Systematic lab effects, fold-change from U. Pitt.

Posterior medians and 95% CIs shown.</p

Infection frequency and 95% CI estimated separately for each aliquot by maximum likelihood (i.e., not using the mixed effects statistical model, see Methods: “Analyzing aliquots separately”).

Cryopreserved aliquots are indicated by shaded symbols, fresh aliquots by open symbols. “Index i” is used in model output, and “Cohort ID” represents the identifier used in the SCOPE/OPTIONS cohort.</p

Effect of cryopreservation, fold-change (posterior median and 95% CI).

Effect of cryopreservation, fold-change (posterior median and 95% CI).</p

Experimental and analytical design of the study.

Panel a: Three frozen aliquots were provided by each HIV+ participant to each lab; an additional fresh aliquot was provided to each lab except SR. Panel b: Experimental design at one of the four labs (U. Pitt.). Fresh panel (five batches): One aliquot from each HIV+ participant was studied fresh and was not batched with any other aliquots. Frozen panel (nine batches): Three aliquots from each participant were cryopreserved and batched together with one other aliquot. Five batches contain two aliquots from the same HIV+ participant. Two HIV+ participants are chosen to supply one aliquot to the same batch (here, participants 2 and 3). The remaining three batches contain an aliquot from one of the remaining HIV+ participants and an aliquot from the negative control. In each lab, different HIV+ participants are chosen for the mixed batch (see S1 Table for complete experimental design). Panel c: Sketch of statistical model used to estimate IUPM for each participant (vi); cryopreservation effect (βs); systematic effect for each lab (βl, set to zero for U. Pitt., which was arbitrarily chosen as reference); and random variation at the level of aliquot, batch, and lab (aij, bkl, cil, respectively). These fixed and random effects combine to determine the likelihood that a given well is positive, and the likelihood of the data equals the product of likelihoods of all wells (see Eq (3)).</p

Accuracy of assays used in the experimental study.

Each assay is measured against a consensus standard, appropriately scaled by βl for that assay. “All-negative” represents infinite error on the fold-change scale, which occurs when the maximum likelihood estimate of IUPM is zero. Median estimate and 95% credible intervals shown for 0.1, 0.2, 0.5, 1, 2, and 4 IUPM on the U. Pitt. scale. At IUPMs of 1 or more, measured values in these assays are expected to be within 1.6- to 1.9-fold of the truth.</p

Difference in accuracy between UCSD and JHU assays, assuming that the JHU assay is a gold standard (not subject to lab-based random effect).

Batch variation-free ensemble estimates of parameters were used in simulations. Median estimate and 95% credible intervals shown for 0.1, 0.2, 0.5, 1, and 2 IUPM on the U. Pitt. scale. All values plotted are also provided in S14 and S15 Tables.</p

Simulated results of latency reduction trials, using a t-test to compare pre- and post-treatment data.

Simulated results of latency reduction trials, using a t-test to compare pre- and post-treatment data.</p

Performance of MCMC estimation using the ensemble model and prior, in simulation of multi-lab experimental design in S3 Table.

The experiment has a total of 194 million to 289 million cells from each of five participants, distributed among four labs, encompassing 474 to 569 wells per participant. Bias and absolute error represent over- or underestimation of effect sizes, as difference in log10 of fold-change. For example, typical batch effects are estimated to be 10−0.202 = 63% of the simulated truth. See Methods (“Validation by simulation: Multiple labs”) for simulation details.</p

Estimated excess variation in QVOA.

Estimated excess variation in QVOA.</p

Fixed and random effects in the model of outgrowth, Eq (2).

Fixed and random effects in the model of outgrowth, Eq (2).</p