",   5L,     11L,               602L,
                  "E12",   5L,     12L,              1074L,
                  "E13",   5L,     13L,               940L,
                  "E14",   5L,     14L,               393L,
                  "E15",   5L,     15L,              1157L,
                  "E16",   5L,     16L,              1248L,
                  "E17",   5L,     17L,               881L,
                  "E18",   5L,     18L,               980L,
                  "E19",   5L,     19L,               675L,
                  "E20",   5L,     20L,              1114L,
                  "E21",   5L,     21L,               897L,
                  "E22",   5L,     22L,               650L,
                  "E23",   5L,     23L,               168L,
                  "E24",   5L,     24L,               271L,
                  "F01",   6L,      1L,               591L,
                  "F02",   6L,      2L,               257L,
                  "F03",   6L,      3L,               609L,
                  "F04",   6L,      4L,               539L,
                  "F05",   6L,      5L,              1015L,
                  "F06",   6L,      6L,               891L,
                  "F07",   6L,      7L,              1063L,
                  "F08",   6L,      8L,               972L,
                  "F09",   6L,      9L,               927L,
                  "F10",   6L,     10L,              1162L,
                  "F11",   6L,     11L,               762L,
                  "F12",   6L,     12L,               770L,
                  "F13",   6L,     13L,               706L,
                  "F14",   6L,     14L,               308L,
                  "F15",   6L,     15L,              1167L,
                  "F16",   6L,     16L,               750L,
                  "F17",   6L,     17L,               963L,
                  "F18",   6L,     18L,              1102L,
                  "F19",   6L,     19L,               407L,
                  "F20",   6L,     20L,               839L,
                  "F21",   6L,     21L,              1047L,
                  "F22",   6L,     22L,               815L,
                  "F23",   6L,     23L,               609L,
                  "F24",   6L,     24L,                65L,
                  "G01",   7L,      1L,               130L,
                  "G02",   7L,      2L,               435L,
                  "G03",   7L,      3L,               823L,
                  "G04",   7L,      4L,               291L,
                  "G05",   7L,      5L,              1278L,
                  "G06",   7L,      6L,               567L,
                  "G07",   7L,      7L,               124L,
                  "G08",   7L,      8L,               797L,
                  "G09",   7L,      9L,               950L,
                  "G10",   7L,     10L,              1095L,
                  "G11",   7L,     11L,               712L,
                  "G12",   7L,     12L,              1169L,
                  "G13",   7L,     13L,               689L,
                  "G14",   7L,     14L,               546L,
                  "G15",   7L,     15L,               602L,
                  "G16",   7L,     16L,               830L,
                  "G17",   7L,     17L,               123L,
                  "G18",   7L,     18L,              1222L,
                  "G19",   7L,     19L,               989L,
                  "G20",   7L,     20L,              1040L,
                  "G21",   7L,     21L,               426L,
                  "G22",   7L,     22L,               275L,
                  "G23",   7L,     23L,              1026L,
                  "G24",   7L,     24L,               670L,
                  "H01",   8L,      1L,               769L,
                  "H02",   8L,      2L,                86L,
                  "H03",   8L,      3L,              1263L,
                  "H04",   8L,      4L,               740L,
                  "H05",   8L,      5L,              1445L,
                  "H06",   8L,      6L,               607L,
                  "H07",   8L,      7L,               173L,
                  "H08",   8L,      8L,              1390L,
                  "H09",   8L,      9L,               749L,
                  "H10",   8L,     10L,               940L,
                  "H11",   8L,     11L,               669L,
                  "H12",   8L,     12L,               746L,
                  "H13",   8L,     13L,               787L,
                  "H14",   8L,     14L,               604L,
                  "H15",   8L,     15L,               912L,
                  "H16",   8L,     16L,               742L,
                  "H17",   8L,     17L,               119L,
                  "H18",   8L,     18L,               995L,
                  "H19",   8L,     19L,              1027L,
                  "H20",   8L,     20L,               745L,
                  "H21",   8L,     21L,               358L,
                  "H22",   8L,     22L,               119L,
                  "H23",   8L,     23L,               221L,
                  "H24",   8L,     24L,                15L,
                  "I01",   9L,      1L,               295L,
                  "I02",   9L,      2L,               682L,
                  "I03",   9L,      3L,               879L,
                  "I04",   9L,      4L,               847L,
                  "I05",   9L,      5L,               735L,
                  "I06",   9L,      6L,               760L,
                  "I07",   9L,      7L,               948L,
                  "I08",   9L,      8L,               736L,
                  "I09",   9L,      9L,              1225L,
                  "I10",   9L,     10L,              1333L,
                  "I11",   9L,     11L,               743L,
                  "I12",   9L,     12L,               713L,
                  "I13",   9L,     13L,               637L,
                  "I14",   9L,     14L,               652L,
                  "I15",   9L,     15L,               838L,
                  "I16",   9L,     16L,               783L,
                  "I17",   9L,     17L,               910L,
                  "I18",   9L,     18L,               766L,
                  "I19",   9L,     19L,               496L,
                  "I20",   9L,     20L,               992L,
                  "I21",   9L,     21L,              1291L,
                  "I22",   9L,     22L,              1475L,
                  "I23",   9L,     23L,               121L,
                  "I24",   9L,     24L,               484L,
                  "J01",  10L,      1L,               620L,
                  "J02",  10L,      2L,               110L,
                  "J03",  10L,      3L,               425L,
                  "J04",  10L,      4L,               889L,
                  "J05",  10L,      5L,               659L,
                  "J06",  10L,      6L,               745L,
                  "J07",  10L,      7L,               840L,
                  "J08",  10L,      8L,               721L,
                  "J09",  10L,      9L,               818L,
                  "J10",  10L,     10L,               601L,
                  "J11",  10L,     11L,               711L,
                  "J12",  10L,     12L,               772L,
                  "J13",  10L,     13L,               890L,
                  "J14",  10L,     14L,               771L,
                  "J15",  10L,     15L,               938L,
                  "J16",  10L,     16L,               518L,
                  "J17",  10L,     17L,               905L,
                  "J18",  10L,     18L,               784L,
                  "J19",  10L,     19L,               906L,
                  "J20",  10L,     20L,                59L,
                  "J21",  10L,     21L,               819L,
                  "J22",  10L,     22L,               544L,
                  "J23",  10L,     23L,               588L,
                  "J24",  10L,     24L,                29L,
                  "K01",  11L,      1L,              1008L,
                  "K02",  11L,      2L,               660L,
                  "K03",  11L,      3L,              1009L,
                  "K04",  11L,      4L,               581L,
                  "K05",  11L,      5L,               902L,
