[Correlation Browser / New Search] [List of best correlations] [List of all variables] [Stats] [Help/About]

Correlations in the bone dataset

Use the form to search for:

an EntrezGene ID (e.g. "1234")
an Accession Number (e.g. "BE644809" or "NM_005715")
a Gene Symbol (e.g. "HMGCR" or "ZNF532", not case-sensitive)
a variable label (e.g. "1562529_s_at" or "hsa-miR-29c*")
a variable number (e.g. "#1234" for the 1234^th variable in the dataset)

(View the full list of available key terms [here]).

Starting timer.
Connected to database.
Searching for user input in variable labels, Entrez IDs, Accession Numbers...
Evaluating targets, filters and restrictions...

Finding correlations with 2 variables:
id	Label1	AccNum	GeneSym	Info	Gene Name
3287	202352_s_at	AI446530	PSMD12		proteasome (prosome, macropain) 26S subunit, non-ATPase, 12
3288	202353_s_at	NM_002816	PSMD12		proteasome (prosome, macropain) 26S subunit, non-ATPase, 12

Fetching correlation data, please wait...
Getting list of correlations for id 3287.
Getting list of p-values for id 3287.
1 of 2 done.
Getting list of correlations for id 3288.
Getting list of p-values for id 3288.
2 of 2 done.
Calculating corrections for multiple testing (n=46234), please wait...
Done; whole program took 0.223 seconds. Transmitting 50 results:

