Obtaining count matrices from .h5mu files

Question

[dglad]

Hi everyone,

My collaborator has sent me CITE-seq data in the form of a .h5mu file. I am trying to load this data into R and then obtain the count matrices and then do subsequent analyses. Does anyone have experience obtaining count matrices from .h5mu data?

Answer 1

[Radu Tanasa]

That is a multimodal format similar to AnnData. Here is how you can load it:

• R: https://github.com/PMBio/MuDataSeurat
• Python: https://github.com/scverse/mudata

[dglad]

Hi there!

Thanks so much for posting. I have been trying to create my own .Rmd file that mirrors what is being done in the two vignettes that they have posted. For the PBMC-CITE-seq.Rmd vignette. I have done everything up to line 62. I am currently trying to do var <- ReadH5MU("file path"), but I am getting an error.

Here is the error message: Warning: non-unique values when setting 'row.names': ‘A1CF’, ‘A2M’, ‘A2M-AS1’, ‘AADACL2-AS1’, ‘AAK1’, ‘ABCA1’, ‘ABCA10’, ‘ABCA13’, ‘ABCA5’, ‘ABCA9’, ‘ABCA9-AS1’, ‘ABCB1’, ‘ABCC1’, ‘ABCD2’, ‘ABCG1’, ‘ABCG2’, ‘ABCG4’, ‘ABHD17B’, ‘ABHD3’, ‘ABL1’, ‘ABL2’, ‘ABLIM1’, ‘ABTB2’, ‘AC002066.1’, ‘AC002331.1’, ‘AC002454.1’, ‘AC002465.2’, ‘AC003092.1’, ‘AC004054.1’, ‘AC005307.1’, ‘AC005355.1’, ‘AC005394.1’, ‘AC005616.1’, ‘AC006369.2’, ‘AC006994.2’, ‘AC007091.1’, ‘AC007179.1’, ‘AC007319.1’, ‘AC007364.1’, ‘AC007391.2’, ‘AC007879.2’, ‘AC007879.3’, ‘AC007879.4’, ‘AC007880.1’, ‘AC007952.4’, ‘AC008691.1’, ‘AC009313.1’, ‘AC010884.1’, ‘AC010983.1’, ‘AC011306.1’, ‘AC011997.1’, ‘AC012123.1’, ‘AC012507.3’, ‘AC015849.2’, ‘AC016735.1’, ‘AC018685.2’, ‘AC018742.1’, ‘AC020743.2’, ‘AC022182.1’, ‘AC024028.1’, ‘AC034228.2’, ‘AC034228.3’, ‘AC062028.1’, ‘AC064834.1’, ‘AC068489.1’, ‘AC068492.1’, ‘AC068831.6’, ‘AC072062.1’, ‘AC073072.1’, ‘AC079466.1’, ‘AC083843.2’, ‘AC084809.2’, ‘AC091153.4’, ‘AC092159.2’, ‘AC092718.1’, ‘AC097381.1’, ‘AC098617.1’, ‘AC099342.1’, ‘AC099344.3’, ‘AC100830.3’, ‘AC106053.1’, ‘AC112721.2’, ‘AC116609.2’, ‘AC133644.2’, ‘AC147651.1’, ‘AC233755.1’, ‘AC234582.2’, ‘ACACA’, ‘ACADL’