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Microarray gene expression analysis of neutrophils from elderly septic patients.

Pellegrina DV, Severino P, Machado MC, Pinheiro da Silva F, Reis EM - Genom Data (2015)

Bottom Line: Abstract available from the publisher.

View Article: PubMed Central - PubMed

Affiliation: Programa Interunidades de Pós-Graduação em Bioinformática, Universidade de São Paulo, São Paulo, Brazil.

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After hybridization and washing steps according to the manufacturer's protocol, microarray slides were scanned using the SureScan Microarray Scanner (Agilent, USA) and images were processed using the Feature Extraction (FE) Software v.12 (Agilent, USA)... Besides the signal intensity from each fluorophore detected in each spot, the FE Software provides additional information, such as each signal's standard deviation, the background signal intensity, Cy3/Cy5 log2 ratio values and also some booleans that result from tests to evaluate the quality of the signal measured in each array element... Of those booleans, we considered the ‘Well Above Background’ (WAB) test, a t-test that compares how different is the signal detected by each probe from the local background, considering the mean pixel intensities as well as their standard deviation, and a 99% confidence interval... The WAB test returns “0” if the signal is too weak and is indistinguishable from the background and “1” if it is significantly higher from the background... For each analysis, two different approaches were used to estimate the statistical significance of differential gene expression, namely Significance Analysis of Microarrays (SAM) and RankProduct (RP), both using publicly available R packages... It is very important to note that while SAM uses means and standard deviations to compare gene expression between sample groups, RP sorts each sample's gene expression measurements and compares, for each gene, how differently they are ranked in each sample group... Fig. 1 show the distributions of genes according to p-values calculated using SAM or RP in different sample group comparisons... Each graph shows, for a given group comparison, how many genes have a p-value smaller than a certain number (Fig. 1)... Note that the black lines only touch the colored lines (meaning that one of the algorithms is strictly more permissive than the other) at very high, nonsignificant p-values... Interestingly, at significant p-values the stricter algorithm varies according to the sample group comparison (Fig. 1, RP in upper panels, SAM in lower panels)... Conceivably, each algorithm will produce a number of false positives, but since they are intrinsically different those will not be the same... With that in mind we opted to consider to the functional analysis described in our original paper only genes identified as differentially expressed with a p ≤ 0.01 in both methods.

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Related in: MedlinePlus

The number of genes identified as significantly differentially expressed (vertical axis) for a given p-value threshold (horizontal axis) according to SAM (blue line), RP (red line) or both approaches (black line) according to both. The dashed black line represents the random uniform distribution of p-values given the number of genes tested.
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f0005: The number of genes identified as significantly differentially expressed (vertical axis) for a given p-value threshold (horizontal axis) according to SAM (blue line), RP (red line) or both approaches (black line) according to both. The dashed black line represents the random uniform distribution of p-values given the number of genes tested.

Mentions: We used the normalized data to perform statistical analyses aimed to identify genes differentially expressed in septic patients and affected by aging. In our original study we performed two sets of differential gene expression analyses: one to identify genes deregulated in sepsis in young and elderly subjects compared to matched healthy controls, and a second that searched for genes deregulated in septic or healthy elderly subjects compared to matched young controls [1]. For each analysis, two different approaches were used to estimate the statistical significance of differential gene expression, namely Significance Analysis of Microarrays (SAM) [4] and RankProduct (RP) [5], both using publicly available R packages [6]. It is very important to note that while SAM uses means and standard deviations to compare gene expression between sample groups [4], RP sorts each sample's gene expression measurements and compares, for each gene, how differently they are ranked in each sample group [5]. Fig. 1 show the distributions of genes according to p-values calculated using SAM or RP in different sample group comparisons. Each graph shows, for a given group comparison, how many genes have a p-value smaller than a certain number (Fig. 1).


Microarray gene expression analysis of neutrophils from elderly septic patients.

