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Sample GSM491386 Query DataSets for GSM491386
Status Public on Jun 08, 2010
Title Scerev_Sparad_F2_hybrid P6C8
Sample type genomic
 
Channel 1
Source name Scerev+Sparad_gDNA
Organism Saccharomyces cerevisiae
Characteristics reference: S.cerevisiae+S.paradoxus genomic DNA
Extracted molecule genomic DNA
Extraction protocol not provided
Label Cy3
Label protocol not provided
 
Channel 2
Source name P6C8 gDNA
Organism Saccharomyces cerevisiae
Characteristics genotype: F2
Extracted molecule genomic DNA
Extraction protocol not provided
Label Cy5
Label protocol not provided
 
 
Hybridization protocol not provided
Scan protocol Agilent
Description Image: http://smd.stanford.edu/MicroArray/gifs/2008-07/80512.gif
Data processing Agilent Feature Extraction
 
Submission date Dec 28, 2009
Last update date Jun 08, 2010
Contact name Gavin Sherlock
E-mail(s) sherlock@genome.stanford.edu
Phone 650 498 6012
Fax 650 724 3701
URL http://genetics.stanford.edu/~sherlock/
Organization name Stanford University
Department Genetics
Street address 300 Pasteur Drive
City Stanford
State/province CA
ZIP/Postal code 94305-5120
Country USA
 
Platform ID GPL9835
Series (1)
GSE19683 Speciation

Data table header descriptions
ID_REF ID_REF
AGILENT_RAW.G_MEAN_SIGNAL Mean foreground intensity Ch 1.; Type: float; Scale: linear_scale
AGILENT_RAW.G_MEDIAN_SIGNAL Median foreground intensity Ch 1.; Type: float; Scale: linear_scale
AGILENT_RAW.R_MEAN_SIGNAL Mean foreground intensity Ch 2.; Type: float; Scale: linear_scale
AGILENT_RAW.R_MEDIAN_SIGNAL Median foreground intensity Ch 2.; Type: float; Scale: linear_scale
AGILENT_RAW.G_MEAN_BG Mean background intensity Ch 1.; Type: float; Scale: linear_scale; Background
AGILENT_RAW.G_MEDIAN_BG Median background intensity Ch 1.; Type: float; Scale: linear_scale; Background
AGILENT_RAW.R_MEAN_BG Mean background intensity Ch 2.; Type: float; Scale: linear_scale; Background
AGILENT_RAW.R_MEDIAN_BG Median background intensity Ch 2.; Type: float; Scale: linear_scale; Background
AGILENT_RAW.G_NUM_PIX Total number of pixels used to compute feature statistics; ie. Total number of inlier pixels per spot, computed independently for the green channel. The number of inlier pixels are the same in both channels.; Type: integer; Scale: linear_scale
AGILENT_RAW.R_NUM_PIX Total number of pixels used to compute feature statistics; ie. Total number of inlier pixels per spot, computed independently for the red channel. The number of inlier pixels are the same in both channels.; Type: integer; Scale: linear_scale
AGILENT_RAW.G_PIX_SDEV Standard deviation of all inlier pixels per feature; this is computed independently for the green channel; Type: float; Scale: linear_scale
AGILENT_RAW.R_PIX_SDEV Standard deviation of all inlier pixels per feature; this is computed independently for the red channel; Type: float; Scale: linear_scale
AGILENT_RAW.G_BG_NUM_PIX Total number of pixels used to compute Local background statistics per spot; ie. Total number of BG inlier pixels. This number is calculated independently for the green channel.; Type: integer; Scale: linear_scale
AGILENT_RAW.R_BG_NUM_PIX Total number of pixels used to compute Local background statistics per spot; ie. Total number of BG inlier pixels. This number is calculated independently for the red channel.; Type: integer; Scale: linear_scale
