Entering edit mode
9 months ago
S'bonelo Glen
•
0
Hello everyone
I am still a newbie in the field of bioinformatics. I have been attempting to visualize unique and common genes across six different tissues using the UpSetR plot package. This script was used to generate the plot; however, out of the six tissues, only six could be on the plot.
library(data.table)
library(UpSetR)
d <- data.table::fread(text = "Brainstem Cerebellum Olfactory Bulb Heart Kidney Liver
Rac3 Coq9 Ndufs7 Slc25a10 Aacs Acss3
Ndufb5 Mtnd5 Cotl1 Adhfe1 Aass Cyp4v2
Clic6 Kpna4 Gabarapl2 Ddx5 Abcc4 Slc7a2
Rbmx Snrpg Rbm3 Pgd Acot12 Ehhadh
Ptcd3 Micos13 Atp5f1e Gss Acsf2 Selenbp2
Ndufa13 Ndufa5 Ndufb3 Arl3 Acsm3 Ugt2b17
Amt Ndufa10 Cstf3 Shmt2 Acy3 Gstp1
Ndufs1 Bcr Mtco2 Tpt1 Adk Pdk1
Acan Mpc1 Bcap31 Me1 Ahcyl1 Bgn
Wasl Cfdp1 Ndufaf2 Abcg2 Aif1l Col4a2
Rbm3 Rps15 Gfap H1-1 Akr1b1 Ttn
Mtnd5 Snu13 Atp6v0c Pcbp2 Amacr Cox6b1
Ddc Lin7c Tmed10 Ddx17 Atp2b1 Mup2
Tmc7 Ndufb5 S100a5 Slc25a1 Ca5b Cyp2d9
Erc1 Ampd3 Ap3b1 H1-3 Cbr1 Cyp2b10
Nup35 Ipo5 Gja1 Cstb Cbr3 Ftl1
Ndufb2 Ndufb10 Ndufb7 Tst Ces1f Cyp8b1
Ndufb1 Ebp Ciapin1 Vat1 Cnpy2 Rbm3
Rexo2 Rabac1 Ndufb4 Glul Col1a1 Ehd1
Cbln3 Wdfy2 Adk Rpl29 Col1a2 Cyp4a10
Arfgef3 Clcn6 Gfpt1 Pc Col4a1 Ndufaf2
Dagla Vbp1 Rpl28 Acy3 Col4a2 Cops2
Slc25a31 Nae1 Dgkz Akr1a1 Cox7a1 Cyp2a4
Tph2 Gucy1a1 Tpbg Pecr Cpne5 Rbp1
Actbl2 Ap1s1 Gprc5b Hnrnpd Creg1 S100a13
Ndufb9 Ndufs1 Acyp2 Serpina1c Crot Gsta4
Timm10b Ndufa3 Kirrel2 Hsd17b11 Cryab Ldhb
Syt12 Ndufs4 Ndufb11 Rpn1 Cyp2d26 Dhtkd1
Unc13c Dnajb4 Ndufb10 Acly Cyp2d9 Ndufb7
Serpina1d Chmp4b Wdr6 Atp6v1b2 Cyp2j6 Acot13
Yme1l1 Pdcd6 Mpst Pxmp2 Cyp4a10 Fmo3
Aprt Ndufaf2 Smdt1 Arpc3 Cyp4a14 Clta
Mtnd1 Igsf21 Sec61g Kpna6 Cyp4b1 Eftud2
Jpt2 Stxbp3 C1qb Atp6v1g1 Cyp7b1 Tex15
Ndufv3 Ndufb1 Ndufa2 Slc25a31 Ddc Ndufs1
Chordc1 Tpd52l2 Hddc2 Aldh3a2 Dpyd Sult1c2
Cbln1 Sh3gl1 Agfg1 Gng12 Echdc3 Srl
Rbbp4 Pnn Manf Tmpo Eea1 Aimp1