                  "K06",  11L,      6L,               639L,
                  "K07",  11L,      7L,              1322L,
                  "K08",  11L,      8L,               903L,
                  "K09",  11L,      9L,               807L,
                  "K10",  11L,     10L,              1150L,
                  "K11",  11L,     11L,               956L,
                  "K12",  11L,     12L,               879L,
                  "K13",  11L,     13L,               106L,
                  "K14",  11L,     14L,               624L,
                  "K15",  11L,     15L,               840L,
                  "K16",  11L,     16L,               840L,
                  "K17",  11L,     17L,               679L,
                  "K18",  11L,     18L,               711L,
                  "K19",  11L,     19L,               569L,
                  "K20",  11L,     20L,              1043L,
                  "K21",  11L,     21L,               751L,
                  "K22",  11L,     22L,               724L,
                  "K23",  11L,     23L,               646L,
                  "K24",  11L,     24L,              1000L,
                  "L01",  12L,      1L,               567L,
                  "L02",  12L,      2L,                22L,
                  "L03",  12L,      3L,               916L,
                  "L04",  12L,      4L,               538L,
                  "L05",  12L,      5L,               984L,
                  "L06",  12L,      6L,               663L,
                  "L07",  12L,      7L,               679L,
                  "L08",  12L,      8L,               488L,
                  "L09",  12L,      9L,               853L,
                  "L10",  12L,     10L,               855L,
                  "L11",  12L,     11L,               791L,
                  "L12",  12L,     12L,              1297L,
                  "L13",  12L,     13L,              1340L,
                  "L14",  12L,     14L,               741L,
                  "L15",  12L,     15L,              1075L,
                  "L16",  12L,     16L,               725L,
                  "L17",  12L,     17L,               735L,
                  "L18",  12L,     18L,               677L,
                  "L19",  12L,     19L,               460L,
                  "L20",  12L,     20L,               287L,
                  "L21",  12L,     21L,              1044L,
                  "L22",  12L,     22L,                27L,
                  "L23",  12L,     23L,               601L,
                  "L24",  12L,     24L,                28L,
                  "M01",  13L,      1L,               126L,
                  "M02",  13L,      2L,               784L,
                  "M03",  13L,      3L,               850L,
                  "M04",  13L,      4L,               580L,
                  "M05",  13L,      5L,              1085L,
                  "M06",  13L,      6L,               794L,
                  "M07",  13L,      7L,               879L,
                  "M08",  13L,      8L,               121L,
                  "M09",  13L,      9L,               901L,
                  "M10",  13L,     10L,               589L,
                  "M11",  13L,     11L,               695L,
                  "M12",  13L,     12L,               605L,
                  "M13",  13L,     13L,               691L,
                  "M14",  13L,     14L,               302L,
                  "M15",  13L,     15L,               878L,
                  "M16",  13L,     16L,               682L,
                  "M17",  13L,     17L,               666L,
                  "M18",  13L,     18L,              1191L,
                  "M19",  13L,     19L,               620L,
                  "M20",  13L,     20L,               634L,
                  "M21",  13L,     21L,               856L,
                  "M22",  13L,     22L,               484L,
                  "M23",  13L,     23L,                94L,
                  "M24",  13L,     24L,                24L,
                  "N01",  14L,      1L,               419L,
                  "N02",  14L,      2L,                27L,
                  "N03",  14L,      3L,               627L,
                  "N04",  14L,      4L,                37L,
                  "N05",  14L,      5L,               562L,
                  "N06",  14L,      6L,               434L,
                  "N07",  14L,      7L,               593L,
                  "N08",  14L,      8L,               888L,
                  "N09",  14L,      9L,              1284L,
                  "N10",  14L,     10L,               685L,
                  "N11",  14L,     11L,               643L,
                  "N12",  14L,     12L,               485L,
                  "N13",  14L,     13L,              1001L,
                  "N14",  14L,     14L,               460L,
                  "N15",  14L,     15L,               651L,
                  "N16",  14L,     16L,               679L,
                  "N17",  14L,     17L,               757L,
                  "N18",  14L,     18L,               172L,
                  "N19",  14L,     19L,               598L,
                  "N20",  14L,     20L,                94L,
                  "N21",  14L,     21L,               639L,
                  "N22",  14L,     22L,                31L,
                  "N23",  14L,     23L,               798L,
                  "N24",  14L,     24L,                 6L,
                  "O01",  15L,      1L,               921L,
                  "O02",  15L,      2L,                37L,
                  "O03",  15L,      3L,               597L,
                  "O04",  15L,      4L,               218L,
                  "O05",  15L,      5L,                68L,
                  "O06",  15L,      6L,               700L,
                  "O07",  15L,      7L,               711L,
                  "O08",  15L,      8L,               462L,
                  "O09",  15L,      9L,               885L,
                  "O10",  15L,     10L,               569L,
                  "O11",  15L,     11L,               804L,
                  "O12",  15L,     12L,               731L,
                  "O13",  15L,     13L,               404L,
                  "O14",  15L,     14L,               321L,
                  "O15",  15L,     15L,               903L,
                  "O16",  15L,     16L,               618L,
                  "O17",  15L,     17L,               798L,
                  "O18",  15L,     18L,              1133L,
                  "O19",  15L,     19L,               735L,
                  "O20",  15L,     20L,               346L,
                  "O21",  15L,     21L,               629L,
                  "O22",  15L,     22L,                14L,
                  "O23",  15L,     23L,               255L,
                  "O24",  15L,     24L,                27L,
                  "P01",  16L,      1L,               364L,
                  "P02",  16L,      2L,                27L,
                  "P03",  16L,      3L,               939L,
                  "P04",  16L,      4L,                31L,
                  "P05",  16L,      5L,               610L,
                  "P06",  16L,      6L,                27L,
                  "P07",  16L,      7L,               955L,
                  "P08",  16L,      8L,                28L,
                  "P09",  16L,      9L,               554L,
                  "P10",  16L,     10L,                20L,
                  "P11",  16L,     11L,              1195L,
                  "P12",  16L,     12L,                41L,
                  "P13",  16L,     13L,               611L,
                  "P14",  16L,     14L,                56L,
                  "P15",  16L,     15L,              1142L,
                  "P16",  16L,     16L,                28L,
                  "P17",  16L,     17L,               795L,
                  "P18",  16L,     18L,                28L,
                  "P19",  16L,     19L,               563L,
                  "P20",  16L,     20L,                33L,
                  "P21",  16L,     21L,               693L,
                  "P22",  16L,     22L,                12L,
                  "P23",  16L,     23L,               554L,
                  "P24",  16L,     24L,                20L
                  )