Pellegrina DV, Severino P, Machado MC, Pinheiro da Silva F, Reis EM - Genom Data (2015)

The number of genes identified as significantly differentially expressed (vertical axis) for a given p-value threshold (horizontal axis) according to SAM (blue line), RP (red line) or both approaches (black line) according to both. The dashed black line represents the random uniform distribution of p-values given the number of genes tested.
© Copyright Policy - CC BY-NC-ND
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4664687&req=5

f0005: The number of genes identified as significantly differentially expressed (vertical axis) for a given p-value threshold (horizontal axis) according to SAM (blue line), RP (red line) or both approaches (black line) according to both. The dashed black line represents the random uniform distribution of p-values given the number of genes tested.
Mentions: We used the normalized data to perform statistical analyses aimed to identify genes differentially expressed in septic patients and affected by aging. In our original study we performed two sets of differential gene expression analyses: one to identify genes deregulated in sepsis in young and elderly subjects compared to matched healthy controls, and a second that searched for genes deregulated in septic or healthy elderly subjects compared to matched young controls [1]. For each analysis, two different approaches were used to estimate the statistical significance of differential gene expression, namely Significance Analysis of Microarrays (SAM) [4] and RankProduct (RP) [5], both using publicly available R packages [6]. It is very important to note that while SAM uses means and standard deviations to compare gene expression between sample groups [4], RP sorts each sample's gene expression measurements and compares, for each gene, how differently they are ranked in each sample group [5]. Fig. 1 show the distributions of genes according to p-values calculated using SAM or RP in different sample group comparisons. Each graph shows, for a given group comparison, how many genes have a p-value smaller than a certain number (Fig. 1).

Bottom Line: Abstract available from the publisher.

View Article: PubMed Central - PubMed

Affiliation: Programa Interunidades de Pós-Graduação em Bioinformática, Universidade de São Paulo, São Paulo, Brazil.

AUTOMATICALLY GENERATED EXCERPT
Please rate it.

After hybridization and washing steps according to the manufacturer's protocol, microarray slides were scanned using the SureScan Microarray Scanner (Agilent, USA) and images were processed using the Feature Extraction (FE) Software v.12 (Agilent, USA)... Besides the signal intensity from each fluorophore detected in each spot, the FE Software provides additional information, such as each signal's standard deviation, the background signal intensity, Cy3/Cy5 log2 ratio values and also some booleans that result from tests to evaluate the quality of the signal measured in each array element... Of those booleans, we considered the ‘Well Above Background’ (WAB) test, a t-test that compares how different is the signal detected by each probe from the local background, considering the mean pixel intensities as well as their standard deviation, and a 99% confidence interval... The WAB test returns “0” if the signal is too weak and is indistinguishable from the background and “1” if it is significantly higher from the background... For each analysis, two different approaches were used to estimate the statistical significance of differential gene expression, namely Significance Analysis of Microarrays (SAM) and RankProduct (RP), both using publicly available R packages... It is very important to note that while SAM uses means and standard deviations to compare gene expression between sample groups, RP sorts each sample's gene expression measurements and compares, for each gene, how differently they are ranked in each sample group... Fig. 1 show the distributions of genes according to p-values calculated using SAM or RP in different sample group comparisons... Each graph shows, for a given group comparison, how many genes have a p-value smaller than a certain number (Fig. 1)... Note that the black lines only touch the colored lines (meaning that one of the algorithms is strictly more permissive than the other) at very high, nonsignificant p-values... Interestingly, at significant p-values the stricter algorithm varies according to the sample group comparison (Fig. 1, RP in upper panels, SAM in lower panels)... Conceivably, each algorithm will produce a number of false positives, but since they are intrinsically different those will not be the same... With that in mind we opted to consider to the functional analysis described in our original paper only genes identified as differentially expressed with a p ≤ 0.01 in both methods.

No MeSH data available.


Related in: MedlinePlus