SAGE |
Direct, quantitative method
Genome knowledge not required
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Low-throughput, time consuming
Same tag on multiple gene
Sequencing error, quantitation bias
Low abundance transcript missed
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DNA microarray |
High-throughput, quantitativemethod
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Knowledge of sequences required
Rare transcripts missed
Labeling and hybridization biases
Identify differentially expressedgenes only.
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Antibody and bead arrays |
Sensitive and specific method
Low abundance transcriptdetected
Reproducible
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Expensive
Availability of specific antibody
Non-specific binding
Fast denaturation of proteins
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Mass spectrometry 2-DE DIGE ICAT iTRAQ SILAC SELDI-TOF |
High resolving power
Low abundance transcript detected only with ICAT, iTRAQand SILAC
Good sequence coverage
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Rare transcripts not detected with2-DE and DIGE
Limited reproducibility with 2-DE andDIGE
ICAT only applicable to cysteinecontaining proteins
Limited dynamic range
SILAC not applicable to clinicalproteins in vivo
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RNA sequencing |
Genome knowledge not required
Non-model organisms can beused
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Large amount of data, storage
Bioinformatics challenge
Only structural/sequence information
Rare transcripts missed
Strand biases
Amplification selection andhybridization artifacts
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Yeast Secretion Trap (YST) |
Functional method
Sequence information alsoobtained
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Mammalian proteins not working inyeast
Low abundance proteins missed
Proteins lacking signal peptidemissed
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Computation algorithms |
Predict secretory proteins
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Not based on experimental data
mRNA levels may not correlate withprotein levels
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