I have different categorical variable which I would like to show in terms of distribution.
So in my data-frame I have like 147 patients and their traits such as age,gender,disease subtypes etc etc.
This is my dataframe subset
head(plot_meta)
patient Sex FAB Diagnosis-Age Bone-Marrow-Blast-Percentage Cytogenetics
1 TCGA-AB-2856 Male M4 63 82 46,XY[20]
2 TCGA-AB-2849 Male M0 39 83 47,XY,del(5)(q22q33),t(10;11)(p13~p15;q22~23),i(17)(q10)[3]/46,XY[17]
3 TCGA-AB-2971 Female M4 76 91 46,XX[20]
4 TCGA-AB-2930 Female M2 62 72 46, XX[20]
5 TCGA-AB-2891 Male M1 42 68 45,XY,der(7)(t:7;12)(p11.1;p11.2),-12,-13, mar[19]/46,XY[1]
6 TCGA-AB-2872 Male M3 42 88 46,XY,del(9)(q13:q22),t(11:21)(p13;q22),t(15;17)(q22;q210[20]
Cytogenetic-Code--Other- Induction
1 Normal Karyotype 7 3 Genasense
2 Complex Cytogenetics 7 3 3
3 Normal Karyotype 7 3
4 Normal Karyotype 7 3 AMD
5 Complex Cytogenetics 7 3 3
6 PML-RARA 7 3 ATRA
So my goal is to show the patient traits distribution as the above figure.
a <- dput(head(plot_meta))
structure(list(patient = structure(c(36L, 33L, 122L, 95L, 66L,
49L), .Label = c("TCGA-AB-2805", "TCGA-AB-2806", "TCGA-AB-2808",
"TCGA-AB-2810", "TCGA-AB-2811", "TCGA-AB-2812", "TCGA-AB-2813",
"TCGA-AB-2814", "TCGA-AB-2815", "TCGA-AB-2817", "TCGA-AB-2818",
"TCGA-AB-2819", "TCGA-AB-2820", "TCGA-AB-2821", "TCGA-AB-2822",
"TCGA-AB-2823", "TCGA-AB-2825", "TCGA-AB-2826", "TCGA-AB-2828",
"TCGA-AB-2830", "TCGA-AB-2834", "TCGA-AB-2835", "TCGA-AB-2836",
"TCGA-AB-2839", "TCGA-AB-2840", "TCGA-AB-2841", "TCGA-AB-2842",
"TCGA-AB-2843", "TCGA-AB-2844", "TCGA-AB-2845", "TCGA-AB-2846",
"TCGA-AB-2847", "TCGA-AB-2849", "TCGA-AB-2851", "TCGA-AB-2853",
"TCGA-AB-2856", "TCGA-AB-2857", "TCGA-AB-2858", "TCGA-AB-2859",
"TCGA-AB-2861", "TCGA-AB-2862", "TCGA-AB-2863", "TCGA-AB-2865",
"TCGA-AB-2866", "TCGA-AB-2867", "TCGA-AB-2869", "TCGA-AB-2870",
"TCGA-AB-2871", "TCGA-AB-2872", "TCGA-AB-2873", "TCGA-AB-2874",
"TCGA-AB-2875", "TCGA-AB-2876", "TCGA-AB-2877", "TCGA-AB-2878",
"TCGA-AB-2880", "TCGA-AB-2881", "TCGA-AB-2882", "TCGA-AB-2883",
"TCGA-AB-2884", "TCGA-AB-2885", "TCGA-AB-2886", "TCGA-AB-2888",
"TCGA-AB-2889", "TCGA-AB-2890", "TCGA-AB-2891", "TCGA-AB-2892",
"TCGA-AB-2893", "TCGA-AB-2894", "TCGA-AB-2895", "TCGA-AB-2896",
"TCGA-AB-2897", "TCGA-AB-2898", "TCGA-AB-2899", "TCGA-AB-2900",
"TCGA-AB-2901", "TCGA-AB-2908", "TCGA-AB-2910", "TCGA-AB-2911",
"TCGA-AB-2912", "TCGA-AB-2913", "TCGA-AB-2914", "TCGA-AB-2915",
"TCGA-AB-2916", "TCGA-AB-2917", "TCGA-AB-2918", "TCGA-AB-2919",
"TCGA-AB-2920", "TCGA-AB-2921", "TCGA-AB-2924", "TCGA-AB-2925",
"TCGA-AB-2927", "TCGA-AB-2928", "TCGA-AB-2929", "TCGA-AB-2930",