Plot=ggplot(ExampleTable, aes(x=Column, y=-Row)) + theme_classic()+
  scale_x_discrete(limits=c(1:24), name="") + 
  scale_y_discrete(limits=c(-1:-16), labels=LETTERS[1:16], name="")

ggsave("/Users/youd2/Desktop/testplot1.png", Plot)
#> Saving 7 x 5 in image

Also, after tracking down, I realized that creating the "Plot" was indeed the step that was getting messed up? I ran the script below alone, saved it "Plot" as .png and compared it between the working R and my malfunctioning R.

Plot=ggplot(ExampleTable, aes(x=Column, y=-Row)) + theme_classic()+
  scale_x_discrete(limits=c(1:24), name="") + 
  scale_y_discrete(limits=c(-1:-16), labels=LETTERS[1:16], name="")

Here are the images that I got. On the left is the good example, and on the right is the one that gets generated off my R.

Not sure if these details provide more clues to what might have happened.

As you mentioned, if this is related to the package update, with breaking changes... the good example was generated from Macbook with the following versions of the packages:
ggplot2 3.2.1
tibble 2.1.3
tidyr 1.0.2
readr 1.3.1
tidyverse 1.3.0
purrr 0.3.3.
dplyr 0.8.4
stringr 1.4.0
forcats 0.5.0

R version 3.6.2
R Studio up-to-date

Not sure if this information will be helpful but wanted to at least provide the metrics so that you know where the "good example" is coming from.

