News from the group:
Research Exchange Fellowships - IAESTE (apply)
CAMDA 2023 - ISMB Conference Track, 26-27 July, Lyon, France (read more)
World-leading patient stratification - graph based cancer data integration (read more)
Confirming molecular mechanisms of tendon regeneration - a powerful ovine fetal model (read more)
CAMDA 2022
ISMB Conference Track,
11-12 July, Madison, USA
(read more)
NVIDIA GTC Best Poster Award
for MM Kańduła
at GTC'18
Outstanding Presentation Prize
for MM Kańduła
at CAMDA'17
Outstanding Presentation Prize
for PP Łabaj
at CAMDA'15 (photo)
Austrian Marshall Plan Foundation scholarship
for MM Kańduła
at Boston University
OeAW APART fellowship
for PP Łabaj

Sequencing Quality Control (SEQC) project,
MAQC Consortium 2011–2014 (read more)
Host–parasite interactions in biocontrol, WWTF grant 2010–2013 (read more)

Power and limitations of RNA-Seq,
FDA SEQC, Nature Biotechnology (read more)
Characterization and improvement of RNA-Seq precision,
Bioinformatics (read more)
Impact of heavy tails in microarray analysis, Bioinformatics (read more)
Novel conserved repeats in sorting signals,
FEBS Journal (read more)
Sound sensation gene,
Nature communications
(read more)
RNA interference in ageing research,
Gerontology (read more)

Characterization and improvement of RNA-Seq precision

Next generation sequencing is considered a promising novel technology also for the profiling of gene expression. We have performed a first systematic study of RNA-Seq reliability. Measurement precision determines the power of any analysis.

Comparison of measurement variation (follow link for paper reprint) Expression estimates for the majority of spliceforms were very noisy, with errors >20%. We have shown that this is a direct consequence of the random sampling of the highly skewed distribution of real gene transcript abundances, independent of the particular sequencing platform and protocol employed. Most of the measurement power is spent on a few strongly expressed transcripts, making the remainder hard to measure. Each doubling of the read depth adds <5% of reliably measured new transcripts.

By exploiting gene models already at the alignment stage, we improved the number of reliably assessed spliceforms by 50% (blue curve). Yet standard microarrays performed 20% better (black curve). We therefore recommend and discuss iterative approaches for efficient expression profiling.


Łabaj 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, i383-i391. (read more | Supplement | reprint | ISMB video )

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