Alternative RNA-Seq application schemas. (a) In an iterative approach, high-abundance transcripts can be identified in low-read sequencing runs, followed by iterative subtraction of the sequences dominating each sample. A profile from the combined runs promises higher measurement precision of expression levels for weakly to moderately expressed transcripts. (b) After normalization of an aliquot (top row), the strength of RNA-Seq in de novo sequence discovery can be exploited for the compilation of a comprehensive target library, against which a custom microarray can then be designed easily (Leparc et al., 2009) The remaining aliquot can then be quantitatively profiled on this optimized array (bottom row). The performance of both approaches of course depends on the quality of the subtraction or normalization step, respectively.
- Labaj PP, Leparc GG, Linggi BE, Markillie LM, Wiley HS, Kreil DP. (2011) Characterization and improvement of RNA-Seq precision in quantitative transcript expression profiling. Bioinformatics 27(13), i383-91. [abstract]