previous model. In any case, the mean square prediction errors in Table 4 are better for the GLS procedures than for the classical one. PC. BSP snr Ï = 0 Ï = 0.5 ...
Figure S9. Schematic presentation of the experimental set-up for Affymetrix. GeneChip Human Genome U219 array hybridizations. MDDC samples from four.
L L LL LLL LLL LLL LLL LLL LLL L |. LL L | L L L LLL LLL LLL LLL LL L |. 1 L L LL LLL LLL | L L L L LLL LLL LLL LLL LL. 1 L L LLL LLL LLL LLL LLL LL. 1 L L LL ...
Table S9. Summary of yeast SH3 domains analyzed by yeast two-hybrid. Screened 3-AT (MM). Yes. Yes. 1. 51 o. SH3 Domain. Abp1. Bbc1. Beml -1. Bem1-2.
Figure S9. 1. 2. 10. 100. 1000. NA b tite r. Group. Group 1. 10. 100. 1000. 0. 1000. 2000. 3000. 4000. 10. 100. 1000. IgG (d28). ELISPOT (d14). NAb titer. IF. N-.
Figure S9. Enrichment of AHR-ARNT PWM to SNPs in LD with CARDIOGRAM+C4D. GWAS lead SNPs. Compared to control PWM, HNF1A and HNF1B, ...
P1.p/P2.p. P9.p/P10.p. P2.p. 55. Yes. P4.pa/P4.pp. Head. P2.p/P3.pa. Head. P3.p became a vulval progenitor. In 6/6 anmals, both posterior CAN axons reached ...
Komura-Kawa et al. -152 spok nobo nvd spo sro. Cyp6t3 phm dib-1 dib-2 sad. INT. - 166. -72 T. TCA. C. -58. -283. GCC -269. -229 TCG CT -215. -90 T ATT GT- ...
Janvier. CX3CR1 M. yD88 +/-. Ly5.1. 0. 2. 4. 6. 8. 10. 12 mouse line. P a th o s c o re. Stecher, Chaffron, Käppeli et al. Figure S9. Development of ...
(B) Predicted folding structure of PMT1 UTR. The RNAfold ... Nucleotide positions are numbered from the UTR 5´-end as in B. UTR, no RNase. (lane 1); UTR ...
Orthologs. Within-mouse outparalogs : Mouse inparalogs. Orthologs. Within-mouse outparalogs. Mouse inparalogs. 0.85. Expression similarity based on ranks.
MT, Leone G, Tonni EP, eds. Evolución Biológica y Climática de la Región Pampeana durante los Ãltimos Cinco. Millones de Años. Un Ensayo de Correlación ...
Krützen, Richard C. Connor, Michael R. Heithaus, Robert C. Lacy and William B. Sherwin. 6. â¡ ...... parameter to population growth rateâ (de Kroon et al. 2000).
S9 Appendix. Simulation Set C (variable size). (b)
1.00
1.00
0.75
0.75
sensitivity
FPR
(a)
0.50
0.25
0.25
0.00
0.00
r he Fis
X2
GC
A
PC
C
P DA
H CM
AS eW tre
e or
1
Sc
e or
2
Sc
e or
3
r
he
Fis
Sc
(c)
X2
GC
A
PC
C
P DA
H CM
tre
AS eW
Sc
AS eW tre
Sc
e or
1
e or
2
Sc
e3
or
Sc
(d)
1.00
1.00
0.75
0.75
F1.score
PPV
0.50
0.50
0.25
0.50
0.25
0.00
0.00
er
h Fis
X2
GC
A
PC
C
P DA
H CM
tre
AS eW
Sc
e or
1 Sc
e or
2 Sc
e or
3
r he
Fis
X2
GC
A
PC
C
P DA
H
CM
e1
or
e2
or
Sc
e3
or
Sc
Performance by association test (Set C, accessory genome). Each association testing method was applied to a set of simulated datasets containing 100 individuals and 5,000 genetic loci, a size typical of gene presence-or-absence data (N = 80). Datasets were simulated with a relatively high level of recombination, R = 0.2, so that performance could be examined under conditions of frequent gain and loss of genetic elements.
(a)
(b)
0.15
1.00
sensitivity
0.75
FPR
0.10
0.05
0.50
0.25
0.00
0.00 5 12 1− 10
00 −1
75 0−
76
5
0 15
6−
12
5 17 1− 15
0 20
5
−7
6−
50
17
76
−1
00
Number of Individuals
12
5
0
12
6−
5
15
0
17
20
1−
15
17
6−
Number of Individuals
(c)
(d)
1.00
1.00
0.75
0.75
F1.score
PPV
1−
10
0.50
0.25
0.50
0.25
0.00
0.00 25 −1
0
5
−7 50
7
10 6−
1 10
0 15 6− 12
15
5 17 1−
Number of Individuals
0
17
6
0 −2
−7
50
5
−1
76
5
00
1−
10
0
12
5
15
6−
12
1−
15
0
17
20
6−
17
Number of Individuals
Performance by number of individuals (Set C). Each association testing method was applied to datasets simulated across a range of sizes, ranging the number of individuals from 50 to 200 and the number of loci from 10,000 to 100,000 (N = 80). All simulated datasets in this figure were generated with R = 0.01. Here, the interquartile mean performance of each association testing method is presented by number of individuals.
(a)
(b)
0.15
1.00
sensitivity
0.75
FPR
0.10
0.05
0.50
0.25
0.00
0.00 10
0 −3
50 0−
3
0 −7 50
0 −9 70
0 10
0
0
−3
−
90
−5
10
Number of Loci (thousands)
0
00
0
50
70
−9
−1
90
Number of Loci (thousands)
(c)
(d)
1.00
1.00
0.75
0.75
F1.score
PPV
−7
30
0.50
0.25
0.50
0.25
0.00
0.00 0 −3
10
0 −5 30
50
0 −7
0 −9 70
Number of Loci (thousands)
0
90
0 −1
−3
10
0
0
−5
30
0
50
−7
00
0
−9
70
−1
90
Number of Loci (thousands)
Performance by number of genetic loci (Set C). Each association testing method was applied to datasets simulated across a range of sizes, ranging the number of individuals from 50 to 200 and the number of loci from 10,000 to 100,000 (N = 80). All simulated datasets in this figure were generated with R = 0.01. Here, the interquartile mean performance of each association testing method is presented by number of genetic loci.