AGILENT_RAW.G_BG_PIX_SDEV Standard deviation of all inlier pixels per feature; this is computed independently for the green channel; Type: float; Scale: linear_scale
AGILENT_RAW.R_BG_PIX_SDEV Standard deviation of all inlier pixels per feature; this is computed independently for the red channel; Type: float; Scale: linear_scale
AGILENT_RAW.TOP Top coordinate of "box" containing spot in gif image; Type: integer; Scale: linear_scale
AGILENT_RAW.BOT Bottom coordinate of "box" containing spot in gif image; Type: integer; Scale: linear_scale
AGILENT_RAW.LEFT Left coordinate of "box" containing spot in gif image; Type: integer; Scale: linear_scale
AGILENT_RAW.RIGHT Right coordinate of "box" containing spot in gif image; Type: integer; Scale: linear_scale
AGILENT_RAW.POSITION_X X-coordinate of spot.; Type: float; Scale: linear_scale
AGILENT_RAW.POSITION_Y Y-coordinate of spot.; Type: float; Scale: linear_scale
AGILENT_COMPUTED.BG_PIX_CORRELATION Ratio of estimated feature Background covariance in Red Green space to product of feature Standard Deviation in Red Green space. The covariance of two features measures their tendency to vary together, ie., co-vary. In this case, it is a cumulative quantitation of the tendency of pixels belonging to a particular feature's Background in Red and Green spaces to co-vary.; Type: float; Scale: linear_scale
AGILENT_COMPUTED.BG_SUB_SIG_CORRELATION Ratio of estimated background subtracted feature signal covariance in Red Green space to product of background subtracted feature Standard Deviation in Red Green space.; Type: float; Scale: linear_scale
AGILENT_COMPUTED.G_BG_SD_USED Standard deviation of background used in green channel; Type: float; Scale: linear_scale; Background
AGILENT_COMPUTED.G_BG_SUB_SIGNAL The net green signal following the subtraction of the background from the raw green mean signal; Type: float; Scale: linear_scale
AGILENT_COMPUTED.G_BG_SUB_SIG_ERROR Propagated standard error as computed on net green background subtracted signal; Type: float; Scale: linear_scale
AGILENT_COMPUTED.G_BG_USED Background value subtracted from the raw mean signal to generate the BG subtracted signal; this value is computed for the green channel. If global BG subtraction is used, the column is identical for every feature in a channel. Options: gBGSubSignal (gMeansignal - gBGUsed); Type: float; Scale: linear_scale
AGILENT_COMPUTED.R_BG_SD_USED Standard deviation of background used in red channel; Type: float; Scale: linear_scale; Background
AGILENT_COMPUTED.R_BG_SUB_SIGNAL The net green signal following the subtraction of the background from the raw red mean signal; Type: float; Scale: linear_scale
AGILENT_COMPUTED.R_BG_SUB_SIG_ERROR Propagated standard error as computed on net red background subtracted signal; Type: float; Scale: linear_scale
AGILENT_COMPUTED.R_BG_USED Background value subtracted from the raw mean signal to generate the BG subtracted signal; this value is computed for the red channel. If global BG subtraction is used, the column is identical for every feature in a channel. Options: rBGSubSignal (rMeansignal - rBGUsed); Type: float; Scale: linear_scale
AGILENT_COMPUTED.G_DYE_NORM_SIGNAL The dye normalized signal in the green channel.; Type: float; Scale: linear_scale
AGILENT_COMPUTED.R_DYE_NORM_SIGNAL The dye normalized signal in the red channel.; Type: float; Scale: linear_scale
