gene expression matrix

eva4 · February 1, 2023, 5:29pm

I have a matrix of gene expression, where each column is a patient and each row is labeled as follows:
Column 1: cell line - A, B, C
Column 2: gene - abc, def, ghi (repeats for each cell line)
Column 3: expression level for patient 1
Column 4: expression level for patient 2
and so on for other patients

I want to use apply function to create a vector of most active genes across patients for each cell line. The criterion for active gene is more than 70% of patients show expression level > 0.

The output should be a vector of following format corresponding to cell lines A, B and C:
( [abc, def], [ abc], [ ] )
That means, for example, that for cell line B gene abc had expression level > 0 in more than 70% of patients.

Any suggestions are welcome.
Many thanks!

technocrat · February 2, 2023, 8:39am

It's more likely that a question will attract an answer with a reprex. See the FAQ.

eva4 · February 2, 2023, 4:42pm

Could you please elaborate? Are you saying this can be solved using a reprex function? I would prefer apply function but am also curious about other methods.

andresrcs · February 2, 2023, 5:03pm

reprex stands for REPRoducible EXample, you can use the reprex() function to create one but it is not a solution to your problem, technocrat is asking you to better explain your problem by providing a reproducible example which is the most effective (and polite) way of asking programming related questions.

If you want more details about it, click on the link technocrat gave you and read the REPREX guide

technocrat · February 2, 2023, 7:16pm

Sorry to be obscure—just that this is hard to solve in the abstract, and some representative data would make it more likely to attempt. It can be faked.

eva4 · February 3, 2023, 4:37pm

Sure, please see the code chunk about how to load the data and below the chunk for data itself in text format (you would just need to save it as matrix.txt) Many thanks!:
{r}```
data0 <- read.table('matrix.txt',header=T)
cell_lines <- as.character(unlist(data0[1,]))
datamtx<- as.matrix(data0[-1,])
mode(datamtx) <- 'numeric'

