The present work details a novel comprehensive MLPA platform for mapping and assessing the significance of chromosomal abnormalities in CLL. MLPA can provide detailed multiplex profiles of chromosomal aberrations in tumor samples in a relatively short period of time. MLPA data analysis and interpretation are critical for calling real amplification or Homatropine Bromide deletion events in each chromosome region. The reference range is generated by randomly selecting a training subset of 50 healthy individuals, and produces consistent normal ratios for the determination of genomic imbalance. We further reduced probe-to-probe and sample-to-sample variations by segmenting the 13 internal reference probes. This process correlates 27 diagnostic probes across all 50 normals, assigning the arithmetic mean and SD of the normalized ratios for each individual probe to produce highest accuracy in individual event calls. A large amount of information is encoded by original probe ratio data, and the reference range is thus established to reduce that information content to a minimal set of discrete gains, losses, or neutral copy numbers. Observation of variation within the control sample pool has allowed us to evaluate performance of the MLPA method, and optimize application of the technique in patients with CLL. Each chromosomal alteration presents different analytical challenges, not only in dynamic range, but also in their noise characteristics, which is often overlooked. For example, there are challenges unique to allelic loss in CLL. First, deletion is Naringin dihydrochalcone restricted in its size, and second, only two copies of a locus can be lost. This is different from amplification. The lacking of real magnitude and interference from normal DNA in the sample, making it difficult to make a deletion call, and this is further exacerbated for single-copy events at the margins of signal and noise. The limit of detection of our improved CLL MLPA assay for calling an allelic loss is approximately 20% of that leukemia clone circulating in the bloodstream. Although the sensitivity is somewhat lower than the sensitivity obtained with interphase FISH, such detection level is sufficient for most untreated CLL patients at diagnosis. On the other hand, absence of an allelic copy is readily detected while gains in copy number are more problematic to confirm by FISH, especially if the distance between the probes is small. This is a key difference between the methods, with MLPA having the potential to more accurately identify and quantify copy number gains. To adapt to the diversity of variation among individual probes, samples and alterations, we developed and validated a multicomponent scoring scheme for the detection of copy-number changes on a large repository of suspected CLL samples. MLPA produced strong concordance with the gold standard, FISH, without pre-enrichment of malignant B-cells, further enhancing its clinical utility. Fourty-nine abnormalities identified by MLPA were previously reported deletions and trisomy. Six abnormalities were not covered by a standard FISH probe panel. Our automated CLL MLPA data processing, analysis and interpretation strategy has significant clinical advantages, especially when handling large MLPA data sets, when samples are of different quality, and when interpretation of MLPA electropherograms is too complex. Additionally, for tests that could be applied in the diagnostic setting, turnaround time is a critical factor. With MLPA, the total process-to-report time, including data analysis, is 2�C3 days compared to 7�C10 day for FISH. MLPA is also cheaper and less labor intensive compared with FISH.