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Table 4 Median number of significant transcripts calls in the comparative dilution analysis (AGS versus NUGC3) before and after power-law correction

From: Finite-size effects in transcript sequencing count distribution: its power-law correction necessarily precedes downstream normalization and comparative analysis

  Original data Power-law corrected data
Mapping method AGS 12p vs NUGC3 12p AGS 12p vs NUGC3 3p AGS 3p vs NUGC3 12p AGS 3p vs NUGC3 3p AGS 12p vs NUGC3 12p AGS 12p vs NUGC3 3p AGS 3p vs NUGC3 12p AGS 3p vs NUGC3 3p
Bowtie1 42 41 39 36 57 52 52 50
Bowtie2 (global) 44 43 43 41 61 59 61 58
Novoalign 43 40 39 36 58 57 57 54
BWA 41 41 39 36 58 55 56 53
  1. The breakdown of significant transcript calls for each combination of the mapping algorithms (Bowtie1, Bowtie2(global), Novoalign and BWA) and normalization methods (DESeq, RLE, TMM, Upperquartile, CPM and Quantile) for all 4 positive comparisons (AGS-12p versus NUGC-12p, AGS-12p versus NUGC-3p, AGS-3p versus NUGC-12p and AGS-3p versus NUGC-3p) are given in the following table. The median number of significant calls for 6 normalization methods are highlighted in red for each mapping algorithm
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Biology Direct

ISSN: 1745-6150

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