"TCGA-AB-2931", "TCGA-AB-2932", "TCGA-AB-2933", "TCGA-AB-2934",
"TCGA-AB-2935", "TCGA-AB-2936", "TCGA-AB-2937", "TCGA-AB-2938",
"TCGA-AB-2939", "TCGA-AB-2940", "TCGA-AB-2941", "TCGA-AB-2942",
"TCGA-AB-2943", "TCGA-AB-2944", "TCGA-AB-2946", "TCGA-AB-2948",
"TCGA-AB-2949", "TCGA-AB-2950", "TCGA-AB-2952", "TCGA-AB-2955",
"TCGA-AB-2956", "TCGA-AB-2959", "TCGA-AB-2963", "TCGA-AB-2965",
"TCGA-AB-2966", "TCGA-AB-2970", "TCGA-AB-2971", "TCGA-AB-2973",
"TCGA-AB-2975", "TCGA-AB-2976", "TCGA-AB-2977", "TCGA-AB-2979",
"TCGA-AB-2980", "TCGA-AB-2981", "TCGA-AB-2982", "TCGA-AB-2983",
"TCGA-AB-2984", "TCGA-AB-2986", "TCGA-AB-2987", "TCGA-AB-2988",
"TCGA-AB-2990", "TCGA-AB-2991", "TCGA-AB-2992", "TCGA-AB-2994",
"TCGA-AB-2995", "TCGA-AB-2996", "TCGA-AB-2998", "TCGA-AB-2999",
"TCGA-AB-3000", "TCGA-AB-3001", "TCGA-AB-3002", "TCGA-AB-3007",
"TCGA-AB-3008", "TCGA-AB-3009", "TCGA-AB-3011", "TCGA-AB-3012"
), class = "factor"), Sex = structure(c(2L, 2L, 1L, 1L, 2L, 2L
), .Label = c("Female", "Male"), class = "factor"), FAB = structure(c(5L,
1L, 5L, 3L, 2L, 4L), .Label = c("M0", "M1", "M2", "M3", "M4",
"M5", "M6", "M7", "nc"), class = "factor"), `Diagnosis-Age` = c(63L,
39L, 76L, 62L, 42L, 42L), `Bone-Marrow-Blast-Percentage` = c(82L,
83L, 91L, 72L, 68L, 88L), Cytogenetics = structure(c(75L, 93L,
51L, 27L, 21L, 57L), .Label = c("37~49,XY, Y,der(1)add(1)(p13)del(1)(q21q25),-5,der(7)inv(7)(p15q11.2)?inv(7)(q22q32), 17,add(17)(p13), 21, mar[cp20]",
"39~47,XX,del(5)(q13q33),-7,der(8)t(8;?8;8)(p23;?p11.2p23;q11.2),der(14)t(1;14)(p12;p11.2)der(1)t(7;16)(p15;q22), 2mar[cp19]",
"41~44,X,?i(X)(p10),-7,der(12)t(8;12)(q11.2;p11.2),-8 [cp11]/46,XX[8[",
"42,XY,-5,-7,add(12)(p13),t(14;15)(q10;q10),der(17)t(5;17)(p13;p11.2),-18[6]/40,idem,-11,-add(12)(p13),der(12)t(?;12)(?;p13),-19[6]/41,idem,-der(17)[3]/41,idem,-der(17), mar1, mar[3]/41,idem,der(1)der(1)(p12)add(1)(p12), der(1)(q21)add(1)(q21),-3,-8[2]",
"43,XY-3,del(5)(q12q33),-7,der(10)t(10;11)(q26;q13),-12,-18, 2mar[20]",
"44-45,X,-Y,-5,add(16)(q22),-17,-18,iso(21), mars[cp5]/82-84,XX,-Y,-3,-4,-11,-12,-19,-21, 21[cp5}",
"44~46,XX,del(11)(q23),der(19)?t(11;19)(q23;p13.1)[cp11]/44~45,XX,-19[cp4]/46,XX [5]",
"44~47,XX,t(1;15)(q32;q26)[14],del(5)(q13q33)[19],-7[20], 8[7],del(12)(p11.2p11.2)[15],del(17)(q21)[8],der(22)t(1;22)(p13;p11.2)[20], mar[13][cp20]",
"44~47,XY,del(5)(q22q35)[20],-7[14],-8[6],der(12)t(10;12)(p11.2q21)[2],add(14)(p12)[11],-17[13],der(17)t(10;17)(q11.2;p13)[14],-18[7],add(18)(p11.2)[7],-21[10],i(21)(q10)[4],-22[4], mar[10], mar1x2[6][cp20]",
"45,X,-X,t(8;21)(q22;q22)[20]", "45,X,-Y, t(8;7;21)(q22;p15;q22[22]/46,XY[3]",