AGILENT_COMPUTED.G_IS_GOOD_PM Feature passes gIsWellAboveBG and additionally the gPerfMatchSignal is positive and significant (t-test p value < 0.01) versus its gDelCtrlSignal; Type: float; Scale: linear_scale
AGILENT_COMPUTED.G_IS_LOW_SPECIFICITY gPerfMatchSignal fails positive and significance t-test (0.01) versus its gDelCtrlSignal; and deletion control passes gIsWellAboveBG; Type: float; Scale: linear_scale
AGILENT_COMPUTED.R_IS_GOOD_PM Feature passes rIsWellAboveBG and additionally the rPerfMatchSignal is positive and significant (t-test p value < 0.01) versus its rDelCtrlSignal; Type: float; Scale: linear_scale
AGILENT_COMPUTED.R_IS_LOW_SPECIFICITY rPerfMatchSignal fails positive and significance t-test (0.01) versus its rDelCtrlSignal; and deletion control passes rIsWellAboveBG; Type: float; Scale: linear_scale
AGILENT_COMPUTED.G_NUM_SAT_PIX Total number of saturated pixels per feature, computed for the green channel; Type: integer; Scale: linear_scale
AGILENT_COMPUTED.R_NUM_SAT_PIX Total number of saturated pixels per feature, computed for the red channel; Type: integer; Scale: linear_scale
AGILENT_COMPUTED.G_PROCESSED_SIGNAL The propagated feature signal in the green channel, used for computation of log ratio; Type: float; Scale: linear_scale
AGILENT_COMPUTED.R_PROCESSED_SIGNAL The propagated feature signal in the red channel, used for computation of log ratio; Type: float; Scale: linear_scale
AGILENT_COMPUTED.G_PVAL_FEAT_EQ_BG Log (base 10) of p-value from t-test of significance between green Mean signal and green background.; Type: float; Scale: linear_scale
AGILENT_COMPUTED.R_PVAL_FEAT_EQ_BG Log (base 10) of p-value from t-test of significance between red Mean signal and red background.; Type: float; Scale: linear_scale
VALUE log10(REDsignal/GREENsignal); Type: float; Scale: linear_scale
AGILENT_COMPUTED.LOG_RATIO_ERROR Error of the log ratio calculated according to the error model chosen.; Type: float; Scale: linear_scale
AGILENT_COMPUTED.PIX_CORRELATION Ratio of estimated feature covariance in Red Green space to product of feature Standard Deviation ion Red Green space. The covariance of two features measures their tendency to vary together, ie., co-vary. In this case, it is a cumultive quantitation of the tendency of pixels belonging to a particular feature in Red and Green spaces to co-vary.; Type: float; Scale: linear_scale
AGILENT_COMPUTED.P_VALUE_LOG_RATIO Log (base 10) of significance level of the Log Ratio computed for a feature.; Type: float; Scale: linear_scale
AGILENT_COMPUTED.DYE_NORM_CORRELATION Dye normalized red and green pixel correlation.; Type: float; Scale: linear_scale
AGILENT_COMPUTED.G_DYE_NORM_ERROR The standard error associated with the green dye normalized signal.; Type: float; Scale: linear_scale
AGILENT_COMPUTED.R_DYE_NORM_ERROR The standard error associated with the red dye normalized signal.; Type: float; Scale: linear_scale
AGILENT_COMPUTED.ERROR_MODEL Indicates the error model that the user chose for feature extraction. Options: 0 (Propagated model chosen by user or by software) | 1 (Universal error model chosen by user of software).; Type: integer; Scale: linear_scale