Ndufaf2 Prodh Kcnj10 Acox1 Ehhadh Cyp2b9
Egfr Exoc7 Ptgds Rhoa Folh1 Cyp4a14
Ca4 Ubxn1 Rpa3 Mapre1 Fth1 Csad
Vps33b Nfu1 Eif3e Gk Ftl1 Gck
Ndufb11 Etnppl Isg15 Rps2 Gsta2 Ss18l2
Gatad2b Spock1 Tmsb10 Atp6v1e1 Gsta3 Hebp1
Scn8a Tagln2 Chmp1a Sult1d1 Gsta4 Mup20
Ensa Cbln1 Mobp Plin1 Hacl1 Nudt7
Hkdc1 Sart3 Mtmr9 Idh1 Hmgb2 Tmem19
Ndufa5 Ndufs6 Ptprf Cpne1 Hmgcs2 Mup18
Prpf6 Tagln Hmox2 Prodh Hmgn2 Selenbp1
Glipr2 Ndufs8 Ptprd Asl Hpd Mpp1
Serpina3k Drc7 Pmm1 Stmn1 Hsd3b2 Gstt2
Serpina1a Hspg2 Pde6d Abhd14b Iqgap2 Tmco1
Camk2g Aamdc Ipo7 Cryz Krt18 Slc30a5
Nmnat1 Rpl26 Ndufc2 Amacr Krt7 Hsd17b6
Tbcd Nmral1 Csde1 Hmgb2 Krt8 Dusp3
Ckm Uck1 Itpa Sfxn1 Ldhd Aass
Mtif2 Lysmd2 Ndufa5 Acad11 Lmnb2 Sh3bgrl3
Hmgn5 Sars2 Actr3b Alox12 Lsm6 Tex44
Tmem245 Cep170b Meis2 H2ac20 Mapre1 Cyp7b1
Cbx3 Bzw1 Bcas3 Csad Mbp Tymp
Gjc3 Apex2 Ensa Ucp1 Mpv17l Fth1
Ugt8 Nucks1 Serpina1a Gpd1 Mrpl22 Serpina3m
Lsmem1 Ndufb6 Serpina3k Xab2 Mrpl23 Ces3a
Rbsn Cp Tnks1bp1 Adh1 Mrpl40 Trmt112
Cpped1 Npm1 Prnp Dcps Mrps26 Rdh16
Arpp19 Rhoa Uap1l1 Dhx9 Myh6 Ndufs4
Ndufa6 Ndufa8 Ndufs3 Ezr Ndufa10 Hspa1b
Ndufs2 Ndufb2 Ndufv2 Sri Ndufa12 Ndufv1
Mug1 Ndufv2 Ndufs4 Ptrh2 Ndufa2 Sult1d1
Ndufs8 Nek9 Cltb Mecr Ndufa5 Acot3
Ndufb7 Ndufa12 Ndufa12 Sqor Ndufa6 Ndufa12
Ndufv1 Ndufs5 Wdfy2 Echdc2 Ndufa7 Upb1
Ndufs3 Ndufa2 Ndufa10 Fabp1 Ndufa9 Ttc39c
Dnah8 Lin7b Mtnd1 Atp2a3 Ndufaf2 Sult1a1
Ndufc2 Nek7 Ctsa Gsr Ndufb7 Sqor
Ndufa10 Ndufs3 Ndufv3 Adrm1 Ndufs1 Aox3
Ndufs7 Ndufv1 Ndufs6 Egfr Ndufs2 Sult2a8
Ndufs5 Ndufb4 Clybl Gmpr Ndufs3 Hyou1
Gcfc2 Ndufa9 Stat1 Gdap2 Ndufs4 Egfr
Ndufb3 Ndufa13 Rpl23 Ywhaq Ndufs6 Ndufa7
Ndufb4 Ndufv3 Ndufv1 Serpina1e Ndufv1 Ndufa6
Ndufa12 Ndufs7 Rif1 Lta4h Ndufv2 Ndufa9
Ndufb8 Ndufb3 Ndufb8 Kifbp Ndufv3 Srd5a1
Serpina1e Pgam2 Capg Psma4 Nqo1 Mpc1
Ndufb10 Ndufc2 Amt Mtr Nucks1 Keg1
Ndufs6 Ndufa6 Ndufs1 Cps1 Nudt19 Serpina3k
Fam136a Cltb Cep170b Ehhadh Pals2 Gsta2
Ndufv2 Ndufb11 Ndufa13 Flii Pecr Gstt3
