Previous: QTL Projection, Up: Meta Analysis
Here we want to address the following question: How many “real” QTL do the QTL detected in the different mapping experiments represent - one, two, three, four,... or as many as the number detected throughout the studies ? The meta-analysis of QTL can be viewed as a clustering procedure. To do so, MetaQTL implements tow kinds of clustering algorithm. Whatever the procedure used to perform the clustering, the QTL locations are assumed to be normally distributed around their true locations with variances which can be derived from the reported CI or r-square values. This Gaussian and unbiased approximation comes from the classical asymptotic Gaussian distribution of the maximum-likelihood estimation of the parameters.
ClustQTL implements a clustering procedure based on a Gaussian mixture model which parameter estimates are obtained by applying a EM-algorithm.
Option | Usage | Type | Explanation
|
---|---|---|---|
-q,--qtlmap | required | string | The map with the QTL to clusterize (XML format).
|
-o,--output | required | string | The output file stem.
|
-t,--tonto | optional | string | The trait ontology.
|
-k,--kmax | optional | integer | The maximal number of clusters.
|
-c,--chr | optional | string | The name of the chromosome on which to perform the meta-analysis.
|
--cimode | optional | integer | The CI computation mode.
|
--cimiss | optional | integer | The imputation mode for missing CI.
|
--emrs | optional | integer | the number of random starting points for the EM algorithm
|
--emeps | optional | double | the convergence threshold for the EM algorithm
|
The option --cimode
controls the mode of computation of the variances of the QTL. There are four modes:
--cimiss
defines how to deal with QTL for which no variance can be computed. There are two possibilities:
The output of ClustQTL is divided into 3 plain text files:
Identifier | Value
|
---|---|
CR | The name of the linkage group.
|
TR | The trait name following by the number of related QTL on the chromosome.
|
QT | A QTL with its identifier, its name, its position on the chromosome and its estimated standard deviation.
|
CL | Indicates the beginning of a clustering result. It is followed by the number of QTL involved in the clustering, the number of clusters, the log-likelihood and the complete log-likelihood of this clustering.
|
CC | The name of a model choice criterion followed by its value.
|
CP | This tag recovers four kinds of entry:
|
CR 3 TR FloweringTime 10 QT 0 Lubberstedt_1997_HT_7 106.35 7.9 QT 1 Cardinal_2001_HT_5 90.76 7.91 QT 2 qplht107 150.02 5.28 QT 3 Cardinal_2001_HT_6 51.03 7.26 QT 4 qplht106 107.46 1.3 QT 5 Groh_1998_HT_2 61.03 17.15 QT 6 Bohn_1996_HT_2 66.81 4.26 QT 7 Lubberstedt_1997_HT_6 80.67 3.04 QT 8 qplht105 75.45 4.61 QT 9 Blanc_SDflofch3 148.15 15.05 QT 10 Blanc_FXflofch3 135.27 21.68 CL 10 2 -462.46 -445.55 CC AIC 930.91 CC BIC 935.11 CP MU 88.87 148.91 CP PI 0.73 0.27 CP CI 3.82 3.76 CP Z 0 1 0 CP Z 1 1 0 CP Z 2 0 1 CP Z 3 1 0 CP Z 4 1 0 CP Z 5 1 0 CP Z 6 1 0 CP Z 7 1 0 CP Z 8 1 0 CP Z 9 0 1 CP Z 10 0.1 0.9 ... |
