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4 votes

Why do microarrays require a priori knowledge of the genome?

If the query genome is unknown, a microarray cannot be made for a target species. Microarrays have DNA fragments of what you want to amplify on them. Those fragments must be known. From nature: DNA ...
pascal's user avatar
  • 604
4 votes
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Why do genes, encoding the same proteins and in the same conditions, have different expression?

If I understand your question and graph correctly, your Y-axis is log(x/REF), where REF is some external standard. Your "Ref" on the x-axis you expect to be the same as REF, so that log(Ref/...
Bryan Krause's user avatar
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4 votes
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Quantifying Gene Expression

What is Protein Expression Level? This was the original title of the post, which I edited myself because I regard the answer as trivial, but the question as more substantial. To deal with the trivial ...
David's user avatar
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4 votes
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Why analyse transcriptome instead of proteome?

Q: Why not just extract the proteins… A: It’s not just a question of extracting the proteins, you would need to separate them and then isolate each of them. There is currently no practical way to do ...
David's user avatar
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3 votes

Why analyse transcriptome instead of proteome?

Why not just extract the proteins and sequence them, quantify them, analyse and draw conclusions? Because proteomics is really hard. To provide one example, there is no protein equivalent of PCR. ...
Charles E. Grant's user avatar
3 votes
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In microarray normalization, why is the normalization factor this?

$G_k^{'}$ and $R_k^{'}$ are normalized values of $G_k$ and $R_k$. Take say G as $[1,2,3,4]$ and R as $[100,150,200,400]$ as your values and you want to normalize them. This is scaling one of them ...
Kiritee Gak's user avatar
2 votes

Why do genes, encoding the same proteins and in the same conditions, have different expression?

It is entirely possible that different cell-lines express the same genes at drastically different levels. The proteinatlas provides data and analyses on differences between certain tissues or cell ...
KaPy3141's user avatar
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2 votes
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What do the intervals between groups of arrays in microarray gene expression data images mean?

The borders provide visual cues for the image analysis software to know which spot is which. The spots are also not printed all at once, but by a series of print heads, and the spaces allow for a ...
MattDMo's user avatar
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What is the most appropriate way to normalize gene expression data?

Normalization of expression data is a big topic with new methods being published regularly. When approaching something like this you generally want look at people who have done similar things to what ...
Dermot Harnett's user avatar
2 votes

Why analyse transcriptome instead of proteome?

While you are correct that 'the end output' is always protein and that functional analysis on the mRNA level can ignore things translational control, there good reasons to analyse the transcriptome: ...
Nicolai's user avatar
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2 votes
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Why are there different gene expressions that are refered to the same gene in microarray experiments results?

What you are looking at there is a microarray dataset (see the description here). Microarrays are chips that have many sequence specific probes on them and sometimes they have multiple probes for the ...
Nicolai's user avatar
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2 votes

Why do we use cRNA instead of initial extracted RNA in the microarray technique?

After clarification via the comments of the OPs question: 1) The procedure you describe is not for standard RNA microarray experiments, it for olgionucleotide microarray. This type of chip is special ...
Nicolai's user avatar
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1 vote

Why analyse transcriptome instead of proteome?

What are the compelling arguments to study the transcriptome to understand biological processes? There are compelling arguments to study the transcriptome but they ...
Michael_A's user avatar
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1 vote

Does PCR amplification affect microarray or DNA biosensor results?

Yes, it does. That is why you should include positive and negative controls and repeat the experiments multiple time to then average the results. In general, amplification by PCR is biased by ...
alec_djinn's user avatar
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1 vote

Does PCR amplification affect microarray or DNA biosensor results?

Anytime you have PCR in a protocol, yes, you might mess up the quantification. So you do as little PCR as you can, so that it stays in the linear range, preserving the different abundances of ...
swbarnes2's user avatar
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1 vote

How do I score differential activity of cellular pathways in microarray data (not enrichment)?

How do I score differential activity of cellular pathways in microarray data (not enrichment)? You would look at downstream genes, which are selective for individual pathways - or genes which have ...
tsttst's user avatar
  • 1,597
1 vote

How to determine continental ancestry group (race) with transcriptome data obtained with RNA microarray?

If you can call genomic variants from your data, depending on your coverage of the genome, you should be able to map ancestry. For example, if you have sequencing reads, you can align your reads to a ...
leekaiinthesky's user avatar
1 vote
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How can microarrays be used to quantitatively determine level of gene expression?

From the comments: MattDMo: You can compare different samples, which may have started out as different amounts of tissue, by using control genes. The numbers reported by most standard ...
1 vote

At which step should I apply a detection filter when preprocessing microarray data? (Before/After normalization, batch effects removal)

My comment above still stands; provided your detection filter doesn't rely on your data being normalized, your detection filter can exist anywhere. However, since it seems you know that you want to ...
virtualxtc's user avatar
1 vote
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Where do I find standard tissue and cell names?

It turns out that ArrayExpress itself uses various ontologies (dictionaries structured as trees) available at Ontology Lookup Service when it processes users' search queries. Experimental Factor ...
Sashko Lykhenko's user avatar
1 vote
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Is the technology "identitas v1 forensics chip" related to microarray technology?

Interesting question. The answer lies encoded in our DNA. If you take eye color for example, the genes important here are well known. The most important are OCA2, HERC2, SLC24A4 and TYR. These are ...
Chris's user avatar
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1 vote

Validation by PCR of a lowly expressed gene in microarray

If it was detectable in a microarray, the odds are very good for RT-rtPCR. If you are designing your own primers, make sure they span an exon junction, or if the gene is intronless, then span the UTR ...
akaDrHouse's user avatar
  • 1,309
1 vote

How many co-expressed genes would be expected in a tissue?

Check the beautiful publication of Daniel Ramsköld et al. 2009, which holds the numbers for generally anticipated co-expression. The specific level of co-expression, which applies to your scenario, ...
tsttst's user avatar
  • 1,597
1 vote

What is the most appropriate way to normalize gene expression data?

Generally speaking for RNA-seq data, you don't want to correct for GC content or other gene level effects (e.g. length) because you compare expression values between conditions WITHIN a gene. For this ...
fanli's user avatar
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