Seleccionar sólo algunas filas de una RGList

Question

Estoy utilizando el paquete Limma analizar algunos datos.Después de la lectura de los datos en bruto con read.maimagenes Puedo obtener un RGList objeto.R. corte y G. de corte son un valor de clase numérico y quiero que los valores por encima de ellos.He intentado algo como esto:

RG$R <- RG$R[RG$R>R.cut] 
RG$G <- RG$G[RG$G>G.cut]

Pero esto convierte a la clase de RG$R de la matriz numérica, ¿cómo podría yo mantener la matriz de la clase (no sé si la introducción de algunos valores de NA afectaría el resto de analizar).He intentado subconjunto como este:

RG.probe$R <- subset(x=RG, subset=RG$R>R.cut)

Pero volviendo un error Error: Two subscripts required

Cómo puede hacerse esto?

A un lado:Si me gustaría obtener sólo las filas que están por encima de la R. corte y G. cortar?

Posible solución: He encontrado que con ifelse Puedo hacerlo aunque debo introducir un valor para los que están en el corte, y no he encontrado la manera de comprobar si ambos canales R y G están por encima de cada corte.

RG$R<-ifelse(RG$R>R.cut, RG$R, '')
RG$G<-ifelse(RG$G>G.cut, RG$G, '')

Aunque se convierte en personaje, y por lo tanto no puedo hacer más análisis.

Los datos para hacer reproducible:

library(limma)
RG<-read.maimages(path, source='agilent')
class(RG)
[1] "RGList"
attr(,"package")
[1] "limma"
dput(head(RG$R))
structure(c(2893, 81.5, 80.5, 140208, 4512, 6272, 4934, 195, 
184.5, 164092, 11819, 10569, 1689.5, 83, 82, 68996, 2260.5, 3603, 
2470, 84, 77, 96750, 3203, 5223, 3246, 85.5, 104.5, 54773, 519.5, 
8244.5, 1807, 86.5, 88, 204574, 15693, 8939.5, 2040, 87, 95, 
131880, 7346, 9922.5, 1445, 76, 85.5, 125598, 3863, 5758.5, 2626, 
87.5, 85, 180266, 18173, 20171.5, 1811.5, 84, 87.5, 122498, 3993, 
5857, 1799, 87.5, 82, 123220, 3780, 5964, 1706, 77.5, 80, 124463, 
3390, 5070, 3787, 81.5, 88, 65874, 269, 781.5, 1476, 90, 89, 
122445, 4232, 6479, 2788, 82, 87.5, 80669, 791, 7440.5, 1503, 
81, 88, 124702, 4270, 6111, 2012.5, 93.5, 90, 215820, 4555, 3101, 
1727.5, 102, 109, 131316, 4284, 6638, 2009, 95.5, 111.5, 175474, 
12665, 17213, 1532, 87.5, 84.5, 117568, 4098, 6100, 1436, 83, 
91, 118472, 4067.5, 6114, 1651.5, 83, 82, 127308, 4150, 6277, 
2028.5, 85.5, 89, 74816, 896.5, 7697, 2698, 84, 92.5, 99431, 
1273, 9182.5, 1833.5, 100, 104, 163604, 15582, 12146, 2359, 102, 
109, 159301, 17229, 9822.5, 1857, 86, 88, 130319, 4354.5, 6266.5, 
1887, 87, 87, 133386, 11639.5, 8931, 2304.5, 86.5, 87, 91022, 
1011, 14524, 1353, 84, 88, 114282, 3935, 5944, 1487, 83, 87, 
125507, 4138, 5804, 3379, 86.5, 88, 63703.5, 331, 1167, 1778, 
87, 83.5, 123988, 4366, 6670, 1862, 94.5, 92, 134174, 4558, 6881, 
2388.5, 82, 91.5, 174744, 8570, 10677, 4374, 94, 94, 179579, 
12753, 10869, 3747.5, 115, 144.5, 133809, 3710, 5406, 5062, 93.5, 
92, 207843, 13220, 6774, 3294, 78, 82.5, 149764, 3774, 5582, 
5303, 93, 100, 93479.5, 803, 6709, 2969, 86.5, 101, 149011, 4043, 
5407, 5488, 106, 118.5, 191053, 9990.5, 12194, 4308, 89, 85, 
143087, 3926.5, 5370.5, 5168, 87, 91.5, 137415, 4028, 5671, 4649.5, 
91, 90, 147328, 4102, 5614.5, 7225, 87, 85, 179052, 15612, 16908, 
5815.5, 84, 88, 200883, 13229, 11482, 3551, 101, 125, 224012, 
20461, 16149.5, 3992, 98, 83, 134744, 3569, 5068, 4817, 97, 92, 
142087, 4203, 5678, 5436, 108, 84.5, 195104, 11299, 13246), .Dim = c(6L, 
51L), .Dimnames = list(NULL, c("US23502326_253482110017_S01_GE2_1105_Oct12_1_1", 
"US23502326_253482110017_S01_GE2_1105_Oct12_2_1",     "US23502326_253482110017_S01_GE2_1105_Oct12_2_2", 
"US23502326_253482110017_S01_GE2_1105_Oct12_2_3", "US23502326_253482110017_S01_GE2_1105_Oct12_2_4", 
"US23502326_253482110027_S01_GE2_1105_Oct12_1_1", "US23502326_253482110027_S01_GE2_1105_Oct12_1_2", 
"US23502326_253482110027_S01_GE2_1105_Oct12_1_3",     "US23502326_253482110027_S01_GE2_1105_Oct12_1_4", 
"US23502326_253482110027_S01_GE2_1105_Oct12_2_1", "US23502326_253482110027_S01_GE2_1105_Oct12_2_2", 
"US23502326_253482110027_S01_GE2_1105_Oct12_2_3", "US23502326_253482110027_S01_GE2_1105_Oct12_2_4", 
"US23502326_253482110028_S01_GE2_1105_Oct12_1_1", "US23502326_253482110028_S01_GE2_1105_Oct12_1_2", 
"US23502326_253482110028_S01_GE2_1105_Oct12_1_4", "US23502326_253482110028_S01_GE2_1105_Oct12_2_1", 
"US23502326_253482110028_S01_GE2_1105_Oct12_2_2", "US23502326_253482110028_S01_GE2_1105_Oct12_2_3", 
