error using fitTimeSeries in metagenomeSeq
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wijera81 • 0
@wijera81-11633
Last seen 5.0 years ago

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

metagenomeseq fittimeseries • 710 views
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@joseph-nathaniel-paulson-6442
Last seen 4.6 years ago
United States

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)
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Thanks, Joseph!! That worked.

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@joseph-nathaniel-paulson-6442
Last seen 4.6 years ago
United States
I'd be happy to look at the data and see what's going on? You can email me directly if you don't want to out the data online. On Oct 8, 2016, 11:04 AM, at 11:04 AM, "wijera81 [bioc]" <noreply@bioconductor.org> wrote: >wijera81 posted the Question: "error using fitTimeSeries in >metagenomeSeq": > >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 ... > >--- >See the full post at: error using fitTimeSeries in metagenomeSeq >Replying to this email will post an answer to the question above.
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wijera81 • 0
@wijera81-11633
Last seen 5.0 years ago

Hi Joseph,

Thank you very much for the quick reply.

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

 

 

 

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