Please check if appropriate organism/ID type was provided! Allowed proportion (0.98) of missing resource elements exceeded (1.00).

[soniyalama]

When running this, I get the error above:
cellphonedb(adata, groupby='cluster_labels', expr_prop=0.1, resource_name='mouseconsensus', verbose=True, key_added='cpdb_res')

My adata contains the gene names, the normalised SCT assay (layer = data) as required, and the barcodes.
My dataset is mouse data and so here, I'm using the mouse consensus.

Another question, what if I want to run it through connectome, which value for the "key_added" parameter should I use?

Thanks in advance.

[soniyalama]

To be more specific, this is the error I got
@dbdimitrov

 --------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
Cell In[44], line 2
      1 # run cellphonedb
----> 2 cellphonedb(adata, groupby='cluster_labels', expr_prop=0.1, resource_name='mouseconsensus', verbose=True, key_added='cpdb_res')

File [/data/leuven/345/vsc34524/miniconda3/envs/liana/lib/python3.10/site-packages/liana/method/sc/_Method.py:250](https://ondemand.hpc.kuleuven.be/data/leuven/345/vsc34524/miniconda3/envs/liana/lib/python3.10/site-packages/liana/method/sc/_Method.py#line=249), in Method.__call__(self, adata, groupby, resource_name, expr_prop, min_cells, groupby_pairs, base, supp_columns, return_all_lrs, key_added, use_raw, layer, de_method, n_perms, seed, n_jobs, resource, interactions, mdata_kwargs, inplace, verbose)
    247 else:
    248     ad = adata
--> 250 liana_res = liana_pipe(adata=ad,
    251                        groupby=groupby,
    252                        resource_name=resource_name,
    253                        resource=resource,
    254                        interactions=interactions,
    255                        expr_prop=expr_prop,
    256                        min_cells=min_cells,
    257                        supp_columns=supp_columns,
    258                        return_all_lrs=return_all_lrs,
    259                        groupby_pairs=groupby_pairs,
    260                        base=base,
    261                        de_method=de_method,
    262                        verbose=verbose,
    263                        _score=self._method,
    264                        n_perms=n_perms,
    265                        seed=seed,
    266                        n_jobs=n_jobs,
    267                        use_raw=use_raw,
    268                        layer=layer,
    269                        )
    270 if inplace:
    271     adata.uns[key_added] = liana_res

File [/data/leuven/345/vsc34524/miniconda3/envs/liana/lib/python3.10/site-packages/liana/method/sc/_liana_pipe.py:143](https://ondemand.hpc.kuleuven.be/data/leuven/345/vsc34524/miniconda3/envs/liana/lib/python3.10/site-packages/liana/method/sc/_liana_pipe.py#line=142), in liana_pipe(adata, groupby, resource_name, resource, interactions, groupby_pairs, expr_prop, min_cells, base, de_method, n_perms, seed, verbose, use_raw, n_jobs, layer, supp_columns, return_all_lrs, _score, _methods, _consensus_opts, _aggregate_method)
    140 resource = explode_complexes(resource)
    142 # Check overlap between resource and adata
--> 143 assert_covered(np.union1d(np.unique(resource[P.ligand]),
    144                           np.unique(resource[P.receptor])),
    145                adata.var_names, verbose=verbose)
    147 # Filter Resource
    148 resource = filter_resource(resource, adata.var_names)

File [/data/leuven/345/vsc34524/miniconda3/envs/liana/lib/python3.10/site-packages/liana/method/_pipe_utils/_pre.py:60](https://ondemand.hpc.kuleuven.be/data/leuven/345/vsc34524/miniconda3/envs/liana/lib/python3.10/site-packages/liana/method/_pipe_utils/_pre.py#line=59), in assert_covered(subset, superset, subset_name, superset_name, prop_missing_allowed, verbose)
     53 if prop_missing > prop_missing_allowed:
     54     msg = (
     55         f"Please check if appropriate organism[/ID](https://ondemand.hpc.kuleuven.be/ID) type was provided! "
     56         f"Allowed proportion ({prop_missing_allowed}) of missing "
     57         f"{subset_name} elements exceeded ({prop_missing:.2f}). "
     58         f"Too few features from the resource were found in the data."
     59     )
---> 60     raise ValueError(msg + f" [{x_missing}] missing from {superset_name}")
     62 _logg(f"{prop_missing:.2f} of entities in the resource are missing from the data.", verbose=verbose & (prop_missing > 0))