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-A15K-01A-11R-A12P-07	TCGA-E2-A15L-01A-11R-A12D-07	TCGA-E2-A15M-01A-11R-A12D-07	TCGA-E2-A15O-01A-11R-A115-07	TCGA-E2-A15P-01A-11R-A115-07	TCGA-E2-A15R-01A-11R-A115-07	TCGA-E2-A15S-01A-11R-A115-07	TCGA-E2-A15T-01A-11R-A115-07	TCGA-E2-A1AZ-01A-11R-A12P-07	TCGA-E2-A1B0-01A-11R-A12P-07	TCGA-E2-A1B1-01A-21R-A12P-07	TCGA-E2-A1B4-01A-11R-A12P-07	TCGA-E2-A1B5-01A-21R-A12P-07	TCGA-E2-A1B6-01A-31R-A12P-07	TCGA-E2-A1BC-01A-11R-A12P-07	TCGA-E2-A1BD-01A-11R-A12P-07
	LumA	LumA	LumA	Normal	Basal	Her2	Basal	Basal	LumA	Basal	Basal	LumB	Basal	Basal	LumA	Her2	Her2	LumB	Basal	Basal	LumA	LumA	LumA	LumB	LumB	LumA	LumB	Her2	Her2	Normal	Basal	Her2	Basal	LumA	LumB	LumA	LumA	LumA	Her2	LumB	Normal	LumA	LumA	LumA	LumA	LumA	Her2	Basal	LumA	LumB	LumB	Basal	LumA	Basal	Her2	Basal	LumB	LumB	LumA	LumA	Normal	LumA	LumA	Basal	LumA	Her2	LumB	LumA	Basal	Normal	Normal	Basal	LumB	LumA	Basal	LumA	LumA	LumB	LumA	Basal	LumA	LumA	Basal	Basal	LumB	LumB	LumB	LumA	LumB	LumB	LumA	LumB	LumB	LumA	LumB	Her2	Her2	LumB	Her2	Basal	Basal	LumA	LumA	Her2	LumA	LumB	Basal	LumA	Basal	LumB	Basal	LumB	LumB	Her2	LumB	LumA	LumB	LumB	LumA	LumA	Her2	LumA	LumB	LumB	Basal	LumB	Her2	Her2	LumA	LumB	Basal	LumB	LumA	Her2	LumA	LumB	LumA	Her2	LumA	Her2	LumB	LumB	Her2	LumA	LumA	LumA	LumB	LumB	LumB	Her2	Her2	LumB	LumB	LumB	LumB	LumB	LumA	LumA	LumB	Her2	LumB	LumA	LumA	Normal	LumA	Her2	LumB	LumA	LumA	LumA	LumB	LumB	LumA	LumB	LumA	Her2	Basal	LumB	LumB	Basal	LumB	Basal	LumA	Basal	LumA	LumB	LumB	Basal	Basal	LumB	Basal	LumA	LumA	LumA	Her2	LumA	Basal	LumB	LumA	Basal	LumA	Her2	LumA	LumA	LumB	LumA	LumA	Basal	LumA	Her2	Her2	Basal	Her2	LumB	LumB	Basal	Normal	Normal	LumA	Her2	LumB	Basal	LumA	Basal	LumB	LumA	LumA	LumB	Normal	LumA	LumB	Her2	LumA	LumA	LumB	LumA	Basal	Her2	Basal	LumA	LumA	Basal	Basal	LumA	LumB	LumA	Her2	Normal	Basal	LumA	LumA	LumB	Basal	Her2	Basal	Her2	LumA	Basal	LumB	Basal	LumB	LumA	Her2	LumB	LumB	Basal	Basal	LumB	LumB	Basal	Basal	Basal	Basal	Normal	LumA	Normal	Basal	LumA	Basal	Basal	LumB	Her2	Normal	LumB	LumA	LumA	Basal	Basal	LumA	Basal	LumA	Her2	LumA	LumB	LumA	Basal	Her2	LumA	Basal	Her2	LumB	LumA	LumA	LumA	Basal	Basal	LumA	Her2	LumB	LumB	LumA	LumA	LumA	LumA	Normal	Her2	Basal	Basal	LumA	LumA	LumA	LumB	LumB	Basal	Normal	LumA	LumA	Basal	LumA	LumB	LumA	LumB	Basal	Her2	LumB	LumA	LumA	LumA	LumA	Basal	LumB	LumB	Her2	LumA	Basal	LumA	LumA	LumB	Her2	Basal	LumA	Basal	LumA	LumA	Normal	LumA	Her2	LumA	LumA	LumA	Basal	Her2	LumB	LumB	LumB	LumB	LumB	LumA	LumA	LumA	Normal	LumA	Basal	LumA	LumA	LumA	LumA	LumA	LumA	Her2	Basal	LumB	LumA	Basal	LumA	Normal	LumA	LumA	Her2	LumA	Normal	LumA	LumB	LumA	LumA	LumA	LumA	LumA	LumA	LumB	LumA	LumA	LumA	Basal	Basal	LumA	Normal	LumA	LumB	LumB	LumB	Her2	Basal	LumB	LumA	LumA	Her2	Basal	Basal	Basal	LumA	LumA	LumB	Basal	LumB	LumA	LumA	Her2	Basal	Her2	LumA	LumA	Her2	Basal	LumA	LumA	LumA	LumA	Her2	LumB	Basal	Basal	Her2	LumB	LumA	Basal	Her2	Her2	Her2	LumB	Basal	Her2	LumB	LumA	Her2	Her2	Basal	LumA	LumA	Basal	Her2	Her2	Her2	Her2	LumB	LumA	Her2	LumB	LumB	LumB	Basal	LumB	LumA	Basal	Basal	Normal	LumA	Basal	LumB	LumA	LumB	Basal	LumB	LumB	LumA	LumB	LumA	LumA	Basal	LumB	Her2	LumA	Basal	LumB	LumA	Her2	LumB	Basal	Basal	Basal	Basal	Her2	LumA	LumA	LumB	LumA	Basal	Basal	LumB	LumA	LumA	Normal	LumA	LumA	LumA	LumA	LumA	LumB	LumB	LumB	LumB	LumA	LumA	LumB	LumB	Basal	Her2	Normal	LumA	Basal	Normal	LumA	LumA