Ndufa11 Pcdhga4 Vwa1 Aldob Ppid Metap1d
Ndufa1 Mif Tinagl1 H1-4 Ptprk Igf2bp3
Ndufb6 Ndufb9 Ndufa11 Kyat3 Pyroxd2 Ndufs5
S100b H1-0 Actl6b Coasy Rbm3 Nudt19
Acta1 Rpl29 Ndufa8 Snrpe Reep6 Atp6v1g1
Ndufa2 Ndufs2 Lsmem1 Vta1 Retsat Maoa
Nfia Acad8 Ilk Osbpl8 Sephs2 Mgst3
Ndufa7 Ndufa11 Ndufa7 Agpat2 Serpina3m Comt
Ndufa8 Ech1 Ndufs5 Clic1 Sh3bgrl3 Mat1a
Ndufs4 Chmp2a Msn Macroh2a1 Slc12a3 Acot4
Alas1 Micos10 Nup85 Sars1 Slc22a27 Fuom
Phyhd1 S100b Nucks1 Pabpc1 Slc22a6 Mrpl14
Mtnd4 Synpr Tceal3 H2ac21 Slc6a19 Serpinb1a
Ndufa9 Ndufa7 Ndufa9 Nudt8 Stat1 Ces3b
Cdh10 Gnpda2 Cep152 Krt18 Tor1aip1 Prelp
Ring1 Rbfox2 Etnppl Fuom Ugt1a2 Mup3
Tmsb10 S1pr1 Acta1 Cyb5b Cyp2c37
Mrpl43 mt-Nd2 Myh11 Slc25a35 Col12a1
Icmt Rnps1 Ddx46 Rbm3 Endov
Ncln Ap3s1 Slc44a2 Gpd1l S100a9
Gh1 Rbx1 Ndufa6 Lrrc59 Slc25a4
Bola3 Cat Ifit1 Hmgn2 Lum
Ahsg Atp5if1 Vps52 Tkt Myl1
Pdlim1 Rpl18a Rac2 Hmgb1 Col1a1
Ca3 Cyp51a1 Tmco5b H1-2 Tpm2
Crim1 Pkn1 Bclaf1 H4c1 Myh7
Supt4h1a Ppp3r1 Ube2v2 Stat1 Dcn
S100a9 Sltm Atp5if1 Aldh9a1 Cyfip1
Shisa6 Chmp7 Mcm6 Elavl1 Phf11
Adcy5 Bcl7c Vac14 H2bc7 Cse1l
Slc4a2 Lama5 Aqp1 H1-5 Col1a2
Rgs8 Prnp Hnrnpul1 Fah Fabp3
Asph Nup85 Dnajc5 Aldh1l2 Acta1
Hsd17b2 Iah1 Fam136a H3-5 Myh8
Prx Mbnl2 Ublcp1 H2ac4 Ogn
Bzw2 Rbm3 Cmtm5 Ldhd Soat2
Mboat4 Hdgfl3 Nipa1 Cryl1 Sf3b5
Cep76 Hacd2 Bzw1 Ncl Btk
Cacna1e Asph Tgm2 Gpd2 Cela1
Ldhd Lpcat4 Akr1e2 Ndrg1 Uap1
Iqsec3 Nek7 Acacb Actn2
Kyat3 Gabbr1 Rcc2 Tnnt3
Hnrnpul1 Pld2 Fgb Upp2
Atp5f1e C1qa Ces1f Tgtp2
Mrps21 Irgm1 Gclc Tpm1
Itpa Try5 Pvalb Myh1
Sec61g Alg2 Bdh1 Tex264
Acads Pik3c3 Sord Amy2a5
Poldip2 Dynll2 Ssb Cela2a
Rpl36a Ckm Fabp4 Ckmt2
Slc6a5 Gstm5 Apoc4 Fmod
Fn1 Urod Bpnt1 Des
Usp19 Rbbp7 Fasn Ckm
Prtn3 Ociad1 Hcfc1 Myl3
Sh3bgrl Rpl29 Cyp4b1 Try5
Gclm Ngef Ganab Nrde2
Egfr Cryab Tkfc Ctrb1
Mobp Rnps1 Acaca Ldb3
Abhd3 Ugdh Cbr2
Cirbp Iglon5 Lipe
Mast1 C1qc Hnrnpa3
Slc44a2 Eif2b4 Septin9
Magi2 Ythdf3 Hnrnpf
Spag7 Rps15 Hnrnpab
C1qbp Atg4b Sfxn3