If the issue is not particular to the version of the package, and from the error on my computer... due to incomplete update of packages, etc. how should I solve the problem?

Thank you!

mara · March 31, 2020, 2:42pm

What about versions of ggpubr?

dhyou21 · March 31, 2020, 2:55pm

The version of ggpubr is v 0.2.5 and when I checked for the updates, no updates seems to be available. The good, working machine also has the same ggpubr version (0.2.5).

mara · March 31, 2020, 4:04pm

Thanks. In that case, it looks like it might be a bug in ggplot2 itself. Would you mind filing the reprex as an issue?

andresrcs · March 31, 2020, 9:08pm

I get the same result with ggplot2 3.3.0 and since you were using 3.2.1 on your other setup, that might be the cause, so filing an issue seems a good idea but. In the meanwhile, you can use this alternative approach for reversing the y-axis.

library(tidyverse)

ggplot(ExampleTable, aes(x=Column, y=fct_rev(factor(-Row, labels = LETTERS[1:16])))) +
    theme_classic() +
    scale_x_discrete(limits=c(1:24), name="") +
    labs(y = "")

The "L" is there just to denote that those are integers it is not a character.

mara · April 2, 2020, 3:27pm

This was a bug that now has a patch available (I haven't read the thread much, but it's always handy to close the loop):