ACTR3B	0.465348584	-0.188155375	-0.234783381	-0.813540155	3.016897131	-0.020508117	-2.256694732	2.107828987	0.314252489	0.321549238	0.117596205	-0.362565473	1.780543099	1.114225337	-1.477900253	-0.50262746	-1.398169922	-1.203649272	-0.64838447	0.72731967	0.35892283	-0.845574663	-0.294403159	-0.740216726	0.162622485	0.437407375	0.71681947	0.123647168	-0.600866617	-0.161637921	2.664161606	2.236856866	2.13790583	0.036442119	-0.587874845	-0.515441263	-0.636816454	-0.136188285	0.82466898	-0.313979803	-0.001821321	-0.802861986	0.198394353	-0.558865818	-0.636816454	0.081824338	-0.074966781	1.738898239	-1.188521866	0.419610426	0.335608828	1.475325427	-0.57915434	0.7691425	0.288268944	0.518027553	-0.396557645	-0.670274717	-0.048627297	-0.69732608	0.810965329	-0.775988593	-0.768869814	2.216034436	-1.459569396	1.077919561	0.495959336	-0.433931238	1.921850872	-0.047915419	-0.027270958	0.139664422	-0.771717325	-1.687904249	3.289012478	-0.576662767	-0.223215364	0.607190266	1.296822031	1.620726499	-0.022821721	0.204445315	1.847815565	2.512709572	-0.462762295	0.213343789	-0.560823482	-1.01001847	0.854923793	-0.677037558	-0.007338375	-1.092062403	0.275277171	0.984841519	-0.128713566	-0.853227351	-0.889355157	-0.179968779	-0.404210333	1.661481512	-1.14527528	0.162266546	-0.990975734	-2.261855847	-0.537153541	0.13325752	1.321025881	-0.768691844	0.547748457	-0.32198843	-0.107001289	-0.293335342	-0.455821485	0.832855576	-0.208265927	-1.043654703	-0.793073664	-0.399049218	-0.089560279	-0.586273119	1.314263041	-0.482516908	0.308023557	0.884288758	-1.093842098	0.169741265	-0.44016017	-0.024779385	0.176860044	-0.554950489	0.80366858	-0.788090518	-0.340141318	-0.536263693	-0.354022938	-0.103263929	1.226524083	0.380457139	-0.621155139	0.517315675	0.585833927	-1.368626988	-0.97513645	-0.55121313	0.827694461	-0.386235415	0.19234339	0.174190502	-0.239232618	0.080578552	-1.036713893	0.079510735	0.460187469	0.559316474	-1.775287267	-0.455643515	-0.508144514	-0.617061841	-1.732040682	-0.875295567	-0.459914783	-0.354022938	-1.306515636	-1.202403486	-0.687537758	-0.559577696	-1.419170322	0.861508664	-0.99257746	-0.934915346	-0.296538793	-1.167699436	-1.274837067	-2.02782597	-0.476287976	0.647767309	2.929692082	-0.943635851	1.010113186	0.467128279	-0.37039613	2.279925482	-0.222681456	-0.083153377	-0.181036595	0.023094407	-1.043298764	-0.162527769	2.705272558	-0.701063439	1.750288286	-1.681497347	-0.490525535	-1.420060169	-0.656393097	-0.942390064	0.127206557	-0.385167598	-1.363465872	2.373359463	0.592062859	-1.535918306	-0.186731619	-0.81176046	-1.122139247	-1.426289102	-0.240478404	1.421222703	-0.462940264	-1.025857754	-2.019105465	1.290771069	-0.954669959	0.48083193	0.150876499	-1.175886032	-0.445855193	0.235234036	-0.493017108	0.391669216	-0.180502687	0.435983619	-0.685224154	0.058332366	-1.001119995	-0.780259861	-0.691156471	-0.350997456	0.164224211	-1.734710224	-0.8395237	-1.057180384	-0.782929403	-0.067314093	0.835881058	-0.753742407	2.010301708	-1.046680184	2.583541428	-0.351175426	-0.857676588	-0.179790809	1.805636797	-0.606561641	0.123113259	-1.369160896	-0.067314093	0.094104233	2.962082528	0.668589739	0.072213986	-0.533594151	0.85937303	1.894443571	3.733758227	-0.351709334	0.459297622	1.323695424	-0.150425844	1.850307138	-0.696080293	-0.343522738	0.254098802	-0.643757264	0.472645333	-0.585027333	0.839084509	-0.806777315	0.367287396	1.091801181	1.771110716	2.036463222	1.605599092	