I'm getting an error while trying to run the following command.

fitTimeSeries(CE_obj_file_aband_graph, lvl='Class', feature = "c__Clostridia",id="X.SampleID", time="Age", B=10, norm=F, log=F)
Error in sort.list(y) : 'x' must be atomic for 'sort.list'
Have you called 'sort' on a list?

Could someone tell me what is going wrong here? Output of str(pData(CE_obj_file_aband_graph)) is given below.

str(pData(CE_obj_file_aband_graph))

'data.frame':    104 obs. of  13 variables:
 $ X.SampleID          : Factor w/ 104 levels "C001","C002",..: 54 49 51 102 31 76 81 30 24 40 ...
 $ BarcodeSequence     : logi  NA NA NA NA NA NA ...
 $ LinkerPrimerSequence: logi  NA NA NA NA NA NA ...
 $ Age                 : num  1 16 16 16 8 5 5 5 5 8 ...
 $ Tissue              : Factor w/ 1 level "CE": 1 1 1 1 1 1 1 1 1 1 ...
 $ Flock               : Factor w/ 2 levels "R2 ","R3": 1 2 2 1 2 1 1 2 2 2 ...
 $ AgeFlock            : Factor w/ 12 levels "12Wk_R2","12Wk_R3",..: 5 4 4 3 12 9 9 10 10 12 ...
 $ AgeTissue           : Factor w/ 6 levels "12Wk_CE","16Wk_CE",..: 3 2 2 2 6 5 5 5 5 6 ...
 $ AgeFlockTissue      : Factor w/ 12 levels "12Wk_R2_CE","12Wk_R3_CE",..: 5 4 4 3 12 9 9 10 10 12 ...
 $ Weight__g           : int  153 14200 13400 16600 3500 1680 1418 1374 1663 3300 ...
 $ AvgWt               : int  143 13700 13700 16650 3270 1568 1568 1381 1381 3270 ...
 $ Bird.               : Factor w/ 104 levels "1","10","100",..: 13 8 10 5 78 48 54 66 59 88 ...
 $ Description         : Factor w/ 104 levels "C001","C002",..: 54 49 51 102 31 76 81 30 24 40 ...

I tried to build new MRexperiment object as described here:error using fitTimeSeries from metagenomeSeq. But still get the same error. 

packageVersion('metagenomeSeq')
[1] ‘1.14.2’​

Thanks

Hi Saranga,

It turns out above one of the parameters was missing. Currently you forgot to include a parameter for the case/control status :-). See the following as an example.

library(metagenomeSeq)
setwd("~/Downloads/Data") # your path

fd = read.csv("CE_obj_featureData.csv",row.names=1)
pd = read.csv("CE_obj_phenoData.csv",row.names=1)
counts= read.csv("mat_counts.tsv",sep="\t",row.names=1)

obj = newMRexperiment(counts,
    phenoData=AnnotatedDataFrame(pd),
    featureData = AnnotatedDataFrame(fd))
obj = filterData(obj)

fit = fitTimeSeries(obj, lvl='Class',class="Flock", feature = "c__Clostridia",id="X.SampleID", time="Age", B=10, norm=TRUE, log=TRUE)

Hi Joseph,

Thank you very much for the quick reply.

Sending my feature data ,pheno-data and count matrix to your email now.