"US23502326_253482110029_S01_GE2_1105_Oct12_1_1", "US23502326_253482110029_S01_GE2_1105_Oct12_1_2", 
"US23502326_253482110029_S01_GE2_1105_Oct12_1_3", "US23502326_253482110029_S01_GE2_1105_Oct12_1_4", 
"US23502326_253482110029_S01_GE2_1105_Oct12_2_1", "US23502326_253482110029_S01_GE2_1105_Oct12_2_2", 
"US23502326_253482110029_S01_GE2_1105_Oct12_2_3", "US23502326_253482110029_S01_GE2_1105_Oct12_2_4", 
"US23502326_253482110030_S01_GE2_1105_Oct12_1_1", "US23502326_253482110030_S01_GE2_1105_Oct12_1_2", 
"US23502326_253482110030_S01_GE2_1105_Oct12_1_3", "US23502326_253482110030_S01_GE2_1105_Oct12_1_4", 
"US23502326_253482110030_S01_GE2_1105_Oct12_2_1", "US23502326_253482110030_S01_GE2_1105_Oct12_2_2", 
"US23502326_253482110030_S01_GE2_1105_Oct12_2_3", "US23502326_253482110030_S01_GE2_1105_Oct12_2_4", 
"US23502326_253482110031_S01_GE2_1105_Oct12_1_1",     "US23502326_253482110031_S01_GE2_1105_Oct12_1_2", 
"US23502326_253482110031_S01_GE2_1105_Oct12_1_3",     "US23502326_253482110031_S01_GE2_1105_Oct12_1_4", 
"US23502326_253482110031_S01_GE2_1105_Oct12_2_1",     "US23502326_253482110031_S01_GE2_1105_Oct12_2_2", 
"US23502326_253482110031_S01_GE2_1105_Oct12_2_3",     "US23502326_253482110031_S01_GE2_1105_Oct12_2_4", 
"US23502326_253482110049_S01_GE2_1105_Oct12_1_1", "US23502326_253482110049_S01_GE2_1105_Oct12_1_2", 
"US23502326_253482110049_S01_GE2_1105_Oct12_1_3",     "US23502326_253482110049_S01_GE2_1105_Oct12_1_4", 
"US23502326_253482110049_S01_GE2_1105_Oct12_2_1",     "US23502326_253482110049_S01_GE2_1105_Oct12_2_2", 
"US23502326_253482110049_S01_GE2_1105_Oct12_2_3",     "US23502326_253482110049_S01_GE2_1105_Oct12_2_4"
)))
dput(head(RG$G))
structure(c(2324, 58, 52, 98015, 9800, 5284, 1472, 114, 92.5, 
27879, 2296, 3272.5, 3637, 216, 204.5, 34898, 731, 5084, 3466, 
77, 74, 32543, 497, 7416, 1344, 79.5, 99, 52753, 2363, 3457, 
686, 39, 44.5, 32866, 2937, 4324, 910, 42, 40, 42361, 2780, 4072, 
1587, 83.5, 97, 79659, 7667, 10103, 754, 49.5, 44, 23664, 2962, 
4166, 1390.5, 136, 156.5, 70132.5, 7914, 4876, 1609, 99, 125, 
25923.5, 610, 5125, 1526, 198.5, 157, 94640.5, 10408, 9233, 1060, 
42, 37, 70033, 3144, 4355.5, 1465, 89, 91, 99188, 9587, 7547, 
743, 61.5, 60, 65888, 3247, 4676.5, 1931.5, 89, 84, 65967, 11226, 
7757, 873.5, 56, 66, 20126.5, 3291, 4736, 1339.5, 298, 300, 75324, 
6712, 8500, 894, 65, 86, 26341.5, 3132.5, 4647, 2372, 80, 81.5, 
73418.5, 5026, 7612, 1564, 70, 73, 77180, 7802.5, 9454, 1315, 
90, 85, 20562, 340, 5337, 868.5, 49, 55, 64712.5, 2947, 4260, 
798, 46, 48, 52505, 3380, 4663.5, 904, 69.5, 80, 33371.5, 3300, 
4997, 813, 73, 81, 29552, 2932, 4632.5, 1696.5, 187, 324, 63647, 
6407, 8571.5, 872, 39.5, 52, 24518, 3094, 4387, 752.5, 54, 52, 
48299.5, 3221, 4278, 2631, 61, 72, 27229, 513, 5019, 1256.5, 
61, 63, 74560, 11016, 9019, 942, 57, 55, 70933.5, 3526.5, 5383, 
1457.5, 162, 193.5, 86276, 8154, 12084, 1590, 213, 293, 66871, 
6580, 9535, 833.5, 57, 62.5, 36416, 3229, 4600, 2161.5, 53.5, 
42.5, 39157.5, 2952, 3977, 3481, 67, 68, 18675, 152, 536, 1977, 
57, 55.5, 32861, 2785, 3812, 4739.5, 112.5, 113.5, 104923, 6231, 
8198, 1907, 57.5, 69, 76674.5, 3219, 4244, 3879.5, 183.5, 171, 
