Analisi dei dati di Microarray

1. Analisi dei dati di Microarray

4. Approcci di analisi Identificazione di geni differenzialmente espressi: Generazione del profilo trascrizionale di due o piu� punti sperimentali. Filtraggio dei segnali non significativi. Valutazione dell�espressione differenziale e validazione statistica. Identificazione di marcatori prognostici e diagnostici: Generazione del profilo trascrizionale di campioni normali e patologici. Filtraggio dei segnali non significativi. Selezione del piu� piccolo set di geni discriminanti per la condizione patologica. Transcriptional pathways identification: Generazione di serie temporali ed esperimenti di silenziamento genico (utilizzando organismi knock-out). Sviluppo di modelli matematici che descrivano il problema (approccio con algoritmi bayesiani).

23. The number of replicates is playing an important role in the identification of true differential expressions. Replication of microarray experiments is important as it reduces variability, and data obtained from replicated experiments can be analysed using formal statistical methods. Yang YH, Speed T. (2002). Design issues for cDNA microarray experiments. Nature Reviews. 3:579-589 Averaging replicates reduces variability. Plots of log ratios M = log2(KO/WT), averaged across replicate slides, against overall intensity A = log2v(KO � WT), which is similarly averaged, are shown. The green spots correspond to eight genes that were known to be differentially expressed between the two mRNA sources (knockout (KO) and wild-type (WT) liver). The numbers of replicate slides (n) shown are a | 1, b | 2, c | 4 and d | 8. Red arrows and elipses indicate false positives. The number of replicates is playing an important role in the identification of true differential expressions. Replication of microarray experiments is important as it reduces variability, and data obtained from replicated experiments can be analysed using formal statistical methods. Yang YH, Speed T. (2002). Design issues for cDNA microarray experiments. Nature Reviews. 3:579-589 Averaging replicates reduces variability. Plots of log ratios M = log2(KO/WT), averaged across replicate slides, against overall intensity A = log2v(KO � WT), which is similarly averaged, are shown. The green spots correspond to eight genes that were known to be differentially expressed between the two mRNA sources (knockout (KO) and wild-type (WT) liver). The numbers of replicate slides (n) shown are a | 1, b | 2, c | 4 and d | 8. Red arrows and elipses indicate false positives.