AGILENT_COMPUTED.G_IS_FOUND A boolean used to flag found (strong) features. The flag is applied independently to the green channel. A feature is considered found if the found spot centroid is within the bounds of the spot deviation limit with respect to corresponding nominal centroid. NOTE: Isfound was previously termed IsStrong.; Type: boolean; Scale: linear_scale
AGILENT_COMPUTED.R_IS_FOUND A boolean used to flag found (strong) features. The flag is applied independently to the red channel. A feature is considered found if the found spot centroid is within the bounds of the spot deviation limit with respect to corresponding nominal centroid. NOTE: Isfound was previously termed IsStrong.; Type: boolean; Scale: linear_scale
AGILENT_COMPUTED.G_IS_FEAT_NON_UNIF_OL Boolean flag indicating if a feature is a NonUniformity Outlier or not. A feature is non-uniform if the pixel noise of feature exceeds a threshold established for a "uniform" feature. Option 1 (Feature is a non-uniformity outlier in the green channel).; Type: boolean; Scale: linear_scale
AGILENT_COMPUTED.R_IS_FEAT_NON_UNIF_OL Boolean flag indicating if a feature is a NonUniformity Outlier or not. A feature is non-uniform if the pixel noise of feature exceeds a threshold established for a "uniform" feature. Option 1 (Feature is a non-uniformity outlier in the red channel).; Type: boolean; Scale: linear_scale
AGILENT_COMPUTED.G_IS_FEAT_POPN_OL Boolean flag indicating if a feature is a Population Outlier or not. Probes with replicate features on a microarray are examined using population statistics. A feature is a population outlier if its signal is less than a lower threshold or exceeds an upper threshold determined using the interquartile range (ie., IQR) of the population. Options: 1 (feature is a population outlier in the green channel).; Type: boolean; Scale: linear_scale
AGILENT_COMPUTED.R_IS_FEAT_POPN_OL Boolean flag indicating if a feature is a Population Outlier or not. Probes with replicate features on a microarray are examined using population statistics. A feature is a population outlier if its signal is less than a lower threshold or exceeds an upper threshold determined using the interquartile range (ie., IQR) of the population. Options: 1 (feature is a population outlier in the red channel).; Type: boolean; Scale: linear_scale
AGILENT_COMPUTED.G_IS_SATURATED Boolean flag indicating if a feature is saturated or not in the green channel. A feature is saturated IF 50% of the pixels in a feature are above the saturation threshold. Options: 1 (saturated) | 0 (not saturated); Type: boolean; Scale: linear_scale
AGILENT_COMPUTED.R_IS_SATURATED Boolean flag indicating if a feature is saturated or not in the red channel. A feature is saturated IF 50% of the pixels in a feature are above the saturation threshold. Options: 1 (saturated) | 0 (not saturated); Type: boolean; Scale: linear_scale
AGILENT_COMPUTED.R_IS_WELL_ABOVE_BG Boolean flag indicating if a feature is well above background or not. Feature passes if RIsPosAndSignif AND RBGSubSignal is greater than 2.6*RBG_SD.Boolean flag indicating if a feature is well above background or not. Feature passes if RIsPosAndSignif AND RBGSubSignal is greater than 2.6*RBG_SD.; Type: boolean; Scale: linear_scale
AGILENT_COMPUTED.G_IS_WELL_ABOVE_BG Boolean flag indicating if a feature is well above background or not. Feature passes if RIsPosAndSignif AND RBGSubSignal is greater than 2.6*RBG_SD.Boolean flag indicating if a feature is well above background or not. Feature passes if RIsPosAndSignif AND RBGSubSignal is greater than 2.6*RBG_SD.; Type: boolean; Scale: linear_scale