ValueError: Please check if appropriate organism[/ID](https://ondemand.hpc.kuleuven.be/ID) type was provided! Allowed proportion (0.98) of missing resource elements exceeded (1.00). Too few features from the resource were found in the data. [A2m, Aanat, Abca1, Ace, Ackr2, Ackr3, Ackr4, Actr2, Acvr1, Acvr1b, Acvr1c, Acvr2a, Acvr2b, Acvrl1, Ada, Adam10, Adam11, Adam12, Adam15, Adam17, Adam2, Adam22, Adam23, Adam28, Adam29, Adam7, Adam9, Adamts3, Adcy1, Adcy7, Adcy8, Adcy9, Adcyap1, Adcyap1r1, Adipoq, Adipor1, Adipor2, Adm, Adm2, Ado, Adora1, Adora2a, Adora2b, Adora3, Adra2a, Adra2b, Adrb1, Adrb2, Adrb3, Ager, Agr2, Agrn, Agrp, Agt, Agtr1a, Agtr2, Ahsg, Aimp1, Alb, Alcam, Alk, Alox5, Ambn, Amelx, Amfr, Amh, Amhr2, Ang, Angpt1, Angpt2, Angpt4, Angptl1, Angptl2, Angptl3, Angptl4, Angptl7, Antxr1, Anxa1, Anxa2, Apcdd1, Apln, Aplnr, Aplp1, Aplp2, Apoa1, Apoa2, Apoa4, Apob, Apoc2, Apoc4, Apod, Apoe, Apoo, App, Aqp1, Aqp5, Ar, Areg, Arf1, Arf6, Arpc5, Art1, Artn, Asgr1, Asgr2, Atp1a3, Atp6ap2, Atrn, Avp, Avpr1a, Avpr1b, Avpr2, Axl, Azgp1, B2m, Bambi, Bcam, Bcan, Bdkrb1, Bdkrb2, Bdnf, Bgn, Bmp1, Bmp10, Bmp15, Bmp2, Bmp3, Bmp4, Bmp5, Bmp6, Bmp7, Bmp8a, Bmpr1a, Bmpr1b, Bmpr2, Boc, Bpi, Brs3, Bsg, Bst1, Btc, Btla, Btn1a1, C1qa, C1qb, C1qbp, C1qtnf1, C1qtnf5, C3, C3ar1, C4a, C4b, C5ar1, C5ar2, C920025E04Rik, Cacna1c, Cadm1, Cadm3, Calca, Calcr, Calcrl, Calml3, Calr, Camp, Cap1, Catsper1, Cav1, Ccbe1, Cck, Cckar, Cckbr, Ccl1, Ccl11, Ccl12, Ccl17, Ccl2, Ccl20, Ccl21b, Ccl22, Ccl24, Ccl25, Ccl27b, Ccl28, Ccl4, Ccl5, Ccr1, Ccr10, Ccr2, Ccr3, Ccr4, Ccr5, Ccr6, Ccr7, Ccr8, Ccr9, Ccrl2, Cd14, Cd151, Cd163, Cd177, Cd180, Cd19, Cd2, Cd200, Cd200r1, Cd200r2, Cd200r4, Cd209a, Cd209e, Cd22, Cd226, Cd244, Cd247, Cd248, Cd27, Cd274, Cd28, Cd300lf, Cd34, Cd36, Cd38, Cd3d, Cd3g, Cd4, Cd40, Cd40lg, Cd44, Cd46, Cd47, Cd48, Cd5, Cd53, Cd59b, Cd5l, Cd6, Cd63, Cd68, Cd69, Cd7, Cd70, Cd72, Cd74, Cd79a, Cd80, Cd81, Cd82, Cd86, Cd8a, Cd8b1, Cd9, Cd93, Cdh1, Cdh10, Cdh11, Cdh2, Cdh5, Cdh7, Cdon, Ceacam1, Ceacam16, Ceacam19, Ceacam2, Cel, Celsr1, Celsr2, Celsr3, Cer1, Cfc1, Cfh, Cfp, Cftr, Cga, Cgn, Chad, Chl1, Chrm1, Chrm3, Chrna10, Chrna3, Chrna4, Chrna7, Chrna9, Chrnb2, Chrnb4, Cirbp, Cklf, Clcf1, Cldn4, Clec10a, Clec11a, Clec12a, Clec14a, Clec1b, Clec3a, Clec4g, Cmklr1, Cnr1, Cnr2, Cntf, Cntfr, Cntn1, Cntn2, Cntn3, Cntn4, Cntn5, Cntn6, Cntnap1, Col10a1, Col11a1, Col11a2, Col12a1, Col13a1, Col14a1, Col15a1, Col16a1, Col18a1, Col19a1, Col1a1, Col1a2, Col20a1, Col22a1, Col24a1, Col26a1, Col27a1, Col28a1, Col2a1, Col3a1, Col4a1, Col4a2, Col4a3, Col4a4, Col4a5, Col4a6, Col5a1, Col5a2, Col5a3, Col6a1, Col6a2, Col6a3, Col6a5, Col6a6, Col7a1, Col8a1, Col8a2, Col9a1, Col9a2, Col9a3, Colq, Comp, Copa, Cort, Cp, Cr2, Crh, Crhr1, Crhr2, Crisp2, Crlf1, Crlf2, Crlf3, Crp, Crtam, Csf1, Csf1r, Csf2, Csf2ra, Csf2rb, Csf3, Csf3r, Cspg4, Ctf1, Cthrc1, Ctla4, Cubn, Cx3cl1, Cx3cr1, Cxcl1, Cxcl10, Cxcl12, Cxcl13, Cxcl14, Cxcl16, Cxcl17, Cxcl2, Cxcl5, Cxcr1, Cxcr2, Cxcr3, Cxcr4, Cxcr5, Cxcr6, Cytl1, Dag1, Dcbld2, Dcc, Dchs1, Dclk3, Dcn, Ddr1, Ddr2, Dhh, Dip2a, Dkk1, Dkk2, Dkk3, Dkk4, Dlk1, Dlk2, Dll1, Dll3, Dll4, Dmp1, Dnajb11, Dpp4, Draxin, Drd2, Drd4, Dsc1, Dsc2, Dsc3, Dscam, Dsg1a, Dsg1b, Dsg2, Dsg3, Dsg4, Dysf, Ear11, Ear5, Ebi3, Ecm1, Edil3, Edn1, Edn2, Edn3, Ednra, Ednrb, Efemp1, Efemp2, Efna1, Efna2, Efna3, Efna4, Efna5, Efnb1, Efnb2, Efnb3, Egf, Egfr, Enam, Eng, Enho, Eno1, Enpep, Entpd1, Epgn, Epha1, Epha10, Epha2, Epha3, Epha4, Epha5, Epha6, Epha7, Epha8, Ephb1, Ephb2, Ephb3, Ephb4, Ephb6, Epo, Epor, Erap1, Erbb2, Erbb3, Erbb4, Ereg, Esam, Etv5, F10, F11, F11r, F12, F13a1, F2, F2r, F2rl1, F2rl2, F2rl3, F3, F7, F8, F9, Fabp5, Fadd, Fam3b, Fam3c, Fap, Farp2, Fas, Fasl, Fat4, Fbln1, Fbln2, Fbn1, Fcer1a, Fcer2a, Fcgr3, Fcgr4, Fcgrt, Ffar2, Fga, Fgb, Fgf1, Fgf10, Fgf11, Fgf12, Fgf13, Fgf14, Fgf15, Fgf16, Fgf17, Fgf18, Fgf2, Fgf20, Fgf21, Fgf22, Fgf23, Fgf3, Fgf4, Fgf5, Fgf6, Fgf7, Fgf8, Fgf9, Fgfr1, Fgfr2, Fgfr3, Fgfr4, Fgfrl1, Fgg, Fgl1, Flot1, Flrt3, Flt1, Flt3, Flt3l, Flt4, Fn1, Fndc5, Fpr1, Fpr2, Fras1, Frem1, Frem2, Frs3, Fshb, Fshr, Fst, Fstl1, Fstl5, Fxyd6, Fzd1, Fzd10, Fzd2, Fzd3, Fzd4, Fzd5, Fzd6, Fzd7, Fzd8, Fzd9, Gabbr2, Gad1, Gal, Galp, Galr1, Galr2, Galr3, Gas1, Gas6, Gast, Gc, Gcgr, Gdf1, Gdf10, Gdf11, Gdf15, Gdf2, Gdf3, Gdf5, Gdf6, Gdf7, Gdf9, Gdnf, Gfra1, Gfra2, Gfra3, Gfra4, Gfral, Gh, Ghr, Ghrh, Ghrhr, Ghrl, Ghsr, Gip, Gipr, Gjb2, Glg1, Glp1r, Glra2, Gm11127, Gm13305, Gm13306, Gm2002, Gm2023, Gm2506, Gm3934, Gm5506, Gm7030, Gnai2, Gnas, Gnb3, Gnrh1, Gnrhr, Gp1ba, Gp1bb, Gp49a, Gp5, Gp6, Gp9, Gpc1, Gpc2, Gpc3, Gpc4, Gpc5, Gpha2, Gphb5, Gpi1, Gpnmb, Gpr135, Gpr151, Gpr152, Gpr171, Gpr182, Gpr19, Gpr20, Gpr25, Gpr35, Gpr37, Gpr37l1, Gpr39, Gpr44, Gpr75, Gpr83, Gpr84, Gprc5d, Gprc6a, Grem1, Grem2, Grin2a, Grin2b, Grin2c, Grin2d, Grm1, Grm4, Grm5, Grm7, Grn, Grp, Grpr, Gstm7, Gsto1, Gstp1, Gstp2, Guca2a, Guca2b, Gucy2c, Gucy2e, Gzma, H2-Aa, H2-Ab1, H2-DMa, H2-DMb1, H2-DMb2, H2-Ea-ps, H2-Eb1, H2-K1, H2-M3, H2-Ob, H2-T23, Hapln1, Has2, Havcr2, Hbegf, Hc, Hcrt, Hcrtr1, Hcrtr2, Hdc, Hebp1, Hfe, Hgf, Hhip, Hmmr, Hp, Hpx, Hras, Hrh1, Hrh2, Hrh3, Hrh4, Hsp90aa1, Hsp90b1, Hspa1a, Hspa4, Hspa8, Hspg2, Htr1a, Htr1b, Htr1d, Htr1f, Htr2a, Htr2b, Htr2c, Htr4, Htr5a, Htr6, Htr7, Iapp, Ibsp, Icam1, Icam2, Icam4, Icam5, Icos, Icosl, Ifna11, Ifnar1, Ifnar2, Ifnb1, Ifne, Ifng, Ifngr1, Ifngr2, Ifnk, Ifnlr1, Igdcc3, Igdcc4, Igf1, Igf1r, Igf2, Igf2r, Igfbp4, Igfbpl1, Igfl3, Igflr1, Igsf1, Igsf10, Ihh, Il10, Il10ra, Il10rb, Il11, Il11ra1, Il11ra2, Il12a, Il12b, Il12rb1, Il12rb2, Il13, Il13ra1, Il13ra2, Il15, Il15ra, Il16, Il17a, Il17b, Il17c, Il17f, Il17ra, Il17rb, Il17rc, Il17re, Il18, Il18bp, Il18r1, Il18rap, Il19, Il1a, Il1b, Il1f10, Il1f5, Il1f6, Il1f8, Il1f9, Il1r1, Il1r2, Il1rap, Il1rapl1, Il1rapl2, Il1rl1, Il1rl2, Il1rn, Il2, Il20, Il20ra, Il20rb, Il21, Il21r, Il22, Il22ra1, Il22ra2, Il23a, Il23r, Il24, Il25, Il27, Il27ra, Il2ra, Il2rb, Il2rg, Il33, Il34, Il3ra, Il4, Il4ra, Il5, Il5ra, Il6, Il6ra, Il6st, Il7, Il7r, Il9, Il9r, Iltifb, Impg2, Inha, Inhba, Inhbb, Inhbc, Inhbe, Ins2, Insl3, Insl5, Insr, Irak4, Islr2, Itga1, Itga10, Itga11, Itga2, Itga2b, Itga3, Itga4, Itga5, Itga6, Itga7, Itga8, Itga9, Itgad, Itgae, Itgal, Itgam, Itgav, Itgax, Itgb1, Itgb2, Itgb3, Itgb3bp, Itgb4, Itgb5, Itgb6, Itgb7, Itgb8, Itih2, Izumo1, Jag1, Jag2, Jam2, Jam3, Jmjd6, Kcna3, Kcnd1, Kcnd2, Kcnj10, Kcnj15, Kcnj4, Kcnq1, Kdr, Kel, Kidins220, Kiss1, Kiss1r, Kit, Kitl, Kl, Klb, Klk1b8, Klrb1a, Klrb1b, Klrb1c, Klrc1, Klrd1, Klrg1, Klrg2, Kng1, Kng2, Kremen1, Kremen2, L1cam, LOC100861969, LOC100861978, Lag3, Lair1, Lama1, Lama2, Lama3, Lama4, Lama5, Lamb1, Lamb2, Lamb3, Lamc1, Lamc2, Lamc3, Lamp1, Lamp2, Lck, Lcn2, Ldlr, Leap2, Lefty1, Lefty2, Lep, Lepr, Lgals1, Lgals3, Lgals3bp, Lgals8, Lgi1, Lgi2, Lgi3, Lgi4, Lgr4, Lgr5, Lgr6, Lhb, Lhcgr, Lif, Lifr, Lilrb4, Lin7c, Lingo1, Lipc, Liph, Lman1, Lmbr1l, Lpar1, Lpar2, Lpar3, Lpar4, Lpl, Lpp, Lrig1, Lrig2, Lrp1, Lrp10, Lrp11, Lrp1b, Lrp2, Lrp4, Lrp5, Lrp6, Lrp8, Lrpap1, Lrrc4, Lrrc4b, Lrrc4c, Lrrn3, Lrrtm2, Lsr, Lta, Ltb, Ltbp1, Ltbp3, Ltbr, Ltf, Lum, Ly86, Ly96, Lypd3, Lyve1, Lyz1, Lyz2, Mag, Maged1, Marco, Mas1, Matn1, Mbl2, Mc1r, Mc2r, Mc3r, Mc4r, Mc5r, Mcam, Mcfd2, Mchr1, Mdk, Megf10, Mepe, Mertk, Met, Mfap2, Mfap3l, Mfap5, Mfge8, Mfng, Mfrp, Mgl2, Mgrn1, Mia, Mif, Mmp12, Mmp13, Mmp1a, Mmp2, Mmp24, Mmp7, Mmp9, Mmrn2, Mog, Mpl, Mpz, Mpzl1, Mrap, Mrc1, Mrc2, Mrgprb1, Mrgprb2, Mrgprx2, Msmp, Mst1, Mst1r, Mstn, Mtnr1a, Mtnr1b, Mttp, Muc2, Muc5ac, Muc6, Musk, Myl9, Myoc, Nampt, Ncam1, Ncam2, Ncan, Ncl, Ncr1, Ncstn, Ndp, Negr1, Nell2, Neo1, Nfasc, Ngf, Ngfr, Nid1, Nlgn1, Nlgn2, Nlgn3, Nmb, Nmbr, Nms, Nmu, Nmur1, Nmur2, Nodal, Notch1, Notch2, Notch3, Notch4, Npb, Npbwr1, Npff, Npffr1, Npffr2, Npnt, Nppa, Nppc, Npr1, Npr2, Npr3, Nps, Npsr1, Nptx1, Nptx2, Nptxr, Npvf, Npw, Npy, Npy1r, Npy2r, Npy5r, Nr0b2, Nrcam, Nrg2, Nrg3, Nrg4, Nrp1, Nrp2, Nrsn1, Nrtn, Nrxn1, Nrxn2, Nt5e, Ntf3, Ntf5, Ntn1, Ntn3, Ntn4, Ntng1, Ntng2, Ntrk1, Ntrk2, Ntrk3, Nts, Ntsr1, Ntsr2, Nucb2, Nxph1, Nxph2, Nxph3, Ocln, Ogfr, Oit1, Olfm2, Olr1, Omg, Oprd1, Oprk1, Oprl1, Oprm1, Orai2, Osm, Osmr, Ostn, Oxt, Oxtr, P2rx7, P2ry12, P2ry14, P2ry6, P4hb, Pam, Pard3, Pcsk1n, Pcsk9, Pdap1, Pdcd1, Pdcd1lg2, Pdcd2, Pdgfa, Pdgfb, Pdgfc, Pdgfd, Pdgfra, Pdgfrb, Pdpn, Pdx1, Pdyn, Pecam1, Penk, Pf4, Pgf, Pglyrp1, Phex, Pi16, Piga, Pigf, Pigr, Pip, Pirb, Pkm, Pla2g10, Pla2r1, Plat, Plau, Plaur, Pld1, Pld2, Plg, Plgrkt, Plscr1, Plscr4, Pltp, Plxdc1, Plxdc2, Plxna1, Plxna2, Plxna3, Plxna4, Plxnb1, Plxnb2, Plxnb3, Plxnc1, Plxnd1, Pmch, Pnoc, Podxl2, Pomc, Postn, Ppy, Prl, Prlh, Prlhr, Prlr, Prn, Prnd, Proc, Procr, Prok1, Prok2, Prokr1, Prokr2, Pros1, Prss2, Prtg, Psap, Psen1, Pspn, Ptch1, Ptch2, Ptdss1, Ptgdr, Ptger2, Ptger3, Ptger4, Ptgir, Ptgs2, Pth, Pth1r, Pth2, Pth2r, Pthlh, Ptk7, Ptn, Ptpn6, Ptpra, Ptprb, Ptprc, Ptprf, Ptprg, Ptprj, Ptprk, Ptprm, Ptprr, Ptprs, Ptpru, Ptprz1, Pyy, Qdpr, Qrfp, Qrfpr, Ramp1, Ramp2, Ramp3, Rarres1, Rarres2, Rbp3, Rbp4, Reck, Reln, Ren1, Ret, Retn, Rgma, Rgmb, Rhag, Rhbdf2, Rhbdl2, Rims1, Rims2, Ripk1, Rln1, Rln3, Rnf43, Robo1, Robo2, Robo3, Robo4, Ror1, Ror2, Rps19, Rpsa, Rspo1, Rspo2, Rspo3, Rspo4, Rtn4, Rtn4r, Rtn4rl1, Rxfp1, Rxfp2, Rxfp3, Rxfp4, Rxra, Ryk, Ryr1, Ryr2, S100a1, S100a10, S100a4, S100a8, S100a9, S100b, S1pr1, S1pr2, S1pr3, S1pr4, S1pr5, Saa1, Saa2, Scara5, Scarb1, Scarf1, Scel, Scgb1a1, Scgb3a1, Scgb3a2, Scn5a, Scn8a, Sctr, Scube2, Sdc1, Sdc2, Sdc3, Sdc4, Sdk2, Sectm1a, Sele, Sell, Selp, Selplg, Sema3a, Sema3b, Sema3c, Sema3d, Sema3e, Sema3f, Sema3g, Sema4a, Sema4b, Sema4c, Sema4d, Sema4f, Sema4g, Sema5a, Sema5b, Sema6a, Sema6b, Sema6d, Sema7a, Serpina1a, Serpina1b, Serpina1c, Serpina1d, Serpina1e, Serpina7, Serpinc1, Serpine1, Serpine2, Serpinf1, Serping1, Sertad1, Sfrp1, Sfrp2, Sftpa1, Sftpd, Shank1, Shank2, Shbg, Shh, Sigirr, Siglec1, Sirpa, Slamf9, Slc16a1, Slc16a2, Slc16a7, Slc17a7, Slc18a2, Slc18a3, Slc2a2, Slc37a1, Slc40a1, Slc4a11, Slc6a8, Slit1, Slit2, Slit3, Slitrk1, Slitrk2, Slitrk3, Slitrk6, Slpi, Slurp1, Smap1, Smo, Snca, Snx14, Socs2, Sorbs1, Sorcs2, Sorcs3, Sorl1, Sort1, Sost, Sostdc1, Sparc, Spink3, Spint1, Spn, Spon1, Spon2, Spp1, Sptan1, Sptbn2, Sst, Sstr1, Sstr2, Sstr3, Sstr4, Sstr5, St14, St6gal1, Stab1, Stab2, Stra6, Stx1a, Stx3, Stx4a, Tac1, Tac2, Tacr1, Tacr2, Tacr3, Tarm1, Tbxa2r, Tcn2, Tctn1, Tdgf1, Tecta, Tectb, Tek, Tff1, Tff2, Tff3, Tfpi, Tfr2, Tfrc, Tg, Tgfa, Tgfb1, Tgfb2, Tgfb3, Tgfbr1, Tgfbr2, Tgfbr3, Tgm2, Tgs1, Thbd, Thbs1, Thbs2, Thbs3, Thbs4, Thpo, Thy1, Tie1, Timp1, Timp2, Timp3, Tln1, Tlr1, Tlr2, Tlr4, Tlr6, Tlr7, Tlr9, Tmed5, Tmem219, Tmem67, Tnc, Tnf, Tnfrsf10b, Tnfrsf11a, Tnfrsf11b, Tnfrsf12a, Tnfrsf13b, Tnfrsf13c, Tnfrsf14, Tnfrsf17, Tnfrsf18, Tnfrsf19, Tnfrsf1a, Tnfrsf1b, Tnfrsf21, Tnfrsf25, Tnfrsf4, Tnfrsf8, Tnfsf10, Tnfsf11, Tnfsf12, Tnfsf13, Tnfsf13b, Tnfsf14, Tnfsf15, Tnfsf18, Tnfsf4, Tnfsf8, Tnn, Tnr, Tnxb, Tph1, Tpo, Tpsb2, Tradd, Traf2, Traf3, Trem1, Trem2, Treml2, Trf, Trh, Trhr, Trpm2, Trpm3, Trpv1, Trpv6, Try10, Try4, Try5, Tshb, Tshr, Tslp, Tspan1, Tspan10, Tspan12, Tspan14, Tspan15, Tspan17, Tspan5, Ttr, Txlna, Tyro3, Tyrobp, Ucn, Ucn2, Ucn3, Unc5a, Unc5b, Unc5c, Unc5d, Uts2, Uts2b, Uts2r, Vangl2, Vasn, Vasp, Vcam1, Vcan, Vcl, Vegfa, Vegfb, Vegfc, Vgf, Vim, Vip, Vipr1, Vipr2, Vldlr, Vsig10l, Vtn, Vwf, Wfikkn2, Wif1, Wnt1, Wnt10a, Wnt10b, Wnt11, Wnt16, Wnt2, Wnt2b, Wnt3, Wnt3a, Wnt4, Wnt5a, Wnt5b, Wnt6, Wnt7a, Wnt7b, Wnt8a, Wnt8b, Wnt9a, Wnt9b, Xcl1, Xcr1, Ybx1, Znrf3, Zp3, a] missing from var_names

