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HCBravoLab / metagenomeSeq

Statistical analysis for sparse high-throughput sequencing
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diff abundance after aggTax #91

Open JHBI115 opened 9 months ago

JHBI115 commented 9 months ago

Hi , I'm not a statistician and not very pro-efficient in R. I'm trying to run fitFeatureModel on the MRexperiment object that was output by aggTax function . And I get this ERROR ; Error in lmFit(log(mat), mod, weights = weights) : row dimension of design doesn't match column dimension of data object

My intial obj :

obj_Treat MRexperiment (storageMode: environment) assayData: 2549 features, 48 samples element names: counts protocolData: none phenoData sampleNames: F110-2 F110-d ... F142-d (48 total) varLabels: patientID preterm_del ... treatment2 (12 total) varMetadata: labelDescription featureData featureNames: 36ba457bd2f0549ccde2199095e7aa18 b3212620482d3313452d1cce8bfb2f73 ... d1b3d9b8720fb1e710a3d20a348b8388 (2549 total) fvarLabels: OTUID Taxon ... Species (9 total) fvarMetadata: labelDescription experimentData: use 'experimentData(object)' Annotation:

Class = aggTax(obj_Treat, lvl = "Class", out = "MRexperiment", returnFullHierarchy=FALSE) Class MRexperiment (storageMode: environment) assayData: 41 features, 48 samples element names: counts protocolData: none phenoData sampleNames: F110-2 F110-d ... F142-d (48 total) varLabels: patientID preterm_del ... treatment2 (12 total) varMetadata: labelDescription featureData featureNames: [Chloracidobacteria] [Saprospirae] ... ZB2 (41 total) fvarLabels: Taxa fvarMetadata: labelDescription experimentData: use 'experimentData(object)' Annotation:

Class = cumNorm(Class, p = 0.5) pd = pData(Class) mod <- model.matrix(~1 + treatment, data = pd) Class_flouride_vs_placebo = fitFeatureModel(Class, mod) Error in lmFit(log(mat), mod, weights = weights) : row dimension of design doesn't match column dimension of data object

dim(mod) [1] 48 2

What am I doing wrong ?

Thank you so much ! Cori