AGILENT_COMPUTED.G_IS_BG_NON_UNIF_OL Boolean flag indicating if a feature's Background is a NonUniformity Outlier or not. A feature is non-uniform if the pixel noise of feature exceeds a threshold established for a "uniform" feature. Option 1 (Feature's background is a non-uniformity outlier in the green channel).; Type: boolean; Scale: linear_scale
AGILENT_COMPUTED.R_IS_BG_NON_UNIF_OL Boolean flag indicating if a feature's Background is a NonUniformity Outlier or not. A feature is non-uniform if the pixel noise of feature exceeds a threshold established for a "uniform" feature. Option 1 (Feature's background is a non-uniformity outlier in the red channel).; Type: boolean; Scale: linear_scale
AGILENT_COMPUTED.G_IS_BG_POPN_OL Boolean flag indicating if a feature's Background is a Population Outlier or not. Probes with replicate features on a microarray are examined using population statistics. A feature's background is a population outlier if its signal is less than a lower threshold or exceeds an upper threshold determined using the interquartile range (ie., IQR) of the population. Options: 1 (feature Background is a population outlier in the green channel).; Type: boolean; Scale: linear_scale
AGILENT_COMPUTED.R_IS_BG_POPN_OL Boolean flag indicating if a feature's Background is a Population Outlier or not. Probes with replicate features on a microarray are examined using population statistics. A feature's background is a population outlier if its signal is less than a lower threshold or exceeds an upper threshold determined using the interquartile range (ie., IQR) of the population. Options: 1 (feature Background is a population outlier in the red channel).; Type: boolean; Scale: linear_scale
AGILENT_COMPUTED.G_IS_POS_AND_SIGNIF Boolean flag indicating if the mean signal of a feature is greater than the corresponding background and if this difference is significant. Significance is established via a 2-sided t-test against the user-settable maximum p-value (BGSub tab) Options: 1 (Feature is positive and significant above background in the green channel); Type: boolean; Scale: linear_scale
AGILENT_COMPUTED.R_IS_POS_AND_SIGNIF Boolean flag indicating if the mean signal of a feature is greater than the corresponding background and if this difference is significant. Significance is established via a 2-sided t-test against the user-settable maximum p-value (BGSub tab) Options: 1 (Feature is positive and significant above background in the red channel); Type: boolean; Scale: linear_scale
AGILENT_COMPUTED.IS_USED_BG_ADJUST Boolean flag used to flag features used for computation of global Background offset; Type: boolean; Scale: linear_scale
AGILENT_COMPUTED.IS_NORMALIZATION Boolean flag which indicates if a feaure is used to measure dye bias. Options: 1 (Feature used) | 0 (Feature not used).; Type: boolean; Scale: linear_scale

Data table