"45,X,-Y,t(8;21)(q22;q22)[13]/45,idem,del(9)(q22;q32)[7]", "45,X,-Y,t(8;21)(q22;q22)[19]/46,XY[1]",
"45,X,-Y[3]/46,XY [17]", "45,XX-7[5]-only 5 metaphases", "45,XX,-7,t(9;11)(p22;q23)[19]/46,XX[1]",
"45,XX,-7[12]/46,XX[8]", "45,XX,-7[20]", "45,XY,-7, t(9;22)(q34;q11.20) [19]/46,XY[1]",
"45,XY,-7[20]", "45,XY,der(7)(t:7;12)(p11.1;p11.2),-12,-13, mar[19]/46,XY[1]",
"45~46,XY,add(X)(q22)[7],Y[4],der(5)t(5;17)(q13;21)[18],-7[18], 8[17],del(12)(q23)[16],-17[18],add(18)(p11.2)[14][cp18]",
"46, XX[14]", "46, XX[15]", "46, XX[16]", "46, XX[19]", "46, XX[20]",
"46, XY[15]", "46, XY[20]", "46,XX,1~50dmin[12]/46,idem,der(6)t(6;?)(q22;?)[2]/46,XX[6]",
"46,XX,9qh [20]", "46,XX,del(3)(q23q26.2),der(7)t(1:7)(q32;q32),del(10)(q22q25),t(13;16)(q34;p11.2)dup(21)(q22)[cp20]",
"46,XX,del(5)(q11.2q33)[1]/48~52,idem, 1, ?del(5)(q15q33), 11, 11,?t(12;22)(p13;q12),-13,-17, i(22)(q10), i(22)(q10), mar[cp19]",
"46,XX,del(5)(q22q33)[4]/46,XX[16]", "46,XX,i(17)(q10)[1]/45,sl-7[2]/48,sl, 13, 19[3]/46,XX[15]",
"46,XX,inv(16)(p13q22)[15]/46,XX[2]", "46,XX,inv(16)(p13q22)[19]/46,XX[1]",
"46,XX,inv(16)(p13q22)[20]", "46,XX,inv(16)(p13q22)[5]/46,idem,t(3;3)(p13;q?28)[5]/46,XX[6]",
"46,XX,t(15;17)(q22;q21.1)[19]/47,idem, 8 [1]", "46,XX,t(15;17)(q22;q21),t(16;19)(p13.3;p13.1)[17]/46,XX[3]",
"46,XX,t(15;17)(q22;q21)[11]/46,XX[9]", "46,XX,t(15;17)(q22;q21)[12]/46,XX[8]",
"46,XX,t(15;17)(q22;q21)[20]", "46,XX,t(8;21)(q22;q22)[17]/46,XX[3]",
"46,XX,t(8;21)(q22;q22)[20]", "46,XX,t(8;21)[15]/46,idem,del(9)(q12q22)[5]",
"46,XX[15]", "46,XX[18]", "46,XX[19]/46,XX,add(7)(p?22)[1]",
"46,XX[20]", "46,XX 13,21[cp17]/46,XX[3]", "46,XY,9qh [19]",
"46,XY,del(11)(p12)[2]/46,XY[18]", "46,XY,del(20)(q11.2)[23]/92,XXYY,del(20)(q11.2)x2[2]/46,XY[3]",
"46,XY,del(7)(q21q36)[18]/46,XY[2]", "46,XY,del(9)(q13:q22),t(11:21)(p13;q22),t(15;17)(q22;q210[20]",
"46,XY,i(17)(q10)[15]/47,XY,idem 13[3]/46,XY[2]", "46,XY,inv(16)(p13;q22)[20]",
"46,XY,inv(16)(p13q22)[17]/46,XY[3]", "46,XY,inv(16)(p13q22)[9]/46,XY[10]",
"46,XY,t(11;19)(q23;p13)[17]/46,XY,t(11;19)(q23;p13),inv(12)(p12p13)[3]",
"46,XY,t(11;19)(q23;p13)[20]", "46,XY,t(15;17)(q22;q21)[19]/46,XY[1]",
"46,XY,t(15;17)(q22;q21)[20]", "46,XY,t(15;17)(q22:q21)[11]/46,XY[9]",
"46,XY,t(2;4)(q34;q21)inv(16)(p13q22) [20]", "46,XY,t(6;11)(q27;q23)[15]",
"46,XY,t(9;11)(p22;q23)[7]/47,XY,t(9;11)(p22;q23)[7]/46,XY[4]",
"46,XY,t(9;22)(q34;q11.2)[13]/34~37,idem,-3,del(4),-4,-5,-7,-9,-10,t?(11;12),-12,-14,-14,-16,-17,-22[cp6]/46,XY[1]",
"46,XY,t(9;22)(q34;q11.2[4]/50,idem, 8, 10, 21, der(22)(t(9;22)(q34;q11.2)[16]",
"46,XY[13]", "46,XY[15]", "46,XY[19]", "46,XY[20]", "46,XY[30]",