110822, 9582, 8426, 1746, 74.5, 74, 33327, 2774, 4017, 3333, 
187, 270.5, 83696, 6616, 7080, 4737, 38, 37, 30041, 429.5, 3970, 
3347, 45, 46, 106822, 8003.5, 7137.5, 2431, 32, 35, 32985, 3121, 
4179, 2535.5, 28, 34, 36131.5, 3135, 4126, 1929, 42, 65, 47428, 
3300, 4626.5, 5371, 54.5, 43.5, 108175, 9983, 6182, 5139.5, 34, 
28, 26774, 152, 518, 2621, 48, 32, 44499, 3409, 4643), .Dim = c(6L, 
51L), .Dimnames = list(NULL, c("US23502326_253482110017_S01_GE2_1105_Oct12_1_1", 
"US23502326_253482110017_S01_GE2_1105_Oct12_2_1", "US23502326_253482110017_S01_GE2_1105_Oct12_2_2", 
"US23502326_253482110017_S01_GE2_1105_Oct12_2_3",     "US23502326_253482110017_S01_GE2_1105_Oct12_2_4", 
"US23502326_253482110027_S01_GE2_1105_Oct12_1_1", "US23502326_253482110027_S01_GE2_1105_Oct12_1_2", 
"US23502326_253482110027_S01_GE2_1105_Oct12_1_3", "US23502326_253482110027_S01_GE2_1105_Oct12_1_4", 
"US23502326_253482110027_S01_GE2_1105_Oct12_2_1", "US23502326_253482110027_S01_GE2_1105_Oct12_2_2", 
"US23502326_253482110027_S01_GE2_1105_Oct12_2_3", "US23502326_253482110027_S01_GE2_1105_Oct12_2_4", 
"US23502326_253482110028_S01_GE2_1105_Oct12_1_1", "US23502326_253482110028_S01_GE2_1105_Oct12_1_2", 
"US23502326_253482110028_S01_GE2_1105_Oct12_1_4", "US23502326_253482110028_S01_GE2_1105_Oct12_2_1", 
"US23502326_253482110028_S01_GE2_1105_Oct12_2_2", "US23502326_253482110028_S01_GE2_1105_Oct12_2_3", 
"US23502326_253482110029_S01_GE2_1105_Oct12_1_1", "US23502326_253482110029_S01_GE2_1105_Oct12_1_2", 
"US23502326_253482110029_S01_GE2_1105_Oct12_1_3", "US23502326_253482110029_S01_GE2_1105_Oct12_1_4", 
"US23502326_253482110029_S01_GE2_1105_Oct12_2_1", "US23502326_253482110029_S01_GE2_1105_Oct12_2_2", 
"US23502326_253482110029_S01_GE2_1105_Oct12_2_3", "US23502326_253482110029_S01_GE2_1105_Oct12_2_4", 
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"US23502326_253482110030_S01_GE2_1105_Oct12_2_1", "US23502326_253482110030_S01_GE2_1105_Oct12_2_2", 
"US23502326_253482110030_S01_GE2_1105_Oct12_2_3", "US23502326_253482110030_S01_GE2_1105_Oct12_2_4", 
"US23502326_253482110031_S01_GE2_1105_Oct12_1_1", "US23502326_253482110031_S01_GE2_1105_Oct12_1_2", 
"US23502326_253482110031_S01_GE2_1105_Oct12_1_3", "US23502326_253482110031_S01_GE2_1105_Oct12_1_4", 
"US23502326_253482110031_S01_GE2_1105_Oct12_2_1", "US23502326_253482110031_S01_GE2_1105_Oct12_2_2", 
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"US23502326_253482110049_S01_GE2_1105_Oct12_2_1", "US23502326_253482110049_S01_GE2_1105_Oct12_2_2", 
"US23502326_253482110049_S01_GE2_1105_Oct12_2_3", "US23502326_253482110049_S01_GE2_1105_Oct12_2_4"
)))

Desde el dput puede crear un RGList por new("RGList") Sé que es mucho datos, pero como yo había preguntó No sé cómo corta la salida.

Answer 1

La solución que finalmente me dieron está haciendo casi el mismo:

RG$G <- ifelse(RG$R>R.cut, RG$G, NA)
RG$R <- ifelse(RG$G>G.cut, RG$R, NA)

La eliminación de estos valores parece aumentar el doble Cambio de cada gen como ya ocurrió comparar el original con la RG RG con borrado de los valores como en la pregunta.