Rank	Label1	Label2	AccNum	GeneSym	Pearson r	Raw p	Bonferroni	FDR (BH)
1	202352_s_at	220083_x_at	NM_016017	UCHL5	0.770798	9.935052e-18	4.593372e-13	4.593372e-13
2	202352_s_at	202303_x_at	NM_003601	SMARCA5	0.765614	2.218565e-17	1.025731e-12	5.128656e-13
3	202352_s_at	203138_at	NM_003642	HAT1	0.763267	3.169886e-17	1.465565e-12	4.885217e-13
4	202353_s_at	229428_at	AI400463	PARG	0.762205	3.720366e-17	1.720074e-12	4.300185e-13
5	202353_s_at	221502_at	AL120704	KPNA3	0.759951	5.212360e-17	2.409882e-12	4.819765e-13
6	202353_s_at	218432_at	NM_012175	FBXO3	0.753765	1.290654e-16	5.967209e-12	9.945348e-13
7	202353_s_at	234982_at	BF577193	UBR3	0.749706	2.306218e-16	1.066257e-11	1.523224e-12
8	202352_s_at	233208_x_at	AA583986	CPSF2	0.748565	2.709542e-16	1.252730e-11	1.565912e-12
9	202352_s_at	205329_s_at	NM_003794	SNX4	0.743091	5.802473e-16	2.682715e-11	2.980795e-12
10	202352_s_at	213859_x_at	AI652586	SMARCA5	0.741640	7.078014e-16	3.272449e-11	3.272449e-12
11	202352_s_at	218119_at	NM_006327		0.739215	9.836387e-16	4.547755e-11	4.134323e-12
12	202353_s_at	208905_at	BC005299	CYCS	0.738615	1.066383e-15	4.930315e-11	4.108595e-12
13	202353_s_at	214553_s_at	NM_006628	ARPP19	0.737534	1.233030e-15	5.700790e-11	4.385223e-12
14	202353_s_at	209512_at	BC004331	HSDL2	0.737285	1.274810e-15	5.893955e-11	4.209968e-12
15	202352_s_at	221547_at	BC000794	PRPF18	0.737006	1.323173e-15	6.117559e-11	4.078373e-12
16	202353_s_at	200883_at	NM_003366	UQCRC2	0.736582	1.400186e-15	6.473618e-11	4.046011e-12
17	202353_s_at	201816_s_at	NM_001483	GBAS	0.734520	1.840907e-15	8.511251e-11	5.006618e-12
18	202352_s_at	203771_s_at	AA740186	BLVRA	0.731994	2.565436e-15	1.186104e-10	6.589465e-12
19	202352_s_at	52285_f_at	AW002970	CEP76	0.731452	2.753437e-15	1.273024e-10	6.700126e-12
20	202353_s_at	212568_s_at	BF978872	DLAT	0.729422	3.582785e-15	1.656465e-10	8.282324e-12
21	202353_s_at	217196_s_at	AL110158	CAMSAP1L1	0.727426	4.630895e-15	2.141048e-10	1.019547e-11
22	202352_s_at	222035_s_at	AI984479	PAPOLA	0.726640	5.120248e-15	2.367295e-10	1.076043e-11
23	202352_s_at	218549_s_at	NM_016033	FAM82B	0.725382	6.009091e-15	2.778243e-10	1.207932e-11
24	202352_s_at	201532_at	NM_002788	PSMA3	0.723187	7.927240e-15	3.665080e-10	1.527117e-11
25	202353_s_at	225845_at	BG253884	ZBTB44	0.722056	9.134810e-15	4.223388e-10	1.689355e-11
26	202353_s_at	213149_at	AW299740	DLAT	0.721441	9.863949e-15	4.560498e-10	1.754038e-11
27	202352_s_at	225737_s_at	BE966247	FBXO22	0.721409	9.903358e-15	4.578719e-10	1.695822e-11
28	202352_s_at	233124_s_at	AK021464	ECHDC1	0.720420	1.119949e-14	5.177971e-10	1.849275e-11
29	202352_s_at	201014_s_at	NM_006452	PAICS	0.718546	1.411997e-14	6.528227e-10	2.251113e-11
30	202353_s_at	212325_at	AK027231	LIMCH1	0.717960	1.517612e-14	7.016525e-10	2.338842e-11
31	202353_s_at	226742_at	AI890133	SAR1B	0.713367	2.653310e-14	1.226731e-9	3.957198e-11
32	202353_s_at	227682_at	BE645154		0.713314	2.670104e-14	1.234496e-9	3.857799e-11
33	202353_s_at	209406_at	AF095192	BAG2	0.711726	3.230986e-14	1.493814e-9	4.526709e-11
34	202352_s_at	218156_s_at	NM_018128	TSR1	0.710683	3.659143e-14	1.691768e-9	4.975789e-11
35	202353_s_at	221482_s_at	BC003418	ARPP19	0.708316	4.843890e-14	2.239524e-9	6.398640e-11
36	202352_s_at	208777_s_at	AF001212	PSMD11	0.707829	5.129916e-14	2.371766e-9	6.588238e-11
37	202353_s_at	242852_at	H23213	LOC285147	0.707071	5.607527e-14	2.592584e-9	7.006984e-11
38	202352_s_at	201068_s_at	NM_002803	PSMC2	0.706850	5.755274e-14	2.660894e-9	7.002352e-11
39	202352_s_at	235025_at	AW196959	WDR89	0.706502	5.994604e-14	2.771545e-9	7.106526e-11
40	202353_s_at	200731_s_at	AW165960	PTP4A1	0.704617	7.467277e-14	3.452421e-9	8.631052e-11
41	202353_s_at	202930_s_at	NM_003850	SUCLA2	0.703418	8.579778e-14	3.966775e-9	9.675060e-11
42	202352_s_at	210691_s_at	AF275803	CACYBP	0.700476	1.202767e-13	5.560875e-9	1.324018e-10
43	202353_s_at	206833_s_at	NM_001108	ACYP2	0.698446	1.514922e-13	7.004089e-9	1.628858e-10
44	202353_s_at	210372_s_at	AF208012	TPD52L1	0.696897	1.804172e-13	8.341407e-9	1.895774e-10
45	202352_s_at	201699_at	NM_002806	PSMC6	0.696750	1.834327e-13	8.480829e-9	1.884629e-10
46	202353_s_at	204062_s_at	BG526973	ULK2	0.696443	1.898758e-13	8.778718e-9	1.908417e-10
47	202353_s_at	215034_s_at	AI189753	TM4SF1	0.694108	2.464750e-13	1.139552e-8	2.424580e-10
48	202353_s_at	209139_s_at	AF083033	PRKRA	0.694075	2.473693e-13	1.143687e-8	2.382682e-10
49	202353_s_at	225267_at	AI935246	KPNA4	0.694026	2.487267e-13	1.149963e-8	2.346863e-10
50	202352_s_at	201821_s_at	BC004439	TIMM17A	0.691967	3.124163e-13	1.444426e-8	2.888851e-10

Note that correlations with a raw p-value above 0.05 may have been removed from the results.

Correlation Browser 2.0: Daniel Sachse, Sjur Reppe, Kåre Gautvik - 2013.

Search Options: Find correlations between...
Gene/Label/Number:	and (Empty also means "all others")
Output Options
Restrict output to	miRs, Transcription factors? (Empty: No restrictions.)
	with keyword:
	KEGG Pathway:
Limit output to	rows.
Remove	"self correlations", i.e. correlations of a variable with itself
Sort results by	positive, negative or absolute value of correlation