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1.
Figure 6

Figure 6. From: puma 3.0: improved uncertainty propagation methods for gene and transcript expression analysis.

The partition of qRT-PCR validated probe-sets in H133 GeneChip dataset. Gene expression estimates are calculated from multi-mgMOS. The scatter plot is drawn with expression of HBRR sample against UHRR sample. Line l1:y=−x+8 and line l2:y=−x+14 partition the 656 qRT-PCR validated probe-sets into 3 groups, labelled as “low”, “median” and “high”.

Xuejun Liu, et al. BMC Bioinformatics. 2013;14:39-39.
2.
Figure 7

Figure 7. From: puma 3.0: improved uncertainty propagation methods for gene and transcript expression analysis.

ROC curves from different methods for U133 GeneChip data. ROC curves are calculated from different gene expression estimation methods, RMA, multi-mgMOS and PM-only multi-mgMOS, combined with PPLR for “low”, “median”, “high” and “all” groups of U133 GeneChips data.

Xuejun Liu, et al. BMC Bioinformatics. 2013;14:39-39.
3.
Figure 8

Figure 8. From: puma 3.0: improved uncertainty propagation methods for gene and transcript expression analysis.

Distribution of expression difference between two conditions for U133 GeneChip data. Probe-set 220818_s_at is a low expression DE gene and probe-set 203073_at is a relatively highly expressed non-DE gene. The blue lines stand for the distributions of expression difference between two conditions calculated from multi-mgMOS and the red lines for PM-only multi-mgMOS.

Xuejun Liu, et al. BMC Bioinformatics. 2013;14:39-39.
4.
Figure 1

Figure 1. From: puma 3.0: improved uncertainty propagation methods for gene and transcript expression analysis.

Function components of the previous and new version of puma. The upper part of the figure shows the function components of the previous version of puma package and the lower part shows the new version. After the extension and improvement, the new version covers expression analysis for 3’ GeneChip and Exon array data at both gene and isoform level.

Xuejun Liu, et al. BMC Bioinformatics. 2013;14:39-39.
5.
Figure 4

Figure 4. From: puma 3.0: improved uncertainty propagation methods for gene and transcript expression analysis.

Distribution of isoform expression for gene ORAOV1. The distributions of the estimated isoform expression for the two alternatively spliced transcripts of gene ORAOV1 in the 15 cell lines are calculated from GME. The blue lines are for 11q13+ group and red lines for 11q13- group. The bold lines are the distributions of the mean expression for each group, obtained from PPLR. Expression is on the log scale.

Xuejun Liu, et al. BMC Bioinformatics. 2013;14:39-39.
6.
Figure 5

Figure 5. From: puma 3.0: improved uncertainty propagation methods for gene and transcript expression analysis.

Distribution of isoform expression for gene NEO1. The distributions of the estimated isoform expression for the two alternatively spliced transcripts of gene NEO1 in the 15 cell lines are calculated from GME. The blue lines are for 11q13+ group and red lines for 11q13- group. The bold lines are the distributions of the mean expression for each group, obtained from PPLR. Expression is on the log scale.

Xuejun Liu, et al. BMC Bioinformatics. 2013;14:39-39.
7.
Figure 3

Figure 3. From: puma 3.0: improved uncertainty propagation methods for gene and transcript expression analysis.

ROC curves from different methods for 5-replicate Exon array data. Gene expression estimation methods are combined with different finding-DE-gene methods. PLIER provides only a point estimate for gene expression and therefore is not applicable to PPLR and IPPLR. The number after PPLR indicates the sample number used in the importance sampling of the algorithm.

Xuejun Liu, et al. BMC Bioinformatics. 2013;14:39-39.
8.
Figure 2

Figure 2. From: puma 3.0: improved uncertainty propagation methods for gene and transcript expression analysis.

ROC curves from different methods for 2-replicate Exon array data. The ROC curves are obtained from the average over the 5 runs each of which randomly selects two replicates. Gene expression estimation methods RMA, PLIER and GMA, are combined with different finding-DE-gene methods, t-test, PPLR and IPPLR. PLIER provides only a point estimate for gene expression and therefore is not applicable to PPLR and IPPLR. The number after PPLR indicates the sample number used in the importance sampling of the algorithm.

Xuejun Liu, et al. BMC Bioinformatics. 2013;14:39-39.

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