Pllp Pvalb Ctsz
Smad3 Lig1 Coro1c
Exoc6b Ehd1 S100a11
Chtop Fn3krp Ssrp1
Hmgn2 Cxadr Ptbp1
Abhd6 Tmem186 Rac2
Cers1 Lsm4 Nup85
Dsg2 Rpl10 Nherf1
Arl8b Ca1 Coro1a
Rbck1 Mindy2 Atp6v1a
Abhd4 Rcc1 Arpc1b
Frrs1l Sart1 Krt8
Rnf214 H3-5 Ruvbl1
Cdc42ep1 H1-0 Pck1
Sf3a3 Clca3a1 Hnrnpc
Metap2 Lpcat4 Rida
Eif2b4 H2-K1 Ces1d
Inpp5f S100a13 Smarcc2
Urod Trappc4 Ewsr1
Nmt2 Ca4 Akr1c21
Alg11 S100a4 Serpina3m
Rad23b Hbb-b2 Chmp1a
Drap1 Celf1 Actbl2
Hddc2 Rap2a Ndufa1
App Ca8 Ndufs4
Cpsf6 Fgg Rala
Ppp2r5c Ube2fb C8a
Kiss1 Eif3k Mug1
Rgs6 Ctnnbl1 Rrp12
Txndc9 Timm10 mt-Nd2
Ehd4 Uvrag Apoa2
Slc25a31 Arid1a Ndufaf2
Cpped1 Krt8 Mtx1
Rbm27 Bpifb9a N6amt1
Cmtm5 Col1a2 Mrpl49
Gh1 Actbl2 Ndufs6
Elp3 Evl Cisd1
Atp6v0c Rpl39 Ndufa12
Ints3 Col6a1 Serpina3k
Tmem68 Map4k1
Tiam1 Atp6v1e2
Cox7a2l Col1a1
Arfgef3 Rpl35
Higd1a Cpsf6
Ptgds Lum
Eny2
Tmsb10
Per2
Tatdn1
Rpl30
Irag2
Otud6b
Myl1
Akap10
Cav1
Fbxl20
Adh1
Ehhadh
Atp4a
Naga
Tceal3
Col1a1
Celf1
Cops6
Vps11
Dync1i2
Hm13
Eif2s2
Fgg
Ralgapa1
Ipo7
Tmod3
Fgb
Phpt1
Eif3j2
Lars2
Snrpb2
Mug1
Slc4a1
Arg1
Celf2
Actbl2
Krt6a
Fga
Ufd1
Fam136a
Ntmt1
Opalin
Omp
Acsf3
Lig3
Xpo5
Tmem240
Aldob
Adprs
Stx1a
H2bc14
Serpina1d
Cldn11
Cyp2j5
Slc6a11
Cpm
Acp2
Ca1
Cd44
Cplx2")
fld <- fromList(as.list(d))
upset(fld)
As it can be seen in the figure below, only five tissues could be seen, with the exception of the kidney, even in the presence of overlapping genes between the kidney and other tissues. Can you kindly assist in this regard, I do not know if there is something wrong with my input data or the script itself.
The format of your data is not optimal because you have gene lists of different length. It would be more convenient to create a list of named vectors as recommended in the package documentation.
Except that, you could play with the arguments to customize your plot. In your case, you should increase the
nsetsargument to 6 :upset(fld,nsets=6)Let me try it, thank you.