5.2 Array Comparative Genomic Hybridization Methods which transcript it was extracted. If the cut site was less than 17nt from the end <strong>of</strong> the transcript, we extended the sequence with adenine stretches, rep- resenting the poly-adenine (poly-A) tail. In these cases, additional upstream tags were also extracted until one tag fully contained in the Ensembl cDNA sequence was obtained. We disregarded Ensembl transcripts not belonging to a gene <strong>of</strong> biotype "protein_coding" or "processed_transcript". Ensembl annotates genes <strong>of</strong> several other biotypes, e.g. pseudogenes and small RNAs, but those annotations are not based on full-length transcript sequences, so we would not expect to find valid virtual tags in those transcripts. For the majority <strong>of</strong> this study, we used a conservative subset <strong>of</strong> the virtual tags from SAGE Genie and Ensembl comprising 25,593 unique tags assigned to 15,103 genes (Table 5.2). Specifically, we used SAGE Genie tags extracted from to the 3’-most cut site in RefSeq or MGC cDNAs having a poly-A tail or a polyadeny- lation signal, and Ensembl tags from transcripts <strong>of</strong> type "protein_coding" or "non_coding". Any virtual tags that mapped to multiple loci by these criteria were excluded. For certain analyses, we made use <strong>of</strong> more comprehensive vir- tual tag sets. In addition, we determined unique, perfect matches for tags to the genome using Bowtie as described above. We calculated a single expression value for each gene in each cell line by summing the counts <strong>of</strong> tags assigned to the gene. 5.2 Array Comparative Genomic Hybridization We re-analysed the array comparative genomic hybridization (CGH) data de- scribed by Pollard et al [404] CGH was performed with Human Genome CGH Microarray 4x44K arrays (Agilent), using genomic DNA from each cell line hybridised in duplicate (dye swap) and normal human female DNA as ref- erence (Promega). Log2 ratios were computed from processed Cy3 and Cy5 intensities reported by the s<strong>of</strong>tware CGH Analytics (Agilent). We corrected for effects related to GC content and restriction fragment size using a modi- fied version <strong>of</strong> the waves array CGH correction algorithm [271]. Log2 ratios were adjusted by sequential loess normalization on three factors: fragment GC content, fragment size, and probe GC content. These were selected after in- vestigating dependence <strong>of</strong> log ratio on multiple factors, including GC content in windows <strong>of</strong> up to 500 kilobases centred around each probe. The Biocon- ductor package CGHnormaliter [506] was then used to correct for intensity dependence and log2 ratios scaled to be comparable between arrays using the 98
5.2 Array Comparative Genomic Hybridization Methods Table 5.2: Classification <strong>of</strong> sequenced tags in each cell line. G144ED G144 G166 G179 CB541 CB660 Sequenced tags 6,383,175 7,133,520 13,415,402 11,610,415 12,103,066 10,043,561 Filtered tags 751,698 11.78% 912,971 12.80% 378,009 2.82% 347,537 2.99% 327,597 2.71% 382,819 3.81% Adapter 594,513 9.31% 765,484 10.73% 90,407 0.67% 45,318 0.39% 39,992 0.33% 248,799 2.48% Mitochondrial 156,534 2.45% 147,245 2.06% 285,881 2.13% 302,148 2.60% 287,493 2.38% 133,935 1.33% Ribosomal RNA 651 0.01% 242 0.00% 1,721 0.01% 71 0.00% 112 0.00% 85 0.00% Tags assigned to a single locus 2,812,750 44.07% 2,640,558 37.02% 6,271,471 46.75% 5,603,364 48.26% 5,984,114 49.44% 3,708,853 36.93% Reference tags, unique 1,420,009 22.25% 1,344,879 18.85% 2,970,554 22.14% 2,805,423 24.16% 2,894,539 23.92% 1,712,143 17.05% Reference tags, best 628,707 9.85% 577,418 8.09% 1,783,685 13.30% 1,267,594 10.92% 1,485,211 12.27% 982,190 9.78% cDNA tags, unique 146,442 2.29% 142,369 2.00% 295,764 2.20% 284,990 2.45% 261,411 2.16% 171,970 1.71% 99 cDNA tags, best 34,999 0.55% 34,472 0.48% 103,632 0.77% 105,787 0.91% 81,547 0.67% 49,374 0.49% Other SAGE Genie tags, unique 345,759 5.42% 322,034 4.51% 652,449 4.86% 684,718 5.90% 749,653 6.19% 455,045 4.53% Other SAGE Genie tags, best 72,658 1.14% 60,725 0.85% 158,601 1.18% 107,955 0.93% 148,854 1.23% 84,542 0.84% Tags not mapping to known transcrip- 164,176 2.57% 158,661 2.22% 306,786 2.29% 346,897 2.99% 362,899 3.00% 253,589 2.52% tome but uniquely to genome Ambiguously mapping tags 205,626 3.22% 185,115 2.60% 608,978 4.54% 418,267 3.60% 437,887 3.62% 388,085 3.86% Reference tags 165,895 2.60% 148,512 2.08% 516,134 3.85% 337,710 2.91% 366,115 3.02% 288,253 2.87% cDNA tags 5,996 0.09% 4,464 0.06% 10,566 0.08% 6,455 0.06% 6,708 0.06% 40,908 0.41% Other SAGE Genie tags 8,581 0.13% 6,717 0.09% 25,914 0.19% 14,668 0.13% 13,553 0.11% 12,508 0.12% Tags not mapping to known transcrip- 25,154 0.39% 25,422 0.36% 56,364 0.42% 59,434 0.51% 51,511 0.43% 46,416 0.46% tome but to multiple genomic locations Unclassified tags 2,613,101 40.94% 3,394,874 47.59% 6,156,944 45.89% 5,241,247 45.14% 5,353,468 44.23% 5,563,803 55.40%
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