"46~49,XY,del(3)(p14),del(5)(p11.2q33),del(17)(q21q21),add(21)(p11.2), 22,mar[cp20]",
"47,XX, der(5)t(2;5)(p11.2;q11.2)?,t(8;16)(p11.2;p13.3)[19]",
"47,XX,i(11)(q10)[18]/46,XX [2]", "47,XX,t(15;17)(q22:q21) mar[20]",
"47,XX 11 [20]", "47,XX 8 [20]", "47,XXY [17]", "47,XY, 13[5]/46,XY[15]",
"47,XY, 21 [6]/46,XY[13]", "47,XY, 21[11]/48,XY, 3, 21[8]", "47,XY, 22[10]/47,XY, 8[7]/45,XY,del(3)(p21),del(4)(p12p15),-7,?dup(7)(q11.2q36)[3]",
"47,XY, 8 [10]/46,XY [10]", "47,XY, 8 [19]", "47,XY, 8 [20]",
"47,XY, 8[15]/46, 8,-17[3]", "47,XY, 9[10]/46,XY[10]", "47,XY,del(5)(q22q33),t(10;11)(p13~p15;q22~23),i(17)(q10)[3]/46,XY[17]",
"47,XY,del(7)(q22), 8,t(15;17)(q22;q21)[18]/46,XY,del(7)(q22),t(15;17)(q22;q21)[2]",
"47,XY 8 [15]/48,XY 8 8[4]/46,XY[1]", "48,XY, 8, 8[16]/46,XY[4]",
"52~54,XY, 2, 4, 6, 8,del(11)(q23), 19, 19, 21[17]/46,XY[3]",
"53~56,XY, 1,del(2)(q33q34), 8, 10, 11x2, 13x1-2, 14,del(17)(p11.2), 19,add(21)(q22), 22[cp20]",
"incomplete-46,XY,del(12)(p11.20[2]/46,XY[3]", "N.D.", "ND",
"Outside hospital with inv(16)"), class = "factor"), `Cytogenetic-Code--Other-` = structure(c(8L,
3L, 8L, 8L, 3L, 9L), .Label = c("BCR-ABL1", "CBFB-MYH11", "Complex Cytogenetics",
"Intermediate Risk Cytogenetic Abnormality", "MLL translocation, poor risk",
"MLL translocation, t(9;11)", "N.D.", "Normal Karyotype", "PML-RARA",
"Poor Risk Cytogenetic Abnormality", "RUNX1-RUNX1T1"), class = "factor"),
Induction = structure(c(11L, 4L, 1L, 8L, 4L, 9L), .Label = c("7 3",
"7 3, dauna", "7 3, IT", "7 3 3", "7 3 3, gleevec", "7 3 3, then 5 2 2",
"7 3 3 PSC", "7 3 AMD", "7 3 ATRA", "7 3 dauno", "7 3 Genasense",
"7 3 study drug", "7 4 ATRA", "Azacitidine", "CLAM", "Cytarabine only",
"Decitabine", "Decitabine then 7 3", "Hydrea & Idarubicin",
"Hydrea, ATRA started", "hydrea, didn't get add'l chemo",
"LBH/Decitabine", "low dose Ara C", "no treatment", "Revlimid",
"Revlmd then Decitbne,7 3,5 2"), class = "factor")), row.names = c(NA,
6L), class = "data.frame")
My attempt so far
df <- plot_meta %>% group_by(patient) %>% count(Sex,FAB,`Diagnosis-Age`) %>% mutate(Percent = n / sum(n)*100)
head(df)
ggplot(df, aes(x = Sex, y = Percent, fill = FAB))
geom_bar(stat = "identity")
geom_text(aes(label = paste(Percent,"%"), y = Percent),
position = position_stack(vjust = 0.5))
coord_flip()
labs(x = "Sex", y = "Percentage",fill = "FAB")
The figure Im getting is this
How do I incorporate other variables distribution in the same plot as above? I would like to add the percentage scale on the axis such that a common percent scale for all the variables is there on one axis.