, ‘ACAN’, ‘ACER2’, ‘ACER3’, ‘ACKR2’, ‘ACOT1’, ‘ACOT12’, ‘ACOT6’, ‘ACOXL’, ‘ACP7’, ‘ACSBG1’, ‘ACSF3’, ‘ACSL1’, ‘ACSL6’, ‘ACSM6’, ‘ACSS3’, ‘ACTA2-AS1’, ‘ACTB’, ‘ACTG1’, ‘ACTL8’, ‘ACTN1’, ‘ACTN1-AS1’, ‘ACTN2’, ‘ACTRT3’, ‘ACVR1C’, ‘ACVR2A’, ‘ACYP2’, ‘ADA’, ‘ADAM10’, ‘ADAM11’, ‘ADAM12’, ‘ADAM19’, ‘ADAM22’, ‘ADAM23’, ‘ADAM28’, ‘ADAM7’, ‘ADAMTS17’, ‘ADAMTS19’, ‘ADAMTS3’, ‘ADAMTS4’, ‘ADAMTS5’, ‘ADAMTS6’, ‘ADAMTS9’, ‘ADARB1’, ‘ADARB2’, ‘ADCY5’, ‘ADCY9’, ‘ADCYAP1’, ‘ADD3’, ‘ADGRB3’, ‘ADGRE2’, ‘ADGRE5’, ‘ADGRG1’, ‘ADGRG5’, ‘ADGRV1’, ‘ADK’, ‘ADM’, ‘ADM5’, ‘ADRA2A’, ‘ADRB1’, ‘ADTRP’, ‘AF067845.1’, ‘AF067845.2’, ‘AFAP1’, ‘AFAP1-AS1’, ‘AFF1’, ‘AFF2’, ‘AFF3’, ‘AGAP1’, ‘AGBL1’, ‘AGBL4’, ‘AGPAT3’, ‘AGPAT5’, ‘AGTPBP1’, ‘AHCYL2’, ‘AHI1’, ‘AHNAK’, ‘AHR’, ‘AHSP’, ‘AIF1’, ‘AIM2’, ‘AIRE’, ‘AJ011932.1’, ‘AJAP1’, ‘AK5’, ‘AK8’, ‘AK9’, ‘AKAP12’, ‘AKAP6’, ‘AKT3’, ‘AL049794.1’, ‘AL109767.1’, ‘AL133475.1’, ‘AL590235.1’, ‘ALAS2’, ‘ALB’, ‘ALCAM’, ‘ALDH1A2’, ‘ALOX5’, ‘ALOX5AP’, ‘ALOXE3’, ‘ALPK1’, ‘ALPK2’, ‘AMBN’, ‘AMHR2’, ‘AMN1’, ‘AMY2A’, ‘ANGPT1’, ‘ANGPT2’, ‘ANGPTL1’, ‘ANK2’, ‘ANK3’, ‘ANKAR’, ‘ANKH’, ‘ANKIB1’, ‘ANKRD17’, ‘ANKRD20A2’, ‘ANKRD26’, ‘ANKRD28’, ‘ANKRD30A’, ‘ANKRD30BL’, ‘ANKRD31’, ‘ANKRD33B’, ‘ANKRD45’, ‘ANKRD55’, ‘ANKRD6’, ‘ANKRD60’, ‘ANKRD62’, ‘ANKRD7’, ‘ANKS1B’, ‘ANKS4B’, ‘ANLN’, ‘ANO1’, ‘ANO10’, ‘ANO2’, ‘ANO5’, ‘ANO6’, ‘ANO7’, ‘ANTXR1’, ‘ANTXR2’, ‘ANTXRL’, ‘ANXA1’, ‘ANXA13’, ‘ANXA2’, ‘ANXA4’, ‘ANXA5’, ‘AOAH’, ‘AOC3’, ‘AP000345.2’, ‘AP000866.1’, ‘AP001042.1’, ‘AP001471.1’, ‘AP001476.2’, ‘AP001476.3’, ‘AP001626.1’, ‘AP002856.4’, ‘AP1S3’, ‘APBA2’, ‘APBB1IP’, ‘APBB2’, ‘APLF’, ‘APLP2’, ‘APOBEC1’, ‘APOBEC3A’, ‘APOBEC4’, ‘APOD’, ‘APOH’, ‘APOLD1’, ‘APP’, ‘AQP1’, ‘AQP3’, ‘AQP9’, ‘AR’, ‘ARAP2’, ‘ARC’, ‘AREG’, ‘ARG2’, ‘ARHGAP10’, ‘ARHGAP24’, ‘ARHGAP25’, ‘ARHGAP26’, 