ID_REF AGILENT_RAW.G_MEAN_SIGNAL AGILENT_RAW.G_MEDIAN_SIGNAL AGILENT_RAW.R_MEAN_SIGNAL AGILENT_RAW.R_MEDIAN_SIGNAL AGILENT_RAW.G_MEAN_BG AGILENT_RAW.G_MEDIAN_BG AGILENT_RAW.R_MEAN_BG AGILENT_RAW.R_MEDIAN_BG AGILENT_RAW.G_NUM_PIX AGILENT_RAW.R_NUM_PIX AGILENT_RAW.G_PIX_SDEV AGILENT_RAW.R_PIX_SDEV AGILENT_RAW.G_BG_NUM_PIX AGILENT_RAW.R_BG_NUM_PIX AGILENT_RAW.G_BG_PIX_SDEV AGILENT_RAW.R_BG_PIX_SDEV AGILENT_RAW.TOP AGILENT_RAW.BOT AGILENT_RAW.LEFT AGILENT_RAW.RIGHT AGILENT_RAW.POSITION_X AGILENT_RAW.POSITION_Y AGILENT_COMPUTED.BG_PIX_CORRELATION AGILENT_COMPUTED.BG_SUB_SIG_CORRELATION AGILENT_COMPUTED.G_BG_SD_USED AGILENT_COMPUTED.G_BG_SUB_SIGNAL AGILENT_COMPUTED.G_BG_SUB_SIG_ERROR AGILENT_COMPUTED.G_BG_USED AGILENT_COMPUTED.R_BG_SD_USED AGILENT_COMPUTED.R_BG_SUB_SIGNAL AGILENT_COMPUTED.R_BG_SUB_SIG_ERROR AGILENT_COMPUTED.R_BG_USED AGILENT_COMPUTED.G_DYE_NORM_SIGNAL AGILENT_COMPUTED.R_DYE_NORM_SIGNAL AGILENT_COMPUTED.G_IS_GOOD_PM AGILENT_COMPUTED.G_IS_LOW_SPECIFICITY AGILENT_COMPUTED.R_IS_GOOD_PM AGILENT_COMPUTED.R_IS_LOW_SPECIFICITY AGILENT_COMPUTED.G_NUM_SAT_PIX AGILENT_COMPUTED.R_NUM_SAT_PIX AGILENT_COMPUTED.G_PROCESSED_SIGNAL AGILENT_COMPUTED.R_PROCESSED_SIGNAL AGILENT_COMPUTED.G_PVAL_FEAT_EQ_BG AGILENT_COMPUTED.R_PVAL_FEAT_EQ_BG VALUE AGILENT_COMPUTED.LOG_RATIO_ERROR AGILENT_COMPUTED.PIX_CORRELATION AGILENT_COMPUTED.P_VALUE_LOG_RATIO AGILENT_COMPUTED.DYE_NORM_CORRELATION AGILENT_COMPUTED.G_DYE_NORM_ERROR AGILENT_COMPUTED.R_DYE_NORM_ERROR AGILENT_COMPUTED.ERROR_MODEL AGILENT_COMPUTED.G_IS_FOUND AGILENT_COMPUTED.R_IS_FOUND AGILENT_COMPUTED.G_IS_FEAT_NON_UNIF_OL AGILENT_COMPUTED.R_IS_FEAT_NON_UNIF_OL AGILENT_COMPUTED.G_IS_FEAT_POPN_OL AGILENT_COMPUTED.R_IS_FEAT_POPN_OL AGILENT_COMPUTED.G_IS_SATURATED AGILENT_COMPUTED.R_IS_SATURATED AGILENT_COMPUTED.R_IS_WELL_ABOVE_BG AGILENT_COMPUTED.G_IS_WELL_ABOVE_BG AGILENT_COMPUTED.G_IS_BG_NON_UNIF_OL AGILENT_COMPUTED.R_IS_BG_NON_UNIF_OL AGILENT_COMPUTED.G_IS_BG_POPN_OL AGILENT_COMPUTED.R_IS_BG_POPN_OL AGILENT_COMPUTED.G_IS_POS_AND_SIGNIF AGILENT_COMPUTED.R_IS_POS_AND_SIGNIF AGILENT_COMPUTED.IS_USED_BG_ADJUST AGILENT_COMPUTED.IS_NORMALIZATION
1 5886.688 6014 6776.031 6769.5 265.8182 264 116.8194 115 32 32 477.3398 239.1531 792 792 40.53042 24.99429 2552 2552 350 350 350.383 2552.5 .140828 0 40.5304 -3558.42 3518.73 9445.1 24.9943 -96.0428 1147.72 6872.07 -599.344 -12.1513 null null null null 0 0 589.4635 144.4208 -2.05418392138135 -.0820462484630006 0 .8374916949 .0675 0 0 592.659 145.209 1 1 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0
2 13691.31 14103 8300.389 8332 238.9177 236 112.1398 108 36 36 1488.933 456.2246 644 644 35.74314 29.01299 2552 2552 375 375 375.887 2552.65 .126085 0 35.7431 4385.72 3545.95 9305.59 29.013 1440.41 1156.72 6859.98 738.686 181.318 null null null null 0 0 738.686 181.3179 -2.89460904968936 -2.92836465366177 -.6100191736 .6728079709 .201964 -.438209661919123 0 597.244 145.608 1 1 1 0 0 0 0 0 0 1 1 0 0 0 1 1 1 0 0
3 13560.18 14083 8372.455 8396 232.4171 230 109.0458 105 33 33 1586.458 340.1095 633 633 32.9669 29.47477 2552 2552 401 401 401.44 2552.73 .0911205 0 32.9669 4375.67 3545.83 9184.51 29.4748 1523.94 1157.79 6848.51 736.994 190.805 null null null null 0 0 736.9943 190.8048 -2.88355498090947 -3.21888613191867 -.5868749231 .6603430648 .35957 -.426964110424708 0 597.223 144.961 1 1 1 0 0 0 0 0 0 1 1 0 0 0 1 1 1 0 0
4 8985.632 9148 8305.132 8354 227.7576 227 108.5891 104 38 38 1032.627 418.1985 623 623 35.4582 33.38899 2553 2553 426 426 426.857 2553.4 .0246987 0 35.4582 -92.1701 3518.73 9077.8 33.389 1466.21 1157.05 6838.92 -15.5242 182.537 null null null null 0 0 589.4635 182.537 -.0242328342609446 -3.01665250845892 0 .7630624868 .0556954 0 0 592.659 144.048 1 1 1 0 0 0 0 0 0 1 0 0 0 0 1 0 1 0 0