Any help or suggestion would be really appreciated
CodePudding user response：
library(tidyverse)
plot_meta <- structure(list(
patient = structure(c(
36L, 33L, 122L, 95L, 66L,
49L
), .Label = c(
"TCGA-AB-2805", "TCGA-AB-2806", "TCGA-AB-2808",
"TCGA-AB-2810", "TCGA-AB-2811", "TCGA-AB-2812", "TCGA-AB-2813",
"TCGA-AB-2814", "TCGA-AB-2815", "TCGA-AB-2817", "TCGA-AB-2818",
"TCGA-AB-2819", "TCGA-AB-2820", "TCGA-AB-2821", "TCGA-AB-2822",
"TCGA-AB-2823", "TCGA-AB-2825", "TCGA-AB-2826", "TCGA-AB-2828",
"TCGA-AB-2830", "TCGA-AB-2834", "TCGA-AB-2835", "TCGA-AB-2836",
"TCGA-AB-2839", "TCGA-AB-2840", "TCGA-AB-2841", "TCGA-AB-2842",
"TCGA-AB-2843", "TCGA-AB-2844", "TCGA-AB-2845", "TCGA-AB-2846",
"TCGA-AB-2847", "TCGA-AB-2849", "TCGA-AB-2851", "TCGA-AB-2853",
"TCGA-AB-2856", "TCGA-AB-2857", "TCGA-AB-2858", "TCGA-AB-2859",
"TCGA-AB-2861", "TCGA-AB-2862", "TCGA-AB-2863", "TCGA-AB-2865",
"TCGA-AB-2866", "TCGA-AB-2867", "TCGA-AB-2869", "TCGA-AB-2870",
"TCGA-AB-2871", "TCGA-AB-2872", "TCGA-AB-2873", "TCGA-AB-2874",
"TCGA-AB-2875", "TCGA-AB-2876", "TCGA-AB-2877", "TCGA-AB-2878",
"TCGA-AB-2880", "TCGA-AB-2881", "TCGA-AB-2882", "TCGA-AB-2883",
"TCGA-AB-2884", "TCGA-AB-2885", "TCGA-AB-2886", "TCGA-AB-2888",
"TCGA-AB-2889", "TCGA-AB-2890", "TCGA-AB-2891", "TCGA-AB-2892",
"TCGA-AB-2893", "TCGA-AB-2894", "TCGA-AB-2895", "TCGA-AB-2896",
"TCGA-AB-2897", "TCGA-AB-2898", "TCGA-AB-2899", "TCGA-AB-2900",
"TCGA-AB-2901", "TCGA-AB-2908", "TCGA-AB-2910", "TCGA-AB-2911",
"TCGA-AB-2912", "TCGA-AB-2913", "TCGA-AB-2914", "TCGA-AB-2915",
"TCGA-AB-2916", "TCGA-AB-2917", "TCGA-AB-2918", "TCGA-AB-2919",
"TCGA-AB-2920", "TCGA-AB-2921", "TCGA-AB-2924", "TCGA-AB-2925",
"TCGA-AB-2927", "TCGA-AB-2928", "TCGA-AB-2929", "TCGA-AB-2930",
"TCGA-AB-2931", "TCGA-AB-2932", "TCGA-AB-2933", "TCGA-AB-2934",
"TCGA-AB-2935", "TCGA-AB-2936", "TCGA-AB-2937", "TCGA-AB-2938",
"TCGA-AB-2939", "TCGA-AB-2940", "TCGA-AB-2941", "TCGA-AB-2942",
"TCGA-AB-2943", "TCGA-AB-2944", "TCGA-AB-2946", "TCGA-AB-2948",
"TCGA-AB-2949", "TCGA-AB-2950", "TCGA-AB-2952", "TCGA-AB-2955",
"TCGA-AB-2956", "TCGA-AB-2959", "TCGA-AB-2963", "TCGA-AB-2965",
"TCGA-AB-2966", "TCGA-AB-2970", "TCGA-AB-2971", "TCGA-AB-2973",
"TCGA-AB-2975", "TCGA-AB-2976", "TCGA-AB-2977", "TCGA-AB-2979",
"TCGA-AB-2980", "TCGA-AB-2981", "TCGA-AB-2982", "TCGA-AB-2983",
"TCGA-AB-2984", "TCGA-AB-2986", "TCGA-AB-2987", "TCGA-AB-2988",
"TCGA-AB-2990", "TCGA-AB-2991", "TCGA-AB-2992", "TCGA-AB-2994",
