[R] Mann-Whitney by group

[David Chertudi]

The time has come to shake the cobwebs off of this analysis.  I have
more data now and need to run the same tests, the same way as above.
My question is this--some of the pairs include NAs, and so are gumming
up the works.  I'm not sure how to exclude them using the lhs ~ rhs
syntax.  Any ideas here?

Many thanks, as usual.  Data and syntax below.

David


sara.data=structure(list(Groups = c(1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L,
2L), Pairs = c(1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L), Actb =
c(2.2734065552504,
1.69621901296377, 1.07836251830772, 1.46314001007756, 1.76537848566894,
0.689064098855446, 0.462820758081676, NA, NA, 2.22119254577143
), Bcl2 = c(0.12954440593121, 0.0902306425601895, 0.219044589401239,
0.103793432483774, 0.119463699676088, 0.112179645963861, 0.136910739776212,
0.433953247043377, 0.401539702575691, 0.352218179109105), Bcl6 =
c(1.78964109252879,
1.56011379020288, 0.750029838175481, 1.80189108290585, 1.09372632818505,
0.275815381178548, 0.785680035605173, NA, NA, 0.311865838414934
), Ccl5 = c(0.140676314771846, 0.103227179167928, 0.210718001043218,
0.101548390950462, 0.140625579216236, 0.218846310909471, 0.132902076760262,
0.35763207205821, 0.320733407260836, 0.0983004520984843), Ccr7 =
c(0.116274608274044,
0.0623582657156311, 0.111654418769019, 0.110221412062233, 0.0646423645035265,
0.0924168984762384, 0.0322085814124609, NA, NA, 0.0315246913534493
), Cd27 = c(0.599332581326994, 0.536313800392409, 0.776647646561188,
0.511624999868611, 0.481254858629634, 0.365428233004039, 0.30446734845483,
0.880574935388197, 1.19362122336861, 0.121581553928565), Cd28 =
c(0.8476006082089,
0.976603410250505, 0.976783190446247, 0.8288118647421, 0.854672311976977,
0.576719839424659, 0.4221908111396, 1.22864113852622, 5.19562728663742,
0.401610355554234), Cd40 = c(0.209298226865743, 0.0680133680665235,
0.0233440779283003, 0.191986570448918, 0.128784506152115, NA,
NA, NA, NA, NA)), .Names = c("Groups", "Pairs", "Actb", "Bcl2",
"Bcl6", "Ccl5", "Ccr7", "Cd27", "Cd28", "Cd40"), class = "data.frame",
row.names = c(NA,
-10L))

results=apply(saradata[,4:length(saradata)], 2,
              function(x)

wilcox.test(x~saradata$Groups,paired=TRUE,alternative="two.sided"))

# Extract p-values from saved results
lapply(results, function(x) x[['p.value']])


--
I drink your milkshake.


On Tue, Jul 10, 2012 at 3:13 PM, R. Michael Weylandt
<michael.weylandt at gmail.com> <michael.weylandt at gmail.com> wrote:
> Untested, I think you need to lapply() over thing with some sort of extractor:
>
> lapply(thing, function(x) x[['p.value']])
>
> Michael
>
> On Jul 10, 2012, at 3:45 PM, Oxenstierna <david.chertudi at gmail.com> wrote:
>
>> This works very well--thanks so much.
>>
>> By way of extension:  how would one extract elements from the result object?
>>
>> For example:
>>
>> thing<=apply(Dtb[,3:10], 2, function(x) wilcox.test(x~Dtb$Group))
>>
>> summary(thing)$p.value
>>
>> Does not provide a list of p-values as it would in a regression object.
>> Ideally, I would like to be able to extract the W score and p-value by
>> A,B,C,...
>>
>> Any ideas greatly appreciated!
>>
>>
>> --
>> View this message in context: http://r.789695.n4.nabble.com/Mann-Whitney-by-group-tp4635618p4636055.html
>> Sent from the R help mailing list archive at Nabble.com.
>>
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