Efficient pooling designs for library screening.
We describe efficient methods for screening clone libraries, based on pooling schemes that we call "random k-sets designs." In these designs, the pools in which any clone occurs are equally likely to be any possible selection of k from the v pools. The values of k and v can be chosen to optimize desirable properties. Random k-sets designs have substantial advantages over alternative pooling schemes: they are efficient, flexible, and easy to specify, require fewer pools, and have error-correcting and error-detecting capabilities. In addition, screening can often be achieved in only one pass, thus facilitating automation. For design comparison, we assume a binomial distribution for the number of "positive" clones, with parameters n, the number of clones, and c, the coverage. We propose the expected number of resolved positive clones--clones that are definitely positive based upon the pool assays--as a criterion for the efficiency of a pooling design. We determine the value of k that is optimal, with respect to this criterion, as a function of v, n, and c. We also describe superior k-sets designs called k-sets packing designs. As an illustration, we discuss a robotically implemented design for a 2.5-fold-coverage, human chromosome 16 YAC library of n = 1298 clones. We also estimate the probability that each clone is positive, given the pool-assay data and a model for experimental errors.
Bruno
W J
WJ
Center for Human Genome Studies, Life Sciences Division, Los Alamos National Laboratory, New Mexico 87545, USA.
Knill
E
E
Balding
D J
DJ
Bruce
D C
DC
Doggett
N A
NA
Sawhill
W W
WW
Stallings
R L
RL
Whittaker
C C
CC
Torney
D C
DC
D016010:Binomial Distribution; D018244:Chromosomes, Artificial, Yeast; D002885:Chromosomes, Human, Pair 16 / Q000235:genetics; D004247:DNA / Q000032:analysis*; D015698:Genomic Library; D006801:Humans; D008433:Mathematics; D008962:Models, Theoretical; D012371:Robotics / Q000379:methods; D012984:Software
D004247:DNA