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‘BCL11A’, ‘BCL11B’, ‘BCL2’, ‘BCL2A1’, ‘BCL2L1’, ‘BCL2L11’, ‘BCL6’, ‘BCO1’, ‘BDNF-AS’, ‘BEND6’, ‘BEX1’, ‘BHMG1’, ‘BICC1’, ‘BICD1’, ‘BID’, ‘BIRC3’, ‘BIRC5’, ‘BLACAT1’, ‘BLK’, ‘BLNK’, ‘BMP10’, ‘BMP2K’, ‘BMP3’, ‘BMPER’, ‘BMPR1A’, ‘BMPR1B’, ‘BMPR2’, ‘BNC2’, ‘BOK’, ‘BORCS5’, ‘BPIFB1’, ‘BRAF’, ‘BRCA2’, ‘BRI3’, ‘BRINP1’, ‘BRINP2’, ‘BRINP3’, ‘BRIP1’, ‘BST2’, ‘BTBD11’, ‘BTBD9’, ‘BTG2’, ‘BTLA’, ‘BTNL8’, ‘BTNL9’, ‘C10orf53’, ‘C11orf49’, ‘C11orf52’, ‘C11orf53’, ‘C11orf80’, ‘C11orf88’, ‘C11orf91’, ‘C12orf42’, ‘C12orf50’, ‘C12orf65’, ‘C12orf71’, ‘C12orf75’, ‘C12orf77’, ‘C15orf41’, ‘C16orf89’, ‘C1orf105’, ‘C1orf141’, ‘C1orf162’, ‘C1orf21’, ‘C1orf229’, ‘C1orf87’, ‘C1QA’, ‘C1QB’, ‘C1QC’, ‘C1QTNF4’, ‘C20orf194’, ‘C22orf34’, ‘C2CD4B’, ‘C2CD4C’, ‘C2orf66’, ‘C2orf73’, ‘C2orf78’, ‘C2orf81’, ‘C2orf83’, ‘C3AR1’, ‘C3orf52’, ‘C4orf17’, ‘C4orf47’, ‘C5AR1’, ‘C5orf17’, ‘C5orf66-AS2’, ‘C6orf118’, ‘C6orf58’, ‘C7orf65’, ‘C8orf34-AS1’, ‘C8orf37-AS1’, ‘C9orf135’, ‘C9orf50’, ‘CA12’, ‘CA3’, ‘CA8’, ‘CACHD1’, ‘CACNA1B’, ‘CACNA1C’, ‘CACNA1S’, ‘CACNA2D3’, ‘CACNB2’, ‘CACNB4’, ‘CACNG2’, ‘CACNG3’, ‘CACNG7’, ‘CADM1’, ‘CADM2’, ‘CADM3’, ‘CALCB’, ‘CALCR’, ‘CALCRL’, ‘CALD1’, ‘CALML3’, ‘CALML6’, ‘CALN1’, ‘CALR’, ‘CALR3’, ‘CALY’, ‘CAMK1D’, ‘CAMK2D’, ‘CAMK4’, ‘CAMKMT’, ‘CAMSAP2’, ‘CAPG’, ‘CAPN8’, ‘CAPS2’, ‘CARD11’, ‘CARD16’, ‘CARD17’, ‘CARD18’, ‘CASC1’, ‘CASC11’, ‘CASC15’, ‘CASC19’, ‘CASC2’, ‘CASC8’, ‘CASC9’, ‘CASK’, ‘CASK-AS1’, ‘CASP1’, ‘CASP8’, ‘CASS4’, ‘CAST’, ‘CATSPER4’, ‘CATSPERB’, ‘CAV1’, ‘CBARP’, ‘CBFA2T2’, ‘CBLB’, ‘CBS’, ‘CCDC138’, ‘CCDC141’, ‘CCDC146’, ‘CCDC168’, ‘CCDC171’, ‘CCDC173’, ‘CCDC178’, ‘CCDC188’, ‘CCDC190’, ‘CCDC26’, ‘CCDC3’, ‘CCDC30’, ‘CCDC7’, ‘CCDC85A’, ‘CCDC88A’, ‘CCDC89’, ‘CCDC91’, ‘CCIN’, ‘CCL14’, ‘CCL15’, ‘CCL17’, ‘CCL19’, ‘CCL20’, ‘CCL22’, ‘CCL25’, ‘CCL3’, ‘CCL4’, ‘CCL4L2’, ‘CCL5’, ‘CCM2L’, ‘CCNB3’, ‘CCND2’, ‘CCNJL’, ‘CCNT2-AS1’, ‘CCR4’, ‘CCR6’, ‘CCR7’, ‘CCR8’, ‘CCR9’, ‘CCSER1’, ‘CCSER2’, ‘CD109’, ‘CD14’, ‘CD160’, ‘CD163L1’, ‘CD177’, ‘CD19’, ‘CD1A’, ‘CD1B’, ‘CD1C’,Warning in .rowNamesDF<-(x, value = value) : duplicate 'row.names' are not allowed Warning: Missing on read: /var. Seurat does not support global variables metadata (_index).Error in h(simpleError(msg, call)) : error in evaluating the argument 'x' in selecting a method for function 't': attempt to apply non-function