[dbdimitrov]

Hi @soniyalama,

Given that LIANA does not find those genesymbols, it might be best to check that your adata.var.index contains them.

re running connectome: they key_added adds the results dataframe to the adata.uns[key_added] slot, you should use the connectome method (also imported in the tutorial) to run connectome.

[soniyalama]

Hi @dbdimitrov,
Thank you for your reply.

Well, we've checked for overlap between both the mouse consensus genes and my own genes and there is an overlap of 1203 genes. So I'm not sure what is creating the issue here?

Kind regards,
Soniya Lama

[soniyalama]

So my dataset contains 15 723 unique genes. The mouseconsensus data which I checked via this code: "mouseconsensus = li.resource.select_resource('mouseconsensus') contains 7978 genes in total, where 1741 are unique.
I did check the overlap which gave me 1203 genes. If you do 1203/7978 that is already 15% of the resource. Now I don't get why the error Is saying that I have 0% overlap between both my adata.var_names and my mouseconsensus?

Am I looking at the mouseconsensus in a wrong way in any way?

Thanks in advance,
Soniya Lama.

[dbdimitrov]

Hi @soniyalama, this is strange - if the var_names overlap with the resource, it should work. I could double-check if you provide a small subset of your data.

[soniyalama]

I can't seem to insert a .h5ad format here. I sent it through mail.

Thanks for your help!

[dbdimitrov]

Hi @soniyalama,

It seems like you are passing the .raw instead of X, and your .raw adata has numbers instead of gene names in .var.

It should work if you pass use_raw=False:
li.mt.cellphonedb(adata, groupby='group_label', expr_prop=0, resource_name='mouseconsensus', verbose=True, use_raw=False)

[dbdimitrov]

I plan to change use_raw to be False by default in future version as it seems now that the preferred approach is just using layers. Hope this helps.

[soniyalama]

Hi Mr. Dimitrov,

This seems to resolve the issue. Thanks a lot. Another question I had if it's correct that the tool is running on the SCT assay, layer = counts, or layer = data? This wasn't specified, and I'm not pretty well known.

Kind regards,
Soniya Lama.

[dbdimitrov]

@soniyalama as long as the cell distributions are normalised it should be fine. I can't recall if SCT counts were non-negative though, I assume yes, and their residuals are the mean-normalised ones?

Either way, comparable cell distributions and non-negative counts would work with liana :)

Hope this helps.