github.com/tidyverse/ggplot2

Discrete scale broken with negative limits

opened 04:10PM - 31 Mar 20 UTC

closed 08:45PM - 30 Apr 20 UTC

dhyou21

bug

I recently reinstalled my R/Rstudio due to the issue with one of the packages, a…nd during this process, I also (1) downloaded and installed R development tools and libraries (clang and gfortran) from https://cran.r-project.org/bin/macosx/tools/ (2) downloaded and installed gfortran compiler for R from https://github.com/fxcoudert/gfortran-for-macOS/releases/tag/6.3 (3) uninstalled Java/JDK 14 and installing Java/JDK 11 version; and (4) ran “R CMD javareconf” comman on the terminal. All of these actions were taken to resolve the error associated with one of the packages requiring Java connection. However, during theses resolution steps, something else seemed to be messed up because the existing function/package/script started working inappropriately (it worked before I tried the resolution steps above). So the problem is (and this problem is SEPARATE from the package problem that I was trying to solve with the resolution steps mentioned above): I run this script that utilizes several packages including ggplot2, tibble, dplyr, etc. to generate my graphs. Just several days ago when I tried to generate these graphs, the script worked fine (see below picture, on the left labeled as a "good example"). ![image](https://user-images.githubusercontent.com/62915812/78048637-0069e180-7348-11ea-988e-f743f2d1e092.png) But after all the resolution steps that I took as discussed above, the exact same script no longer works properly (see above picture, on the right side labeled as a "bad example" that I'm getting now). I used the exact same script, same packages to generate these graphs but now the graphs are being generated strangely…It seems like the tickmarks on the y axis are now not getting evenly spaced out throughout the whole y-axis and the problem starts at the stage where I create "Plot." Does anyone have any idea what might have gone wrong during the resolution that could have damaged R (or its associated packages) to cause this problem? I want to go back to the ggplot2 that used to create that "good example" The data that I used are basically table of different cell numbers in each well ("Number_of_Objects) in 384-well plate and I tried to depict the data using the heatmap approach as shown in the figure. The figure shows the collection of small rectangles corresponding to each well in 384-well plate and they are colored on gray gradient based on the cell density (darker, the greater density). The code that I used to plot this is: ```r library("tidyverse") library("stringr") library("ggplot2") library("ggpubr") #Table corresponds to the data table of 384-well plate that will be analyzed# Plot=ggplot(Table, aes(x=Column, y=-Row)) + theme_classic()+ scale_x_discrete(limits=c(1:24), name="") + scale_y_discrete(limits=c(-1:-16), labels=LETTERS[1:16], name="") pShape=Plot + ggtitle("Number of non-border cells") + geom_tile(aes(fill=Number_of_Objects)) + scale_fill_gradient(low = "black", high = "gray80", name="") ``` I used the exactly the same script both times and both times the script runs without any error but generates completely different graphs. How can I fix the issue so that I can go back to the "good example" graph state? During install/reinstall, some of those packages might have been updated as well. I checked the updates on all the packages that were installed and except for "tibble," which is a package that gets called along with those libraries when I load "tidyverse," everything was up-to-date. Here is the exact console output that I get when I call those libraries: ``` > library("tidyverse") ── Attaching packages ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────── tidyverse 1.3.0 ── ✓ ggplot2 3.3.0 ✓ purrr 0.3.3 ✓ tibble 2.1.3 ✓ dplyr 0.8.5 ✓ tidyr 1.0.2 ✓ stringr 1.4.0 ✓ readr 1.3.1 ✓ forcats 0.5.0 ── Conflicts ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────── tidyverse_conflicts() ── x dplyr::filter() masks stats::filter() x dplyr::lag() masks stats::lag() > library("stringr") > library("ggplot2") > library("ggpubr") Loading