5 12355.54 12473 21902.78 22345 218.0795 215 106.2798 102 37 37 1650.911 1505.351 629 629 32.51604 33.72039 2553 2553 451 451 451.68 2553.25 .144084 0 32.516 3376.21 3534.89 8979.33 33.7204 15065.3 1893.91 6837.48 568.655 1864.89 null null null null 0 0 589.4635 1864.893 -1.88812949647267 -130.74666926529 .5001969925 .2509459741 .386176 -1.33503345366725 0 595.38 234.442 1 1 1 0 0 0 0 0 0 1 0 0 0 0 1 0 1 0 0
6 9603.27 9873 18840.86 18994 219.6567 218 104.1301 99.5 37 37 1270.851 1102.527 638 638 30.93229 31.45284 2553 2553 477 477 477.195 2553.52 .158463 0 30.9323 716.572 3519.45 8886.7 31.4528 12005.8 1660.92 6835.1 120.692 1477.07 null null null null 0 0 589.4635 1477.067 -.224232317077051 -99.1666424879906 .398943383 .2818180498 .46369 -.804402430027428 0 592.781 204.342 1 1 1 0 0 0 0 0 0 1 0 0 0 0 1 0 1 0 0
7 7060.029 7194 8388.4 8408 213.5216 211 106.9984 101 35 35 809.0368 350.7789 625 625 30.15335 36.56043 2554 2554 502 502 502.438 2554.47 .152489 0 30.1533 -1737.74 3518.73 8797.77 36.5604 1557.24 1158.24 6831.16 -292.687 190.375 null null null null 0 0 589.4635 190.3747 -.699519734633394 -3.33847788747772 0 .7494383368 -.0162946 0 0 592.659 141.596 1 1 1 0 0 0 0 0 0 1 0 0 0 0 1 0 1 0 0
8 10417 10985 17370.69 17485 214.7592 213 104.9777 100 39 39 1392.194 847.8368 627 627 31.17083 35.87095 2554 2554 528 528 528.235 2554.19 .0962967 0 31.1708 1693.56 3522.8 8723.44 35.8709 10544 1558.53 6826.68 285.246 1280.6 null null null null 0 0 589.4635 1280.6 -.674892962660311 -83.4144535480934 .3369567266 .3036428928 .502577 -.573289767230046 0 593.345 189.288 1 1 1 0 0 0 0 0 0 1 0 0 0 0 1 0 1 0 0
9 7986.487 8243 19332.13 19226 214.0143 211 101.9095 99 39 39 1028.037 1041.545 630 630 30.40325 30.31561 2554 2554 553 553 553.449 2554.03 .0738977 0 30.4032 -666.111 3518.73 8652.6 30.3156 12505.6 1697.4 6826.55 -112.193 1508.88 null null null null 0 0 589.4635 1508.879 -.205647212169525 -104.47235978959 .4081976536 .2783931627 .668492 -.845951748483236 0 592.659 204.802 1 1 1 0 0 0 0 0 0 1 0 0 0 0 1 0 1 0 0
10 7730 8000 17960.32 17921 213.7429 211 104.71 100 38 38 959.9882 917.2532 638 638 30.72826 34.59806 2554 2554 578 578 578.921 2554.39 .146593 0 30.7283 -867.936 3518.73 8597.94 34.5981 11133.2 1598.99 6827.07 -146.186 1334.13 null null null null 0 0 589.4635 1334.132 -.282648262970382 -89.7989690391825 .3547420768 .296716958 .527137 -.634756509344615 0 592.659 191.612 1 1 1 0 0 0 0 0 0 1 0 0 0 0 1 0 1 0 0
11 9641.105 10029.5 9379.316 9481.5 219.8927 218 106.1199 100 38 38 1123.326 366.6762 634 634 29.90688 34.9697 2554 2554 604 604 604.256 2554.91 .145644 0 29.9069 1102.66 3520.45 8538.45 34.9697 2549.27 1175.69 6830.05 185.72 303.371 null null null null 0 0 589.4635 303.3711 -.38131192151297 -7.8633682028313 0 .6143225782 -.121412 0 0 592.949 139.911 1 1 1 0 0 0 0 0 0 1 0 0 0 0 1 0 1 0 0
12 14473 15284 34502.37 34785 214.104 211 105.0342 99 35 35 1954.91 3235.609 644 644 31.23054 34.85052 2554 2554 629 629 629.63 2554.63 .181868 0 31.2305 5983.31 3569.23 8489.69 34.8505 27670.3 2995.62 6832.05 1007.77 3269.94 null null null null 0 0 1007.768 3269.936 -4.91615710117106 -235.143778183093 .5111786233 .1576477515 -.0116871 -2.92638912573097 0 601.166 354.007 1 1 1 0 0 0 0 0 0 1 1 0 0 0 1 1 1 0 0