"TCGA-AB-2995", "TCGA-AB-2996", "TCGA-AB-2998", "TCGA-AB-2999",
"TCGA-AB-3000", "TCGA-AB-3001", "TCGA-AB-3002", "TCGA-AB-3007",
"TCGA-AB-3008", "TCGA-AB-3009", "TCGA-AB-3011", "TCGA-AB-3012"
), class = "factor"), Sex = structure(c(2L, 2L, 1L, 1L, 2L, 2L), .Label = c("Female", "Male"), class = "factor"), FAB = structure(c(
5L,
1L, 5L, 3L, 2L, 4L
), .Label = c(
"M0", "M1", "M2", "M3", "M4",
"M5", "M6", "M7", "nc"
), class = "factor"), `Diagnosis-Age` = c(
63L,
39L, 76L, 62L, 42L, 42L
), `Bone-Marrow-Blast-Percentage` = c(
82L,
83L, 91L, 72L, 68L, 88L
), Cytogenetics = structure(c(
75L, 93L,
51L, 27L, 21L, 57L
), .Label = c(
"37~49,XY, Y,der(1)add(1)(p13)del(1)(q21q25),-5,der(7)inv(7)(p15q11.2)?inv(7)(q22q32), 17,add(17)(p13), 21, mar[cp20]",
"39~47,XX,del(5)(q13q33),-7,der(8)t(8;?8;8)(p23;?p11.2p23;q11.2),der(14)t(1;14)(p12;p11.2)der(1)t(7;16)(p15;q22), 2mar[cp19]",
"41~44,X,?i(X)(p10),-7,der(12)t(8;12)(q11.2;p11.2),-8 [cp11]/46,XX[8[",
"42,XY,-5,-7,add(12)(p13),t(14;15)(q10;q10),der(17)t(5;17)(p13;p11.2),-18[6]/40,idem,-11,-add(12)(p13),der(12)t(?;12)(?;p13),-19[6]/41,idem,-der(17)[3]/41,idem,-der(17), mar1, mar[3]/41,idem,der(1)der(1)(p12)add(1)(p12), der(1)(q21)add(1)(q21),-3,-8[2]",
"43,XY-3,del(5)(q12q33),-7,der(10)t(10;11)(q26;q13),-12,-18, 2mar[20]",
"44-45,X,-Y,-5,add(16)(q22),-17,-18,iso(21), mars[cp5]/82-84,XX,-Y,-3,-4,-11,-12,-19,-21, 21[cp5}",
"44~46,XX,del(11)(q23),der(19)?t(11;19)(q23;p13.1)[cp11]/44~45,XX,-19[cp4]/46,XX [5]",
"44~47,XX,t(1;15)(q32;q26)[14],del(5)(q13q33)[19],-7[20], 8[7],del(12)(p11.2p11.2)[15],del(17)(q21)[8],der(22)t(1;22)(p13;p11.2)[20], mar[13][cp20]",
"44~47,XY,del(5)(q22q35)[20],-7[14],-8[6],der(12)t(10;12)(p11.2q21)[2],add(14)(p12)[11],-17[13],der(17)t(10;17)(q11.2;p13)[14],-18[7],add(18)(p11.2)[7],-21[10],i(21)(q10)[4],-22[4], mar[10], mar1x2[6][cp20]",
"45,X,-X,t(8;21)(q22;q22)[20]", "45,X,-Y, t(8;7;21)(q22;p15;q22[22]/46,XY[3]",
"45,X,-Y,t(8;21)(q22;q22)[13]/45,idem,del(9)(q22;q32)[7]", "45,X,-Y,t(8;21)(q22;q22)[19]/46,XY[1]",
"45,X,-Y[3]/46,XY [17]", "45,XX-7[5]-only 5 metaphases", "45,XX,-7,t(9;11)(p22;q23)[19]/46,XX[1]",
"45,XX,-7[12]/46,XX[8]", "45,XX,-7[20]", "45,XY,-7, t(9;22)(q34;q11.20) [19]/46,XY[1]",
"45,XY,-7[20]", "45,XY,der(7)(t:7;12)(p11.1;p11.2),-12,-13, mar[19]/46,XY[1]",
"45~46,XY,add(X)(q22)[7],Y[4],der(5)t(5;17)(q13;21)[18],-7[18], 8[17],del(12)(q23)[16],-17[18],add(18)(p11.2)[14][cp18]",