required package: magrittr Attaching package: ‘magrittr’ The following object is masked from ‘package:purrr’: set_names The following object is masked from ‘package:tidyr’: extract ``` I tried to create a reprex and the output is below. The example data is similar to the structure of my actual dataset - I created it using "datapasta" package's paste as tribble function. One thing to note is that on columns "row" "column" and "Number_of_Objects," there is a letter "L" after every number but it is not supposed to be there. The original sample data that I copied from Excel only contain numbers - and I don't know why "L" got added to every single number in the data. Anyhow...the thing that was strange with the reprex was that... in the rendered reprex, the image saving output was 7x5 whereas, when I actually ran the code on my R, the image was saved as 7x7 (see the last line, that says "saving 7x5 in image" - in my console, when the code was actually run, it says "Saving 7x7 in image") ``` library("tidyverse") library("stringr") library("ggplot2") library("ggpubr") #> Loading required package: magrittr #> #> Attaching package: 'magrittr' #> The following object is masked from 'package:purrr': #> #> set_names #> The following object is masked from 'package:tidyr': #> #> extract ExampleTable <- tibble::tribble( ~Well, ~Row, ~Column, ~Number_of_Objects, "A01", 1L, 1L, 532L, "A02", 1L, 2L, 400L, "A03", 1L, 3L, 875L, "A04", 1L, 4L, 573L, "A05", 1L, 5L, 970L, "A06", 1L, 6L, 626L, "A07", 1L, 7L, 1330L, "A08", 1L, 8L, 623L, "A09", 1L, 9L, 657L, "A10", 1L, 10L, 964L, "A11", 1L, 11L, 905L, "A12", 1L, 12L, 80L, "A13", 1L, 13L, 650L, "A14", 1L, 14L, 250L, "A15", 1L, 15L, 484L, "A16", 1L, 16L, 493L, "A17", 1L, 17L, 550L, "A18", 1L, 18L, 401L, "A19", 1L, 19L, 841L, "A20", 1L, 20L, 410L, "A21", 1L, 21L, 1166L, "A22", 1L, 22L, 74L, "A23", 1L, 23L, 54L, "A24", 1L, 24L, 882L, "B01", 2L, 1L, 113L, "B02", 2L, 2L, 90L, "B03", 2L, 3L, 682L, "B04", 2L, 4L, 567L, "B05", 2L, 5L, 949L, "B06", 2L, 6L, 749L, "B07", 2L, 7L, 771L, "B08", 2L, 8L, 494L, "B09", 2L, 9L, 806L, "B10", 2L, 10L, 616L, "B11", 2L, 11L, 865L, "B12", 2L, 12L, 44L, "B13", 2L, 13L, 65L, "B14", 2L, 14L, 416L, "B15", 2L, 15L, 51L, "B16", 2L, 16L, 1279L, "B17", 2L, 17L, 519L, "B18", 2L, 18L, 1017L, "B19", 2L, 19L, 763L, "B20", 2L, 20L, 212L, "B21", 2L, 21L, 763L, "B22", 2L, 22L, 435L, "B23", 2L, 23L, 532L, "B24", 2L, 24L, 227L, "C01", 3L, 1L, 714L, "C02", 3L, 2L, 851L, "C03", 3L, 3L, 530L, "C04", 3L, 4L, 1296L, "C05", 3L, 5L, 564L, "C06", 3L, 6L, 979L, "C07", 3L, 7L, 801L, "C08", 3L, 8L, 680L, "C09", 3L, 9L, 137L, "C10", 3L, 10L, 655L, "C11", 3L, 11L, 735L, "C12", 3L, 12L, 855L, "C13", 3L, 13L, 1374L, "C14", 3L, 14L, 1380L, "C15", 3L, 15L, 612L, "C16", 3L, 16L, 475L, "C17", 3L, 17L, 1241L, "C18", 3L, 18L, 358L, "C19", 3L, 19L, 731L, "C20", 3L, 20L, 666L, "C21", 3L, 21L, 943L, "C22", 3L, 22L, 1056L, "C23", 3L, 23L, 891L, "C24", 3L, 24L, 738L, "D01", 4L, 1L, 769L, "D02", 4L, 2L, 556L, "D03", 4L, 3L, 598L, "D04", 4L, 4L, 95L, "D05", 4L, 5L, 201L, "D06", 4L, 6L, 912L, "D07", 4L, 7L, 908L, "D08", 4L, 8L, 865L, "D09", 4L, 9L, 990L, "D10", 4L, 10L, 859L, "D11", 4L, 11L, 1439L, "D12", 4L, 12L, 711L, "D13", 4L, 13L, 812L, "D14", 4L, 14L, 533L, "D15", 4L, 15L, 572L, "D16", 4L, 16L, 1056L, "D17", 4L, 17L, 61L, "D18", 4L, 18L, 293L, "D19", 4L, 19L, 1071L, "D20", 4L, 20L, 839L, "D21", 4L, 21L, 830L, "D22", 4L, 22L, 562L, "D23", 4L, 23L, 75L, "D24", 4L, 24L, 5L, "E01", 5L, 1L, 585L, "E02", 5L, 2L, 751L, "E03", 5L, 3L, 134L, "E04", 5L, 4L, 1368L, "E05", 5L, 5L, 991L, "E06", 5L, 6L, 875L, "E07", 5L, 7L, 617L, "E08", 5L, 8L, 936L, "E09", 5L, 9L, 1337L, "E10", 5L, 10L, 78L, "E11", 5L, 11L, 602L, "E12", 5L, 12L, 1074L, "E13", 5L, 13L, 940L, "E14", 5L, 14L, 393L, "E15", 5L, 15L, 1157L, "E16", 5L, 16L, 1248L, "E17", 5L, 17L, 881L, "E18", 5L, 18L, 980L, "E19", 5L, 19L, 675L, "E20", 5L, 20L, 1114L, "E21", 5L, 21L, 897L, "E22", 5L, 22L, 650L, "E23", 5L, 23L, 168L, "E24", 5L, 24L, 271L, "F01", 6L, 1L, 591L, "F02", 6L, 2L, 257L, "F03", 6L, 3L, 609L, "F04", 6L, 4L, 539L, "F05", 6L, 5L, 1015L, "F06", 6L, 6L, 891L, "F07", 6L, 7L, 1063L, "F08", 6L, 8L, 972L, "F09", 6L, 9L, 927L, "F10", 6L, 