search for: control2

...o normalization by the median of some control genes for the example below? Many Many Thanks in advance This strategy selects a subset of genes (called ?control genes?) and makes the median of their data distribution similar across arrays. ??? ??? id1??? id2??? id3 control1??? 0.8??? 0.7??? 0.6 control2??? 0.6??? 0.2??? 0.4 probe1??? ??? 0.3??? 0.2??? 0.5 probe2??? ??? 0.4??? 0.9??? 0.7 probe3??? ??? 0.6??? 0.7??? 0.4

...? Any help would be greatly appreciated. Isaac A representation of the experiments follows: Experiment 1 Control1 Treat1 Treat2 Blk1 s1 s2 s3 Blk2 s4 s5 s6 Blk3 s7 s8 s9 Experiment 2 Control2 Treat3 Treat4 Blk1 s1a s2a s3a Blk2 s4a s5a s6a Blk3 s7a s8a s9a Control1 and Control2 I are the same control cell line. I would like to compare Treat1 to Treat3 and Treat 4 and also I would like to compare...

Here is my model with interaction terms and control variables (I changed variables names for easy read): reg1 <- lm(y ~ x1*x2*x3 +control1 + control2 + control3) x1 ranges from 0 to 6; x2 from 0 to 5; and x3 from 0 to 4. All three are discrete ordinal variables; but I will treat them as continuous variables. (a) How can I see the predicted values of y for each of these scenarios (210 scenarios I guess)? (b) How can I see the predicted value...

...in unless -force-vector-width=<> is specified. Let me know if I am missing something. -Thx struct nodeTy { unsigned int c1; unsigned int c2; unsigned int state; }; struct quantum_reg { struct nodeTy node[32]; unsigned int size; }; void quantum_toffoli(int control1, int control2, int target, struct quantum_reg *reg, int n) { int i; int N = reg->size; for(i=0; i < N; i++) { if(reg->node[i].state & ((unsigned int)1 << control1)) if(reg->node[i].state & ((unsigned int)1 << control2)) r...

Dear list, Hello to everybody, I´m interested in finding a package for statistical analysis of binary data, I have a matrix with the following structure: Case1 Case2 Case 3 ....... CaseX Control1 Control2 Control3 ....... ControlY Pep1 1 0 1 1 0 0 0 1 Pep2 1 1 1 1 1 0 0 1 Pep3 0 1 1 1 1 0 0 1 ... Pepz 1 1 1 1 1 0 0 1 I would like to know some R package to calculte similarity matrix or to make some statistical diferences between cases and controls Any help it would be very appreciated BW...

I have data set up like the following: control1 <- sample(1:75, 3947398, replace=TRUE) control2 <- sample(1:75, 28793, replace=TRUE) control3 <- sample(1:100, 392733, replace=TRUE) control4 <- sample(1:75, 858383, replace=TRUE) patient1 <- sample(1:100, 28048, replace=TRUE) patient2 <- sample(1:50, 80400, replace=TRUE) patient3 <- sample(1:100, 48239, replace=TRUE) control &...

...unsigned int c1; > > unsigned int c2; > > unsigned int state; > > }; > > > > struct quantum_reg > > { > > struct nodeTy node[32]; > > unsigned int size; > > }; > > > > void > > quantum_toffoli(int control1, int control2, int target, struct quantum_reg > *reg, int n) > > { > > int i; > > > > int N = reg->size; > > for(i=0; i < N; i++) > > { > > if(reg->node[i].state & ((unsigned int)1 << control1)) > > if...

...unsigned int c1; > > unsigned int c2; > > unsigned int state; > > }; > > > > struct quantum_reg > > { > > struct nodeTy node[32]; > > unsigned int size; > > }; > > > > void > > quantum_toffoli(int control1, int control2, int target, struct quantum_reg > *reg, int n) > > { > > int i; > > > > int N = reg->size; > > for(i=0; i < N; i++) > > { > > if(reg->node[i].state & ((unsigned int)1 << control1)) > > if...

...in unless -force-vector-width=<> is specified. Let me know if I am missing something. -Thx struct nodeTy { unsigned int c1; unsigned int c2; unsigned int state; }; struct quantum_reg { struct nodeTy node[32]; unsigned int size; }; void quantum_toffoli(int control1, int control2, int target, struct quantum_reg *reg, int n) { int i; int N = reg->size; for(i=0; i < N; i++) { if(reg->node[i].state & ((unsigned int)1 << control1)) if(reg->node[i].state & ((unsigned int)1 << control2)) r...

...e; >> >> }; >> >> >> >> struct quantum_reg >> >> { >> >> struct nodeTy node[32]; >> >> unsigned int size; >> >> }; >> >> >> >> void >> >> quantum_toffoli(int control1, int control2, int target, struct >> quantum_reg *reg, int n) >> >> { >> >> int i; >> >> >> >> int N = reg->size; >> >> for(i=0; i < N; i++) >> >> { >> >> if(reg->node[i].state & ((...

...in unless -force-vector-width=<> is specified. Let me know if I am missing something. -Thx struct nodeTy { unsigned int c1; unsigned int c2; unsigned int state; }; struct quantum_reg { struct nodeTy node[32]; unsigned int size; }; void quantum_toffoli(int control1, int control2, int target, struct quantum_reg *reg, int n) { int i; int N = reg->size; for(i=0; i < N; i++) { if(reg->node[i].state & ((unsigned int)1 << control1)) if(reg->node[i].state & ((unsigned int)1 << control2)) r...

Hi Michael, Thanks for testing this on your benchmarks and target. I think the results will help guide the direction we go. I tested the feature with spec2k/2k6 on AArch64/Kryo and saw minor performance swings, aside from a large (30%) improvement in spec2k6/libquantum. The primary loop in that benchmark has a conditional store, so I expected it to benefit. Regarding the cost model, I think the

...sn't have effect. Playing with glusterfs options too. What I can do with performance? My volumes: Volume Name: nginx Type: Replicate Volume ID: e3306431-e01d-41f8-8b2d-86a61837b0b2 Status: Started Number of Bricks: 1 x 2 = 2 Transport-type: tcp Bricks: Brick1: control1:/storage/nginx Brick2: control2:/storage/nginx Volume Name: instances Type: Distributed-Replicate Volume ID: d32363fc-4b53-433c-87b7-ad51acfa4125 Status: Started Number of Bricks: 2 x 2 = 4 Transport-type: tcp Bricks: Brick1: control1:/storage/instances Brick2: control2:/storage/instances Brick3: compute1:/storage/instances Bric...