"46, XX[14]", "46, XX[15]", "46, XX[16]", "46, XX[19]", "46, XX[20]",
"46, XY[15]", "46, XY[20]", "46,XX,1~50dmin[12]/46,idem,der(6)t(6;?)(q22;?)[2]/46,XX[6]",
"46,XX,9qh [20]", "46,XX,del(3)(q23q26.2),der(7)t(1:7)(q32;q32),del(10)(q22q25),t(13;16)(q34;p11.2)dup(21)(q22)[cp20]",
"46,XX,del(5)(q11.2q33)[1]/48~52,idem, 1, ?del(5)(q15q33), 11, 11,?t(12;22)(p13;q12),-13,-17, i(22)(q10), i(22)(q10), mar[cp19]",
"46,XX,del(5)(q22q33)[4]/46,XX[16]", "46,XX,i(17)(q10)[1]/45,sl-7[2]/48,sl, 13, 19[3]/46,XX[15]",
"46,XX,inv(16)(p13q22)[15]/46,XX[2]", "46,XX,inv(16)(p13q22)[19]/46,XX[1]",
"46,XX,inv(16)(p13q22)[20]", "46,XX,inv(16)(p13q22)[5]/46,idem,t(3;3)(p13;q?28)[5]/46,XX[6]",
"46,XX,t(15;17)(q22;q21.1)[19]/47,idem, 8 [1]", "46,XX,t(15;17)(q22;q21),t(16;19)(p13.3;p13.1)[17]/46,XX[3]",
"46,XX,t(15;17)(q22;q21)[11]/46,XX[9]", "46,XX,t(15;17)(q22;q21)[12]/46,XX[8]",
"46,XX,t(15;17)(q22;q21)[20]", "46,XX,t(8;21)(q22;q22)[17]/46,XX[3]",
"46,XX,t(8;21)(q22;q22)[20]", "46,XX,t(8;21)[15]/46,idem,del(9)(q12q22)[5]",
"46,XX[15]", "46,XX[18]", "46,XX[19]/46,XX,add(7)(p?22)[1]",
"46,XX[20]", "46,XX 13,21[cp17]/46,XX[3]", "46,XY,9qh [19]",
"46,XY,del(11)(p12)[2]/46,XY[18]", "46,XY,del(20)(q11.2)[23]/92,XXYY,del(20)(q11.2)x2[2]/46,XY[3]",
"46,XY,del(7)(q21q36)[18]/46,XY[2]", "46,XY,del(9)(q13:q22),t(11:21)(p13;q22),t(15;17)(q22;q210[20]",
"46,XY,i(17)(q10)[15]/47,XY,idem 13[3]/46,XY[2]", "46,XY,inv(16)(p13;q22)[20]",
"46,XY,inv(16)(p13q22)[17]/46,XY[3]", "46,XY,inv(16)(p13q22)[9]/46,XY[10]",
"46,XY,t(11;19)(q23;p13)[17]/46,XY,t(11;19)(q23;p13),inv(12)(p12p13)[3]",
"46,XY,t(11;19)(q23;p13)[20]", "46,XY,t(15;17)(q22;q21)[19]/46,XY[1]",
"46,XY,t(15;17)(q22;q21)[20]", "46,XY,t(15;17)(q22:q21)[11]/46,XY[9]",
"46,XY,t(2;4)(q34;q21)inv(16)(p13q22) [20]", "46,XY,t(6;11)(q27;q23)[15]",
"46,XY,t(9;11)(p22;q23)[7]/47,XY,t(9;11)(p22;q23)[7]/46,XY[4]",
"46,XY,t(9;22)(q34;q11.2)[13]/34~37,idem,-3,del(4),-4,-5,-7,-9,-10,t?(11;12),-12,-14,-14,-16,-17,-22[cp6]/46,XY[1]",
"46,XY,t(9;22)(q34;q11.2[4]/50,idem, 8, 10, 21, der(22)(t(9;22)(q34;q11.2)[16]",
"46,XY[13]", "46,XY[15]", "46,XY[19]", "46,XY[20]", "46,XY[30]",
"46~49,XY,del(3)(p14),del(5)(p11.2q33),del(17)(q21q21),add(21)(p11.2), 22,mar[cp20]",
"47,XX, der(5)t(2;5)(p11.2;q11.2)?,t(8;16)(p11.2;p13.3)[19]",
"47,XX,i(11)(q10)[18]/46,XX [2]", "47,XX,t(15;17)(q22:q21) mar[20]",
"47,XX 11 [20]", "47,XX 8 [20]", "47,XXY [17]", "47,XY, 13[5]/46,XY[15]",
