[BioC] RNA-Seq - analysis of time series data?

[Jakob Hedegaard]

Hi,

I wonder how to analyze a RNA-Seq dataset of a time-series experiment.

The dataset origin from a challenge experiment with 4-6 samples per time point (T00,T06,T12,T24 and T48) from two series of challenge (with one of two different serotypes). In total 48 individual samples and two factors, time and serotype (see the table below for details)
RNA-Seq profiles have been obtained using Illumina GAIIx with multiplexing.

I have used edgeR (the Cox-Reid and GLM method) to obtain the genes significantly affected to each time point relative to time zero (e.g. T12-T00) - thus initially ignoring the potential difference between the serotypes.

But how can I obtain the genes significantly affected across the different contrastes?


        group lib.size norm.factors serotype time
AP_01 control  3734226    1.0575860      con  T00
AP_02 control  4528260    1.0581673      con  T00
AP_03 control  3648163    1.0594602      con  T00
AP_28 control  4671178    1.0430147      con  T00
AP_29 control  3746020    1.0528085      con  T00
AP_30 control  4471915    1.1277386      con  T00
AP_31 AP6.T06  7384334    0.9187757      AP6  T06
AP_32 AP6.T06  3649621    0.9035999      AP6  T06
AP_33 AP6.T06  5644324    0.8929802      AP6  T06
AP_34 AP6.T06  3791540    0.9396600      AP6  T06
AP_36 AP6.T06  3922243    0.8524249      AP6  T06
AP_37 AP6.T12  3113854    1.0491183      AP6  T12
AP_38 AP6.T12  2153867    1.0996506      AP6  T12
AP_39 AP6.T12  2979503    1.0905274      AP6  T12
AP_40 AP6.T12  5375493    1.0420513      AP6  T12
AP_41 AP6.T12  3769654    0.9094147      AP6  T12
AP_42 AP6.T12  2621303    1.1272673      AP6  T12
AP_43 AP6.T24  3537847    1.0037276      AP6  T24
AP_44 AP6.T24  3660552    1.0757808      AP6  T24
AP_45 AP6.T24  3284038    1.0701603      AP6  T24
AP_46 AP6.T24  3250374    1.0230341      AP6  T24
AP_47 AP6.T24  7208387    0.9535068      AP6  T24
AP_48 AP6.T24  4169075    0.9730747      AP6  T24
AP_49 AP6.T48  5989902    0.9825794      AP6  T48
AP_50 AP6.T48  3529028    0.9471979      AP6  T48
AP_51 AP6.T48  5104071    1.0772029      AP6  T48
AP_53 AP6.T48  4823387    0.9710606      AP6  T48
AP_54 AP6.T48  3788201    1.0976409      AP6  T48
AP_55 AP2.T06  4919578    0.7872065      AP2  T06
AP_56 AP2.T06  4580068    0.9533078      AP2  T06
AP_57 AP2.T06  3908180    0.9193207      AP2  T06
AP_58 AP2.T06  3466801    0.9887874      AP2  T06
AP_59 AP2.T06  4267998    0.8769085      AP2  T06
AP_60 AP2.T12  4533905    0.9058305      AP2  T12
AP_62 AP2.T12  5906089    0.9352388      AP2  T12
AP_63 AP2.T12  3676318    1.1260072      AP2  T12
AP_64 AP2.T12  2206081    1.0579246      AP2  T12
AP_65 AP2.T12  3955338    1.0221930      AP2  T12
AP_66 AP2.T12  3775918    0.9300664      AP2  T12
AP_67 AP2.T24  3853681    0.9659259      AP2  T24
AP_69 AP2.T24  3761829    0.9592286      AP2  T24
AP_70 AP2.T24  4263273    1.0742397      AP2  T24
AP_71 AP2.T24  4736798    0.9864702      AP2  T24
AP_72 AP2.T24  6387114    1.0462401      AP2  T24
AP_73 AP2.T48  3389351    1.0303610      AP2  T48
AP_75 AP2.T48  1489023    1.1863821      AP2  T48
AP_76 AP2.T48  3588175    1.0250639      AP2  T48
AP_78 AP2.T48  3848562    0.9855582      AP2  T48


sessionInfo()
R version 2.12.0 (2010-10-15)
Platform: x86_64-pc-mingw32/x64 (64-bit)

locale:
[1] LC_COLLATE=Danish_Denmark.1252  LC_CTYPE=Danish_Denmark.1252    LC_MONETARY=Danish_Denmark.1252 LC_NUMERIC=C                    LC_TIME=Danish_Denmark.1252    

attached base packages:
[1] grDevices datasets  splines   graphics  stats     tcltk     utils     methods   base     

other attached packages:
[1] edgeR_1.8.2     svSocket_0.9-50 TinnR_1.0.3     R2HTML_2.2      Hmisc_3.8-3     survival_2.35-8

loaded via a namespace (and not attached):
[1] cluster_1.13.1  grid_2.12.0     lattice_0.19-13 limma_3.6.6     svMisc_0.9-60   tools_2.12.0  


Best regards

Jakob Hedegaard
Project scientist
 
AARHUS UNIVERSITY
Faculty of Agricultural Sciences
Dept. of Genetics and Biotechnology
Blichers Allé 20, P.O. BOX 50
DK-8830 Tjele
Denmark