2D – Plot of minimum value of measured distances between to and to genes for all cells

<p><b>Copyright information:</b></p><p>Taken from "Simultaneous localization of MLL, AF4 and ENL genes in interphase nuclei by 3D-FISH: MLL translocation revisited"</p><p>BMC Cancer 2006;6():20-20.</p><p>Published online 24 Jan 2006</p><p>PMCID:PMC1388228.</p><p>Copyright © 2006 Gué et al; licensee BioMed Central Ltd.</p> Distances are expressed in μm. Vertical and horizontal blue lines symbolize the gene proximity criterion (2 μm) below which genes could be potentially translocated. Values express the percentage of cells in which the distances reported in one axis is smaller than the distance on the other axis. Grey areas correspond to nuclei where only one of gene could be translocated

Relative position of the variants in the Colony Size assay and fluctuation of the best cut-off.

<p>(<b>A</b>) Waterfall distribution of colony sizes, according to median values (standard method). Boxplot representation results from 9 (mutants) or 36 (BRCA1 and Vector) colony size values. The red and blue colors of the boxes indicate the pathogenic and neutral mutations, respectively, according to their prior classification. Box central bar, median; box, interquartile range (50% of the distribution); whiskers, extreme values; dotted horizontal line, median of BRCA1; thick horizontal line, experimental best cut-off (see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006096#pgen.1006096.s004" target="_blank">S2 Fig</a>). The distribution of the best cut-off fluctuation, obtained after random sampling (bootstrap), of the 9 mutants and 36 BRCA1 values, is visualized by the pink, grey and light blue areas, that delimit 4%, 90% and 4.9% of the distribution, respectively, which altogether represents a total coverage of 98.9%. (<b>B</b>) Waterfall distribution according to p values (MWW method). The p value assigned to each variant is symbolized by a segment. The upside-down representation facilitates the comparison of the mutation arrangement with the one obtained in <b>A</b>. Arrows pinpoint a modification of the mutation rank depending on the method used. Framed mutations indicate identical p values (see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006096#pgen.1006096.s033" target="_blank">S4 Table</a>). Segment colors, thick horizontal line and colored areas, as in <b>A</b>.</p

Variant classification using the probability system.

<p>(<b>A</b>) Schematic of the probability system of classification. The left figure depicts a theoretical waterfall distribution of pathogenic and neutral missense mutations, as in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006096#pgen.1006096.g001" target="_blank">Fig 1B</a>. Horizontal black line, experimental best cut-off. (1) Variant classification according to the experimental best cut-off (method used in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006096#pgen.1006096.t001" target="_blank">Table 1</a>). (2) Distribution of the best cut-off generated by bootstrap analysis from the experimental data. (3) Cumulative distribution function (CDF) derived from the distribution of the best cut-off. This CDF provides a probabilistic classification of the variants, depending on their positions in the CDF. (<b>B</b>) Classification of the <i>BRCA1</i> variants assessed in four functional assays. Colored background in the table indicates the five-class nomenclature, as in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006096#pgen.1006096.s030" target="_blank">S1 Table</a>. Names in red and blue indicate the pathogenic and neutral mutations, respectively, according to their prior classification. The sensitivity, specificity and accuracy computation are detailed in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006096#pgen.1006096.s035" target="_blank">S6 Table</a>.</p

Experimental sensitivity, specificity and accuracy of functional assays and siRNA screening using the experimental best cut-off.

<p>Experimental sensitivity, specificity and accuracy of functional assays and siRNA screening using the experimental best cut-off.</p

High throughput siRNA screening and fluctuation of the best cut-off.

<p>An average of 150 human prostate tumoral cells were plated, treated with siRNAs targeting the indicated gene and grown for 72 hours before cell counting. The WT reference (No siRNA), the positive control of cell growth inhibition (siKIF11), the two negative controls of cell growth inhibition (siGOLGA2 and siGL2) and 8 among 406 siRNA targeted genes are shown. The complete analysis of the 406 targeted genes is available using the ProClass toolbox and the included siRNA full.txt file, as explained at the end of the README.doc file. (<b>A</b>) Waterfall distribution of cell growth after siRNA treatment, according to median values (standard method). As in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006096#pgen.1006096.g001" target="_blank">Fig 1A</a>, except that boxplot representation results from 12 (siRNA) or 1,140 (No siRNA) values. (<b>B</b>) Waterfall distribution according to p values (MWW method), as in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006096#pgen.1006096.g001" target="_blank">Fig 1B</a>. (<b>C</b>) Classification of the siRNA targeted genes, as in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006096#pgen.1006096.g002" target="_blank">Fig 2B</a>, except that probabilities are related to cell growth inhibition, with the corresponding five-class nomenclature: "no inhibition" (blue, class1), "likely no inhibition" (light blue, class2), "unclear inhibition" (grey, class3), "likely inhibition" (light red, class4) and "inhibition" (red, class5).</p