"47,XY, 21 [6]/46,XY[13]", "47,XY, 21[11]/48,XY, 3, 21[8]", "47,XY, 22[10]/47,XY, 8[7]/45,XY,del(3)(p21),del(4)(p12p15),-7,?dup(7)(q11.2q36)[3]",
"47,XY, 8 [10]/46,XY [10]", "47,XY, 8 [19]", "47,XY, 8 [20]",
"47,XY, 8[15]/46, 8,-17[3]", "47,XY, 9[10]/46,XY[10]", "47,XY,del(5)(q22q33),t(10;11)(p13~p15;q22~23),i(17)(q10)[3]/46,XY[17]",
"47,XY,del(7)(q22), 8,t(15;17)(q22;q21)[18]/46,XY,del(7)(q22),t(15;17)(q22;q21)[2]",
"47,XY 8 [15]/48,XY 8 8[4]/46,XY[1]", "48,XY, 8, 8[16]/46,XY[4]",
"52~54,XY, 2, 4, 6, 8,del(11)(q23), 19, 19, 21[17]/46,XY[3]",
"53~56,XY, 1,del(2)(q33q34), 8, 10, 11x2, 13x1-2, 14,del(17)(p11.2), 19,add(21)(q22), 22[cp20]",
"incomplete-46,XY,del(12)(p11.20[2]/46,XY[3]", "N.D.", "ND",
"Outside hospital with inv(16)"
), class = "factor"), `Cytogenetic-Code--Other-` = structure(c(
8L,
3L, 8L, 8L, 3L, 9L
), .Label = c(
"BCR-ABL1", "CBFB-MYH11", "Complex Cytogenetics",
"Intermediate Risk Cytogenetic Abnormality", "MLL translocation, poor risk",
"MLL translocation, t(9;11)", "N.D.", "Normal Karyotype", "PML-RARA",
"Poor Risk Cytogenetic Abnormality", "RUNX1-RUNX1T1"
), class = "factor"),
Induction = structure(c(11L, 4L, 1L, 8L, 4L, 9L), .Label = c(
"7 3",
"7 3, dauna", "7 3, IT", "7 3 3", "7 3 3, gleevec", "7 3 3, then 5 2 2",
"7 3 3 PSC", "7 3 AMD", "7 3 ATRA", "7 3 dauno", "7 3 Genasense",
"7 3 study drug", "7 4 ATRA", "Azacitidine", "CLAM", "Cytarabine only",
"Decitabine", "Decitabine then 7 3", "Hydrea & Idarubicin",
"Hydrea, ATRA started", "hydrea, didn't get add'l chemo",
"LBH/Decitabine", "low dose Ara C", "no treatment", "Revlimid",
"Revlmd then Decitbne,7 3,5 2"
), class = "factor")
), row.names = c(
NA,
6L
), class = "data.frame")
df <-
plot_meta %>%
# Columns to include in the stacked barplots
select(FAB, Induction, Sex) %>%
pivot_longer(everything()) %>%
count(name, value) %>%
group_by(name) %>%
mutate(perc = n / sum(n) * 100)
df
#> # A tibble: 12 × 4
#> # Groups: name [3]
#> name value n perc
#> <chr> <fct> <int> <dbl>
#> 1 FAB M0 1 16.7
#> 2 FAB M1 1 16.7
#> 3 FAB M2 1 16.7
#> 4 FAB M3 1 16.7
#> 5 FAB M4 2 33.3
#> 6 Induction 7 3 1 16.7
#> 7 Induction 7 3 3 2 33.3
#> 8 Induction 7 3 AMD 1 16.7
#> 9 Induction 7 3 ATRA 1 16.7
#> 10 Induction 7 3 Genasense 1 16.7
#> 11 Sex Female 2 33.3
#> 12 Sex Male 4 66.7
df %>%
ggplot(aes(name, perc, fill = value))
geom_col()
coord_flip()
Created on 2022-03-02 by the reprex package (v2.0.0)