<p>No idea how your code looks like before pasting into the web form, but in general it is not a great idea pasting +260 rows/lines of data in your script.
From what I can see in the form you have columns of data separated by different number of spaces even in the header (2 and 4 spaces).
Because of this it is impossible to figure out to which column is which.</p>
<p>The easiest is to keep the data in the <code>TSV</code> or <code>CSV</code> format file and make sure there are no issues with column delimiters.</p>
<p><strong>EDIT</strong></p>
<p>I have saved the Google Spreadsheet as <code>de_genes.csv</code>, edited just in case <code>Olfactory Bulb</code> to <code>Olfactory_Bulb</code> then did:</p>
<pre><code>in_fn &lt;- &quot;de_genes.csv&quot;

df = fread(in_fn)

de_lists &lt;- fromList(as.list(df))


upset(de_lists, sets=c( &quot;Brainstem&quot;,    &quot;Cerebellum&quot;,   &quot;Olfactory_Bulb&quot;,   &quot;Heart&quot;, &quot;Kidney&quot;, &quot;Liver&quot;) , order.by = &quot;freq&quot;)
</code></pre>
<p>I got:</p>
<p><a href="https://i.sstatic.net/f1YSF.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/f1YSF.png" alt="upsetR plot" /></a></p>

CC BY-SA 4.0
2024-02-20T23:32:32.320Z
I tried using that strategy (i.e., keeping data in csv instead of pasting it) but I am struggling with reading my csv file using the "data.table" function.        See the original data here (https://docs.google.com/spreadsheets/d/17KuGuzBjBhaRBoDCq-3SvnklBZQF1C-HcTpss1V0zKA/edit?usp=sharing)
S'bonelo Glen Khumalo
CC BY-SA 4.0
2024-02-21T14:22:59.857Z
Updated the answer. It should work now
darked89
CC BY-SA 4.0
2024-02-21T19:05:26.880Z
It is indeed working, thank you.
S'bonelo Glen Khumalo
CC BY-SA 4.0
2024-02-22T16:23:38.700Z
@S'boneloGlenKhumato  could you upvote this answer and mark it as accepted please?
M__
CC BY-SA 4.0
2024-02-20T15:58:09.027Z
2024-02-21T08:05:56.940Z
2024-02-21T08:05:56.940Z
darked89
<p>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 <code>UpSetR</code> plot package. This script was used to generate the plot; however, out of the six tissues, only six could be on the plot.</p>
<pre class="lang-r prettyprint-override"><code>library(data.table)
library(UpSetR)
d &lt;- data.table::fread(text = &quot;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&quot;)
fld &lt;- fromList(as.list(d))
upset(fld)
</code></pre>
<p>As shown 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.</p>
<p><a href="https://i.sstatic.net/pgvZL.jpg" rel="nofollow noreferrer"><img src="https://i.sstatic.net/pgvZL.jpg" alt="enter image description here" /></a>.</p>
<p>Can you kindly assist in this regard, I do not know if there is something wrong with my input data or the script itself.</p>

<r><upsetr>
How to visualize unique and overlapping genes in upSet R plot
# How to visualize unique and overlapping genes in upSet R plot

(Asked by: username_0 on 2024-02-20)

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 shown 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.

**Tags:** r, upsetr

---

## 1 answers

### Answer by username_1 on 2024-02-20. Score: 3

No idea how your code looks like before pasting into the web form, but in general it is not a great idea pasting +260 rows/lines of data in your script.
From what I can see in the form you have columns of data separated by different number of spaces even in the header (2 and 4 spaces).
Because of this it is impossible to figure out to which column is which.
The easiest is to keep the data in the TSV or CSV format file and make sure there are no issues with column delimiters.
EDIT
I have saved the Google Spreadsheet as de_genes.csv, edited just in case Olfactory Bulb to Olfactory_Bulb then did:
in_fn <- "de_genes.csv"

df = fread(in_fn)

de_lists <- fromList(as.list(df))


upset(de_lists, sets=c( "Brainstem",    "Cerebellum",   "Olfactory_Bulb",   "Heart", "Kidney", "Liver") , order.by = "freq")

I got:

> **Comments:**
> **username_0**: I tried using that strategy (i.e., keeping data in csv instead of pasting it) but I am struggling with reading my csv file using the "data.table" function.        See the original data here (https://docs.google.com/spreadsheets/d/17KuGuzBjBhaRBoDCq-3SvnklBZQF1C-HcTpss1V0zKA/edit?usp=sharing)  
> **username_1**: Updated the answer. It should work now  
> **username_0**: It is indeed working, thank you.  
> **username_2**: @S'boneloGlenKhumato  could you upvote this answer and mark it as accepted please?  

---