10L, 1162L, "F11", 6L, 11L, 762L, "F12", 6L, 12L, 770L, "F13", 6L, 13L, 706L, "F14", 6L, 14L, 308L, "F15", 6L, 15L, 1167L, "F16", 6L, 16L, 750L, "F17", 6L, 17L, 963L, "F18", 6L, 18L, 1102L, "F19", 6L, 19L, 407L, "F20", 6L, 20L, 839L, "F21", 6L, 21L, 1047L, "F22", 6L, 22L, 815L, "F23", 6L, 23L, 609L, "F24", 6L, 24L, 65L, "G01", 7L, 1L, 130L, "G02", 7L, 2L, 435L, "G03", 7L, 3L, 823L, "G04", 7L, 4L, 291L, "G05", 7L, 5L, 1278L, "G06", 7L, 6L, 567L, "G07", 7L, 7L, 124L, "G08", 7L, 8L, 797L, "G09", 7L, 9L, 950L, "G10", 7L, 10L, 1095L, "G11", 7L, 11L, 712L, "G12", 7L, 12L, 1169L, "G13", 7L, 13L, 689L, "G14", 7L, 14L, 546L, "G15", 7L, 15L, 602L, "G16", 7L, 16L, 830L, "G17", 7L, 17L, 123L, "G18", 7L, 18L, 1222L, "G19", 7L, 19L, 989L, "G20", 7L, 20L, 1040L, "G21", 7L, 21L, 426L, "G22", 7L, 22L, 275L, "G23", 7L, 23L, 1026L, "G24", 7L, 24L, 670L, "H01", 8L, 1L, 769L, "H02", 8L, 2L, 86L, "H03", 8L, 3L, 1263L, "H04", 8L, 4L, 740L, "H05", 8L, 5L, 1445L, "H06", 8L, 6L, 607L, "H07", 8L, 7L, 173L, "H08", 8L, 8L, 1390L, "H09", 8L, 9L, 749L, "H10", 8L, 10L, 940L, "H11", 8L, 11L, 669L, "H12", 8L, 12L, 746L, "H13", 8L, 13L, 787L, "H14", 8L, 14L, 604L, "H15", 8L, 15L, 912L, "H16", 8L, 16L, 742L, "H17", 8L, 17L, 119L, "H18", 8L, 18L, 995L, "H19", 8L, 19L, 1027L, "H20", 8L, 20L, 745L, "H21", 8L, 21L, 358L, "H22", 8L, 22L, 119L, "H23", 8L, 23L, 221L, "H24", 8L, 24L, 15L, "I01", 9L, 1L, 295L, "I02", 9L, 2L, 682L, "I03", 9L, 3L, 879L, "I04", 9L, 4L, 847L, "I05", 9L, 5L, 735L, "I06", 9L, 6L, 760L, "I07", 9L, 7L, 948L, "I08", 9L, 8L, 736L, "I09", 9L, 9L, 1225L, "I10", 9L, 10L, 1333L, "I11", 9L, 11L, 743L, "I12", 9L, 12L, 713L, "I13", 9L, 13L, 637L, "I14", 9L, 14L, 652L, "I15", 9L, 15L, 838L, "I16", 9L, 16L, 783L, "I17", 9L, 17L, 910L, "I18", 9L, 18L, 766L, "I19", 9L, 19L, 496L, "I20", 9L, 20L, 992L, "I21", 9L, 21L, 1291L, "I22", 9L, 22L, 1475L, "I23", 9L, 23L, 121L, "I24", 9L, 24L, 484L, "J01", 10L, 1L, 620L, "J02", 10L, 2L, 110L, "J03", 10L, 3L, 425L, "J04", 10L, 4L, 889L, "J05", 10L, 5L, 659L, "J06", 10L, 6L, 745L, "J07", 10L, 7L, 840L, "J08", 10L, 8L, 721L, "J09", 10L, 9L, 818L, "J10", 10L, 10L, 601L, "J11", 10L, 11L, 711L, "J12", 10L, 12L, 772L, "J13", 10L, 13L, 890L, "J14", 10L, 14L, 771L, "J15", 10L, 15L, 938L, "J16", 10L, 16L, 518L, "J17", 10L, 17L, 905L, "J18", 10L, 18L, 784L, "J19", 10L, 19L, 906L, "J20", 10L, 20L, 59L, "J21", 10L, 21L, 819L, "J22", 10L, 22L, 544L, "J23", 10L, 23L, 588L, "J24", 10L, 24L, 29L, "K01", 11L, 1L, 1008L, "K02", 11L, 2L, 660L, "K03", 11L, 3L, 1009L, "K04", 11L, 4L, 581L, "K05", 11L, 5L, 902L, "K06", 11L, 6L, 639L, "K07", 11L, 7L, 1322L, "K08", 11L, 8L, 903L, "K09", 11L, 9L, 807L, "K10", 11L, 10L, 1150L, "K11", 11L, 11L, 956L, "K12", 11L, 12L, 879L, "K13", 11L, 13L, 106L, "K14", 11L, 14L, 624L, "K15", 11L, 15L, 840L, "K16", 11L, 16L, 840L, "K17", 11L, 17L, 679L, "K18", 11L, 18L, 711L, "K19", 11L, 19L, 569L, "K20", 11L, 20L, 1043L, "K21", 11L, 21L, 751L, "K22", 11L, 22L, 724L, "K23", 11L, 23L, 646L, "K24", 11L, 24L, 1000L, "L01", 12L, 1L, 567L, "L02", 12L, 2L, 22L, "L03", 12L, 3L, 916L, "L04", 12L, 4L, 538L, "L05", 12L, 5L, 984L, "L06", 12L, 6L, 663L, "L07", 12L, 7L, 679L, "L08", 12L, 8L, 488L, "L09", 12L, 9L, 853L, "L10", 12L, 10L, 855L, "L11", 12L, 11L, 791L, "L12", 12L, 12L, 1297L, "L13", 12L, 13L, 1340L, "L14", 12L, 14L, 741L, "L15", 12L, 15L, 1075L, "L16", 12L, 16L, 725L, "L17", 12L, 17L, 735L, "L18", 12L, 18L, 677L, "L19", 12L, 19L, 460L, "L20", 12L, 20L, 287L, "L21", 12L, 21L, 1044L, "L22", 12L, 22L, 27L, "L23", 12L, 23L, 601L, "L24", 12L, 24L, 28L, "M01", 13L, 1L, 126L, "M02", 13L, 2L, 784L, "M03", 13L, 3L, 850L, "M04", 13L, 4L, 580L, "M05", 13L, 5L, 1085L, "M06", 13L, 6L, 794L, "M07", 13L, 7L, 879L, "M08", 13L, 8L, 121L, "M09", 13L, 9L, 901L, "M10", 13L, 10L, 589L, "M11", 13L, 11L, 695L, "M12", 13L, 12L, 605L, "M13", 13L, 13L, 691L, "M14", 13L, 14L, 302L, "M15", 13L, 15L, 878L, "M16", 13L, 16L, 682L, "M17", 13L, 17L, 666L, "M18", 13L, 18L, 1191L, "M19", 13L, 19L, 620L, "M20", 13L, 20L, 634L, "M21", 13L, 21L, 856L, "M22", 13L, 22L, 484L, "M23", 13L, 23L, 94L, "M24", 13L, 24L, 24L, "N01", 14L, 1L, 419L, "N02", 14L, 2L, 27L, "N03", 14L, 3L, 627L, "N04", 14L, 4L, 37L, "N05", 14L, 5L, 