Assessment of algorithms for high throughput detection of genomic copy number variation in oligonucleotide microarray data

Baross, Ágnes; Delaney, Allen D; Li, H Irene; Nayar, Tarun; Flibotte, Stephane; Qian, Hong; Chan, Susanna Y; Asano, Jennifer; Ally, Adrian; Cao, Manqiu; Birch, Patricia; Brown-John, Mabel; Fernandes, Nicole; Go, Anne; Kennedy, Giulia; Langlois, Sylvie; Eydoux, Patrice; Friedman, JM; Marra, Marco A

doi:10.1186/1471-2105-8-368

Table 3 Candidate copy number variants from empirical data

From: Assessment of algorithms for high throughput detection of genomic copy number variation in oligonucleotide microarray data

All from Xba data
Method	Reference Set	#CNVs	# Duplications	% ^a	# Deletions	% ^a	# False Positive Deletions ^b	% ^c
1-CNAG	2	3,210	1,755	55	1,455	45	970	67
2-CNAG	50	924	820	89	104	11	35	34
3-CNAG-GLAD	2	1,850	996	54	854	46	343	40
4-CNAG-GLAD	50	340	69	20	271	80	62	23
5-dChip	50	31,354	19,093	61	12,261	39	3,830	31
6-dChip	214	5,443	4,076	75	1,367	25	452	33
7-dChip-GLAD	50	1,292	66	5	1,226	95	456	37
8-dChip-GLAD	214	1,207	30	2	1,177	98	402	34
9-CNAT-GLAD	50	701	253	36	448	64	214	48
10-CNAT-GLAD	106	454	232	51	222	49	98	44
11-CNAT-GLAD	214	866	240	28	626	72	363	58
p <= 0.05 and copy number < 1.25 or > 2.75 from Xba data
Method	Reference Set	#CNVs	# Duplications	%	# Deletions	%	# False Positive Deletions	%
1-CNAG	2	444	361	81	83	19	21	25
2-CNAG	50	235	211	90	24	10	3	13
3-CNAG-GLAD	2	416	332	80	84	20	27	32
4-CNAG-GLAD	50	133	48	36	85	64	17	20
5-dChip	50	17,034	4,846	28	12,188	72	3,804	31
6-dChip	214	2,273	907	40	1,366	60	452	33
7-dChip-GLAD	50	1,042	27	3	1,015	97	313	31
8-dChip-GLAD	214	1,027	22	2	1,005	98	283	28
9-CNAT-GLAD	50	426	87	20	339	80	115	34
10-CNAT-GLAD	106	272	88	32	184	68	61	33
11-CNAT-GLAD	214	540	117	22	423	78	172	41
All from Hind data
Method	Reference Set	#CNVs	# Duplications	%	# Deletions	%	# False Positive Deletions	%
1-CNAG	2	2,127	1,161	55	966	45	638	66
2-CNAG	50	324	202	62	122	38	41	34
3-CNAG-GLAD	2	1,299	697	54	602	46	206	34
4-CNAG-GLAD	50	366	20	5	346	95	87	25
5-dChip	50	21,124	17,843	84	3,281	16	1,402	43
6-dChip	214	5,792	4,603	79	1,189	21	469	39
7-dChip-GLAD	50	790	42	5	748	95	253	34
8-dChip-GLAD	214	806	41	5	765	95	274	36
9-CNAT-GLAD	50	650	108	17	542	83	210	39
10-CNAT-GLAD	106	360	90	25	270	75	108	40
11-CNAT-GLAD	214	462	56	12	406	88	161	40
p <= 0.05 and copy number < 1.25 or > 2.75 from Hind data
Method	Reference Set	#CNVs	# Duplications	%	# Deletions	%	# False Positive Deletions	%
1-CNAG	2	377	300	80	77	20	26	34
2-CNAG	50	52	12	23	40	77	15	38
3-CNAG-GLAD	2	383	287	75	96	25	29	30
4-CNAG-GLAD	50	140	9	6	131	94	38	29
5-dChip	50	6,488	3,230	50	3,258	50	1,392	43
6-dChip	214	1,822	637	35	1,185	65	468	39
7-dChip-GLAD	50	744	23	3	721	97	238	33
8-dChip-GLAD	214	748	18	2	730	98	245	34
9-CNAT-GLAD	50	547	52	10	495	90	182	37
10-CNAT-GLAD	106	311	67	22	244	78	89	36
11-CNAT-GLAD	214	426	48	11	378	89	150	40

^aPercentage of all candidate CNVs.
^bNumbers of false positive deletions were estimated using SNP genotype data (Methods).
^cThis is the percentage of false positives among the deletions (# false positive deletions/# deletions * 100).

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ISSN: 1471-2105

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