Chromosome Trait K Criterion Value Delta Weight 3 FT 1 AIC 1969.57 1654.71 0 3 FT 2 AIC 930.91 616.05 0 3 FT 3 AIC 445.55 130.69 0 3 FT 4 AIC 364.46 49.6 0 3 FT 5 AIC 314.86 0 0.51 3 FT 6 AIC 315.54 0.68 0.36 3 FT 7 AIC 317.92 3.06 0.11 3 FT 8 AIC 322.44 7.58 0.01 3 FT 9 AIC 326.44 11.58 0 3 FT 10 AIC 330.44 15.58 0 3 FT 30 AIC 361.77 46.92 0 3 FT 1 BIC 1970.97 1643.5 0 3 FT 2 BIC 935.11 607.64 0 3 FT 3 BIC 452.55 125.08 0 3 FT 4 BIC 374.27 46.8 0 3 FT 5 BIC 327.47 0 0.84 3 FT 6 BIC 330.95 3.48 0.15 3 FT 7 BIC 336.14 8.67 0.01 3 FT 8 BIC 343.46 15.99 0 3 FT 9 BIC 350.26 22.79 0 3 FT 10 BIC 357.06 29.59 0 3 FT 30 BIC 403.81 76.34 0 |
Criterion Chromosome Trait Model AIC 3 FT 2 AIC 10 FT 4 AIC 5 FT 4 AIC 7 FT 5 AIC 2 FT 4 AIC 9 FT 3 AIC 4 FT 3 AIC 8 FT 5 AIC 6 FT 3 AIC 1 FT 5 BIC 3 FT 2 BIC 10 FT 3 BIC 5 FT 4 BIC 7 FT 5 BIC 2 FT 4 BIC 9 FT 3 BIC 4 FT 3 BIC 8 FT 5 BIC 6 FT 3 BIC 1 FT 5 |
Another way to clusterize the observed QTL is to use standard hierarchical clustering procedures. QTLTree implements two kinds of hierarchical clustering algorithm :
Option | Usage | Type | Explanation
|
---|---|---|---|
-q,--qtlmap | required | string | The map with the QTL to clusterize (XML format).
|
-o,--output | required | string | The output file.
|
-m,--mode | optional | integer | The clustering mode (default is 2).
|
-t,--tonto | optional | string | The trait ontology.
|
--cimode | optional | integer | The variance computation mode.
|
--cimiss | optional | integer | The imputation mode for missing variances.
|
The option -m
(or --mode
) allows user to switch between the two possible clustering algorithms:
--cimode
and --cimiss
works as for QTLClust.
The output of QTLTree consists in one plain text file. The file is organized as follows:
Identifier | Value
|
---|---|
CR | The name of the linkage group.
|
TR | The name of the trait followed by the number of related QTL on the chromosome.
|
QT | A QTL involved in the clustering with its identifier, its name, its most probable position on the chromosome and its estimated standard deviation.
|
HC | The tree obtained by the clustering algorithm in Newick's format.
|
CR 10 TR FT 16 QT 0 Ribaut_1996_DPS_6 8.02 7 QT 1 Bohn_2000_DPS_12 51.68 4.87 QT 2 Poupard_2001_DPS_13 40.02 3.65 QT 3 Mechin_2001_HT_5 71 4.26 QT 4 Lubberstedt_1997_HT_20 59.14 3.65 QT 5 Groh_1998_HT_7 100.01 12.2 QT 6 qplht127 52.39 5.25 QT 7 Rebai_1997_SD_5 66.51 5.17 QT 8 Blanc_DFflofch10 61.57 2.55 QT 9 Rebai_1997_SD_25 54.5 12.46 QT 10 Rebai_1997_SD_19 62.14 10.64 QT 11 Blanc_FXflofch10 58.17 3.57 QT 12 Ribaut_1996_SD_6 6.78 10.83 QT 13 Rebai_1997_SD_33 59.96 9.73 QT 14 Rebai_1997_SD_12 49.04 14.59 QT 15 Blanc_SFflofch10 53.13 3.32 HC ((0:0.16,12:0.16):87.85,((((((1:0.24,((6:0.06,15:0.06):0.11,9:0.11):0.24):0.4,14:0.4) HC :7.43,(((4:0.04,13:0.04):0.16,11:0.16):1.11,(8:0.01,10:0.01):1.11):7.43):15.64, HC (3:2.43,7:2.43):15.64):24.56,5:24.56):40.9,2:40.9):87.85); |