562L, "N06", 14L, 6L, 434L, "N07", 14L, 7L, 593L, "N08", 14L, 8L, 888L, "N09", 14L, 9L, 1284L, "N10", 14L, 10L, 685L, "N11", 14L, 11L, 643L, "N12", 14L, 12L, 485L, "N13", 14L, 13L, 1001L, "N14", 14L, 14L, 460L, "N15", 14L, 15L, 651L, "N16", 14L, 16L, 679L, "N17", 14L, 17L, 757L, "N18", 14L, 18L, 172L, "N19", 14L, 19L, 598L, "N20", 14L, 20L, 94L, "N21", 14L, 21L, 639L, "N22", 14L, 22L, 31L, "N23", 14L, 23L, 798L, "N24", 14L, 24L, 6L, "O01", 15L, 1L, 921L, "O02", 15L, 2L, 37L, "O03", 15L, 3L, 597L, "O04", 15L, 4L, 218L, "O05", 15L, 5L, 68L, "O06", 15L, 6L, 700L, "O07", 15L, 7L, 711L, "O08", 15L, 8L, 462L, "O09", 15L, 9L, 885L, "O10", 15L, 10L, 569L, "O11", 15L, 11L, 804L, "O12", 15L, 12L, 731L, "O13", 15L, 13L, 404L, "O14", 15L, 14L, 321L, "O15", 15L, 15L, 903L, "O16", 15L, 16L, 618L, "O17", 15L, 17L, 798L, "O18", 15L, 18L, 1133L, "O19", 15L, 19L, 735L, "O20", 15L, 20L, 346L, "O21", 15L, 21L, 629L, "O22", 15L, 22L, 14L, "O23", 15L, 23L, 255L, "O24", 15L, 24L, 27L, "P01", 16L, 1L, 364L, "P02", 16L, 2L, 27L, "P03", 16L, 3L, 939L, "P04", 16L, 4L, 31L, "P05", 16L, 5L, 610L, "P06", 16L, 6L, 27L, "P07", 16L, 7L, 955L, "P08", 16L, 8L, 28L, "P09", 16L, 9L, 554L, "P10", 16L, 10L, 20L, "P11", 16L, 11L, 1195L, "P12", 16L, 12L, 41L, "P13", 16L, 13L, 611L, "P14", 16L, 14L, 56L, "P15", 16L, 15L, 1142L, "P16", 16L, 16L, 28L, "P17", 16L, 17L, 795L, "P18", 16L, 18L, 28L, "P19", 16L, 19L, 563L, "P20", 16L, 20L, 33L, "P21", 16L, 21L, 693L, "P22", 16L, 22L, 12L, "P23", 16L, 23L, 554L, "P24", 16L, 24L, 20L ) Plot=ggplot(ExampleTable, aes(x=Column, y=-Row)) + theme_classic()+ scale_x_discrete(limits=c(1:24), name="") + scale_y_discrete(limits=c(-1:-16), labels=LETTERS[1:16], name="") ggsave("/Users/youd2/Desktop/testplot1.png", Plot) #> Saving 7 x 5 in image ``` Also, after tracking down, I realized that creating the "Plot" was indeed the step that was getting messed up? I ran the script below alone, saved it "Plot" as .png and compared it between the working R and my malfunctioning R. ``` Plot=ggplot(ExampleTable, aes(x=Column, y=-Row)) + theme_classic()+ scale_x_discrete(limits=c(1:24), name="") + scale_y_discrete(limits=c(-1:-16), labels=LETTERS[1:16], name="") ``` Here are the images that I got. On the left is the good example, and on the right is the one that gets generated off my R. ![image|690x390](upload://yyV56eQBeTMeOEGyqN25d3aXVRQ.png) ![image](https://user-images.githubusercontent.com/62915812/78048825-4d4db800-7348-11ea-8a9f-0b3effe16c0a.png) Not sure if these details provide more clues to what might have happened. If this is related to the package update, with breaking changes... the good example was generated from Macbook with the following versions of the packages: ggplot2 3.2.1 tibble 2.1.3 tidyr 1.0.2 readr 1.3.1 tidyverse 1.3.0 purrr 0.3.3. dplyr 0.8.4 stringr 1.4.0 forcats 0.5.0 R version 3.6.2 R Studio up-to-date Not sure if this information will be helpful but wanted to at least provide the metrics so that you know where the "good example" is coming from. Again, my malfunctioning machine also used to perform well exactly as this Macbook which generated the "good example." I understand that the problem can be anything here. If it is indeed the error due to installing different compilers, do I have to uninstall those as well (how can I figure this out)? I thought that the compilers will also be uninstalled when I uninstall the R but is that not the case? Do I have to go through uninstall/reinstall of Java as well? Can "R CMD javareconf" mess up the defaults on ggplot2? What are some commands that I can check on terminal to find a potential bug that I'm having with ggplot2? If this is related to the package update error, what could solve the problem? I already tried uninstalling/reinstalling all the packages used in this script and that didn’t solve the problem. If the issue is not particular to the version of the package, and from the error on my computer... due to incomplete update of packages, etc. how should I solve the problem? I wanted to bring this up as an issue in case this is a bug inherent to ggplot2. Thank you!

system · April 23, 2020, 3:28pm

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