[R] Differential Gene Expression in R

[Anas Jamshed]

EdgeR in Galaxy requires factor, group, and contrast so what should I do?

On Mon, Aug 23, 2021 at 12:09 AM Matthew McCormack <
mccormack using molbio.mgh.harvard.edu> wrote:

>    You can look into the edgeR vignette. To get the vignette type
> 'vignette("edgeR")' in the R command line. Also, just type 'vignette()'
> and R will list all the vignette's for your loaded packages.  Vignettes
> often have a model analysis that you can follow along and try to adjust
> to your specific data. There is also Biostars,
> https://www.biostars.org/ . However, I doubt you will find anyone on an
> online forum that will walk you through the whole analysis. Although,
> there is probably only 10 plus or minus 4 commands for the whole analysis.
>
>      Alternatively, if you click on the URL you provided below, and at
> the bottom of that page click on 'SRA Run Selector', scroll down a
> little on the page you get to and select the runs you want to analyze by
> checking the appropriate boxes, then click on the grey box on the right
> that has the word 'Galaxy' in it, and it will load your selected runs
> into an instance of Galaxy in which it is a little easier to analyze
> data than on the R command line.
>
>     In the leftmost column of the galaxy page, scroll down to Genomics
> Analysis and then click RNA-seq and scroll down a little and you will
> see that edgeR is available. You will still have to learn a little about
> edgeR analysis, so reading the vignette will be very helpful.
>
>     Also, for the comparisons you want to do, statistical help is
> recommended.
>
> Matthew
>
> On 8/22/21 2:13 PM, Anas Jamshed wrote:
> >          External Email - Use Caution
> >
> >   I have downloaded data from:
> >
> https://secure-web.cisco.com/11QZcUaPohN9T-S3dXC_GmXle9LtWOwH3EZzb3DhLTvve9_5ltt1RpGGssjgmLGBrEaZGEhesLze6XzCJazVRBgu4xc8kHortjlXtfoXyWlsSXouXicfjhSkh_t-WWivcXHpnTvUtVtq9wEKnxWPCPFNu9hprFt91ho02_8XiRAYDkVLcT76BhLbTleUjEezCPbuh9ieLGA6MVW9oiqYERXpYc2dL-KmvVBER3bd-7KiXJJngxji9kbJDDmm-Irysc8aUWDHZZpWkIB8yT_HFAg/https%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fgeo%2Fquery%2Facc.cgi%3Facc%3DGSE162562%26fbclid%3DIwAR0iZQhttG8HzGhFIIMWbFgNszQrVDgiyVChYzQ_ypCx_d-1pn_tm7STjGs
> >
> > and now I want to compare:
> > healthy vs Mild healthy vs Highly exposed seronegative (ishgl) Healthy vs
> > Asymptomatic covid19 patient healthy vs Highly exposed seronegative (non
> > ishgl)  from this data.
> >
> > I started  like  :
> >
> > library(edgeR)
> > library(limma)
> > library(GEOquery)
> > library(Biobase)
> >
> > Sys.setenv("VROOM_CONNECTION_SIZE" = 131072 * 2)
> >
> > setwd("D:\\")
> >
> > untar("GSE162562_RAW.tar")
> >
> > filelist = list.files(pattern = ".*.txt.gz")
> >
> >
> >
> > But after getting text files I don't know how to proceed further. I want
> to
> > find degs from these files  *Plz help me *
> >
> >       [[alternative HTML version deleted]]
> >
> > ______________________________________________
> > R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
> >
> https://secure-web.cisco.com/1tH9oPhtwGwMZPdSa6iYRfgPKcDjB0RbwLvAsZlByhBsnZOnWMGyfAJedegd7zgzjhBGoJR4l667r5yELyZUobz_rb-7cCszSEx-M4al0kObEUewwS1-66OaSN7ZHYe8OS9Oz6xG6KzS1XBqB5GDyXiA8FMoIEfaq49EamqyjBtwwgsNKpMdy2IyCTZ2dSL_cdkkD5dacTj5gg4PLprBua7uc32IM4bJmSXSAMxd31lqPP9m3V83kjORuTO61SZzQOeTSf8g8HwY6bDJLlOATxA/https%3A%2F%2Fstat.ethz.ch%2Fmailman%2Flistinfo%2Fr-help
> > PLEASE do read the posting guide
> http://secure-web.cisco.com/1qNZPXyZ9T-DwVY58dRhW-s2KI0g8PKqYBjd8eU1WX1DwW8TqASTq2NkdBNjUHF6T9QiEWRKhGinSfo78D3RrHq9hc9HVXYF7t9KAzK-sUNE0Y0IB62wcBJrH8Gd0LS7aus-36dSfndVD9CShsOMfwyMj5KIVQI8sppBOu5xbWhJEYfH3MgGhC_TVJIkQ126GdEuG4wK7xnnBh90fF4tdTJbHmaIWBn4yxPbhSdrYqs7GCgf_Gp4kee0aSyzxk_0WBkd2fPtnz5Ecbqkb1P8C6g/http%3A%2F%2Fwww.R-project.org%2Fposting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
> >
>
> ______________________________________________
> R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

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