-0.620443261	0.809719543	-0.234071503	0.17152096	-0.390684652	2.564320723	1.954953197	-1.153639846	-0.379828513	0.263175246	0.324574719	-0.859812222	0.17152096	3.327809826	1.767195387	0.505391719	0.417296822	1.121700055	-0.997916544	-0.3705741	0.578537178	-0.102552051	0.326710353	-0.413998655	0.687810444	-1.112706864	-0.535729785	0.153724011	-0.136188285	-1.069994187	-0.362743443	1.655430549	1.385984745	-0.890245004	0.021314712	-0.900567235	-0.365057046	-0.253826116	-0.418269923	0.752769307	-0.388904957	-0.125510115	0.012950146	-0.010007918	1.448096096	0.922196259	-0.627917979	-0.239766526	0.687988413	-1.345846893	0.926645497	0.082180277	-0.719394296	-0.149891935	2.083803106	0.798685435	0.039645569	-0.346904158	0.474602998	-1.183182781	-1.193505012	0.368889122	-1.436611332	-0.750716926	0.389177643	-1.345846893	-0.367904558	-0.380718361	-0.313623864	-0.486076298	-0.851803595	2.687653578	-0.362565473	-0.558865818	0.328845987	0.117596205	0.434203924	-0.705156737	1.698499165	0.173656594	-0.449948492	0.159419035	-0.123196512	-1.112884834	-0.805531528	-0.536085724	-0.451906156	-0.786844732	-0.10290799	0.423881694	0.168495479	-0.967483762	-0.058237649	0.613419198	-0.959119196	-0.386235415	-0.049695113	0.33489695	-1.422017834	-1.206140845	0.319413604	-0.278385905	-0.826887867	-0.00911807	0.157995279	-0.039906792	-2.239609661	2.475869888	-0.303301634	-1.016425371	1.824857501	-0.024779385	1.24841433	-1.057180384	-1.643411877	-0.843439029	-0.840591517	0.885890484	-1.429848491	0.022738468	-0.92637281	-0.31842904	-0.942568034	-0.008228223	0.203199529	-0.147756301	0.160308882	0.20604704	-0.407947692	-0.491593352	-1.434475698	-2.059504539	0.787829296	0.624453306	0.008856848	0.620715947	0.453246659	0.017577353	-0.26290256	1.830018617	-0.824040355	-0.044178059	0.096595805	-0.611010878	1.502020851	0.221708355	0.193589176	-0.668850962	-0.527899127	-0.423964946	1.555055758	0.494179641	-0.188867253	-0.751606773	-0.334268324	1.335263441	0.290226608	-0.51294969	0.316566092	0.023984254	0.203555468	0.47015376	-0.304369451	-0.812472338	-0.687537758	-1.155241572	0.487238831	0.475314876	2.6869417	-0.43660078	-0.310598383	-0.612612603	-0.090628096	1.078987378	-0.539823083	0.113324937	-0.143307064	1.336509227	-0.408125662	-0.155942898	-0.643579294	0.146249293	-0.299386305	-0.328039392	0.030391156	0.285421432	2.691034999	-0.283013112	-0.864617398	-1.120181583	-0.155942898	1.025240593	-0.672410351	-1.047925971	-1.525418106	0.25125129	2.588346604	-0.349217761	-0.402964547	-0.761751034	0.614309045	-0.963568433	-0.093475607	-0.534128059	0.665030349	0.246624084	-1.244760224	-0.144374881	-0.22463912	-0.407947692	-0.856786741	0.213699728	1.101233564	-0.688605575	-1.066256828	1.591895442	0.348066692	0.548816274	-0.432329512	0.780176608	0.742269107	-0.358828114	0.201597803	-0.539289174	2.250916455	0.542409372	-0.630053613	1.640303143	0.334363041	-1.055756628	0.020780804	0.372448512	0.437585344	4.211072394	0.118308083	-0.107001289	-0.230334144	0.188250092	0.782668181	1.088063822	-0.350463548	-0.357226388	0.041781203	0.020424865	-0.254715963	-0.11696758	-1.356703032	-0.37039613	0.411957738	0.621249855	-0.224995059	0.319235635	1.927723865	0.718599165	-0.053432473	-0.052542625	0.599893517	-1.680251561	-1.669395422	0.080400582
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system · March 17, 2023, 4:38pm

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