13 7185.744 7393 14371.97 14467 211.7222 211 103.581 98 39 39 892.097 589.1412 630 630 30.14497 35.04205 2555 2555 655 655 655.274 2555.14 .180916 0 30.145 -1260.25 3518.73 8446 35.042 7539.39 1373.2 6832.58 -212.264 884.551 null null null null 0 0 589.4635 884.5512 -.453198317638572 -50.9080026120153 .1762661023 .366862788 .56175 -.200043517010328 0 592.659 161.11 1 1 1 0 0 0 0 0 0 1 0 0 0 0 1 0 1 0 0
14 11807.19 12195.5 36635.39 35986 216.1994 213 103.6203 98 36 36 1563.578 2678.399 632 632 33.83546 33.70918 2555 2555 680 680 680.5 2555.23 .175617 0 33.8355 3403.79 3535.15 8403.4 33.7092 29796 3193.01 6839.37 573.3 3470.93 null null null null 0 0 589.4635 3470.926 -1.91282218823884 -249.23603246875 .7699884254 .1876037306 .389982 -4.3920297353179 0 595.425 371.952 1 1 1 0 0 0 0 0 0 1 0 0 0 0 1 0 1 0 0
15 12549.44 12789 10472.53 10581.5 213.0097 210 104.4242 101 32 32 957.3489 646.8211 620 620 33.52722 31.68217 2555 2555 705 705 705.743 2555.76 .157904 0 33.5272 4179.82 3543.46 8369.61 31.6822 3626.66 1203.66 6845.87 704.007 419.424 null null null null 0 0 704.007 419.4241 -2.67220188392174 -14.7207986209222 -.224923645 .4843688526 -.283987 -.192203458340176 0 596.825 139.203 1 1 1 0 0 0 0 0 0 1 1 0 0 0 1 1 1 0 1
16 13276.45 13485 13810.42 13796 210.0754 208 104.8026 98 38 38 1341.084 522.7241 623 623 33.7743 35.47226 2555 2555 731 731 731.256 2555.96 .216641 0 33.7743 4919.53 3552.95 8356.92 35.4723 6959.51 1342.24 6850.92 828.596 799.006 null null null null 0 0 828.5959 799.0064 -3.51199672663351 -44.8489122109279 -.01579251896 .3298101245 -.0973831 -.0169111839804417 0 598.423 154.1 1 1 1 0 0 0 0 0 0 1 1 0 0 0 1 1 1 0 1
17 8084.611 8338.5 23772.22 23668 207.2552 205 101.0925 97 36 36 971.0619 1507.703 627 627 31.2511 31.03792 2555 2555 756 756 756.558 2555.74 .183548 0 31.2511 -245.78 3518.73 8330.39 31.0379 16911.3 2043.82 6860.91 -41.3966 1927.57 null null null null 0 0 589.4635 1927.575 -.067542978306683 -148.620964753711 .5145542908 .2448733236 .565114 -1.44838012144481 0 592.659 232.957 1 1 1 0 0 0 0 0 0 1 0 0 0 0 1 0 1 0 0
18 14713.42 14676.5 22812.39 22717 215.5256 215 104.8301 100 36 36 1124.853 1249.795 624 624 31.82798 34.22089 2556 2556 782 782 782.067 2556.51 .143147 0 31.828 6405.16 3576.55 8308.26 34.2209 15940.3 1964.23 6872.06 1078.82 1803.56 null null null null 0 0 1078.82 1803.561 -5.53610999586615 -139.336995823286 .2231820107 .1977284305 .00715243 -.5866805202352 0 602.397 222.242 1 1 1 0 0 0 0 0 0 1 1 0 0 0 1 1 1 0 1
19 10716 10719.5 10064.44 10046.5 212.4032 210 102.0903 96 36 36 970.0519 477.7231 620 620 32.30702 34.38932 2556 2556 807 807 807.244 2556.7 .158211 0 32.307 2409.7 3526.97 8306.3 34.3893 3180.43 1190.97 6884.02 405.865 357.265 null null null null 0 0 589.4635 357.2647 -1.12139434091081 -11.6548753494287 0 .5702914412 -.0635568 0 0 594.047 133.785 1 1 1 0 0 0 0 0 0 1 0 0 0 0 1 0 1 0 0
20 10955.88 11175 10022.7 10139 210.2048 208.5 103.0587 97 33 33 984.1578 519.9155 630 630 31.2818 32.26881 2556 2556 832 832 832.618 2556.76 .164408 0 31.2818 2669.52 3528.84 8286.36 32.2688 3123.45 1189.46 6899.25 449.627 348.342 null null null null 0 0 589.4635 348.3416 -1.30875755685856 -11.2855729960078 0 .5769846535 -.32736 0 0 594.362 132.654 1 1 1 0 0 0 0 0 0 1 0 0 0 0 1 0 1 0 0

Total number of rows: 15744

Table truncated, full table size 6326 Kbytes.




Supplementary data files not provided
Processed data included within Sample table
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