Usecase ea: Difference between revisions

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==== Enrichment analysis workflow ====
{{DISPLAYTITLE:Enrichment Analyses}}
One of the standard approaches in downstream analysis of gene expression is enrichment analysis that can be useful for evaluating biological function under condition. In this use-case, two type of annotation enrichment analyses are introduced for refTSS users.


To prepare input for GWAS-LD enrichment analysis on refTSS, TSS ID lists were restored in working directory. Algorithm of GWAS-LD enrichment analysis is described in here.
----
One of the standard approaches in downstream analysis of gene expression is enrichment analysis that can be useful for evaluating biological function under condition. In this use-case, two scenarios of annotation enrichment analyses are introduced for refTSS users.  


GWAS-LD enrichment analysis examines the number of TSSs overlapping with LD blocks on the genome or a '''given TSS ID list''' provided by the user ('''e.g., significant TSS sets from differential analysis'''). Here we introduce the workflow of this method.
* ''' Gene enrichment analyses'''
: '''GO and KEGG pathway annotation enrichment analysis''' are commonly used for examination of the over-representation of gene annotations. Here we introduce the workflow of general annotation enrichment analysis using refTSSs.


<html>
* ''' GWAS-LD enrichment analysis'''
<p style="text-align: center;"><img src="https://raw.githubusercontent.com/suimye/test_github/main/uPic/%E3%82%B9%E3%82%AF%E3%83%AA%E3%83%BC%E3%83%B3%E3%82%B7%E3%83%A7%E3%83%83%E3%83%88%202023-06-05%2023.36.36.png" style="zoom:60%;"></p>
: Novel enrichment service called '''refTSS-LD''' was lunched on refTSS4. refTSS-LD provides '''GWAS-LD enrichment analysis''' using refTSS IDs.  
</html>


===== 1. Differential analysis is carried out with refTSS as the reference =====


# TSS tag counts are calculated against the refTSSv4 TSS reference using TSS sequencing data (e.g., CAGE, RAMPAGE, etc.). For instance, the `featureCounts` function in the Subread package can be useful for this process.
For checking both approaches, there is an example input file of TSS ID lists from CAGE analysis of neural crest cell differentiation experiments with iPS cells ([[Source::https://reftss.riken.jp/reftss/userfiles/gwas_ld_example_ids.230607.txt| day0_vs_day18]]).
# Normalization and statistical testing were performed by standard packages such as DESeq2 and edgeR. For example, edgeR is used to calculate statistical significance between treated and control samples.
# The IDs of TSSs showing significant expression changes are extracted from the testing results. These TSS IDs are input into the refTSS website for GWAS-LD enrichment analysis. Here is an example file of TSS ID lists from CAGE analysis of neural crest cell differentiation experiments with iPS cells ([[Source::https://reftss.riken.jp/reftss/userfiles/gwas_ld_example_ids.230607.txt| day0_vs_day18]]).


===== 2. GWAS-LD enrichment analysis =====


<html>
----
<p style="text-align: center;"><img src="https://github.com/suimye/test_github/assets/296176/15be287f-be9a-437e-b0b0-10cedceaf619" style="zoom:60%;"></p>
</html>
 
From the menu, select refTSS-LD and paste the TSS IDs into the box.
 
===== 3. Interpreting the results of the enrichment analysis =====


<html>
<html>
<p style="text-align: center;"><img src="https://github.com/suimye/test_github/assets/296176/1cf69b4d-d103-4ea5-a824-443c602fb4b0" style="zoom:60%;"></p>
<p style="text-align: center;"><img src="https://raw.githubusercontent.com/suimye/test_github/main/uPic/%E3%82%B9%E3%82%AF%E3%83%AA%E3%83%BC%E3%83%B3%E3%82%B7%E3%83%A7%E3%83%83%E3%83%88%202023-06-05%2023.36.36.png" style="zoom:60%;"></p>
</html>
</html>
The table shows the results of the GWAS-LD analysis conducted using the example data. Results are sorted by order of FDR. The enriched TSS IDs are displayed in the "hits" column, allowing for inspection of which TSSs are concentrated in LD blocks grouped by traits.
----
----
 
==== 1. Gene annotation enrichment analysis ====
==== 4. Workflow of general annotation enrichment analysis ====
: Annotation enrichment analysis examines the over-representation of genes of interest with biological annotations such as GO and KEGG pathways. To apply TSS analysis using refTSS to gene annotation enrichment, '''TSS IDs must be converted to gene IDs or symbols ''' for input into annotation enrichment tools. refTSS4 has newly launched a simple web tool for converting TSS IDs to gene symbols to support refTSS users.
 
GO and KEGG pathway annotation enrichment analysis examines the over-representation of genes with biological annotations such as GO and KEGG pathways. Here we introduce the workflow of general annotation enrichment analysis using refTSS and external enrichment analysis tools.


<html>
<html>
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</html>
</html>


===== 1. General annotation enrichment analysis is carried out with refTSS as the reference =====
1.1. '''TSS expression analysis and extraction of statistically significant TSSIDs.'''
: TSS sequencing is useful method for evaluation of gene expression value using TSS tags. refTSS4 introduces how to perform differential analysis of TSS on [[Usecase2|Tutorial of TSS differential analysis ]].
<div></div>
1.2. '''ID conversion from TSSID to Official Gene symbols.'''
: Conversion of differentially expressed TSSID to [[IdConversion|ID conversion tools ]]
: <html>
<p style="text-align: center;"><img src="https://github.com/suimye/test_github/assets/296176/7d0d22ab-4622-4d9f-819d-0c0df08e42db" style="zoom:60%;"></p>
</html>
1.3. '''External enrichment tools (e.g., DAVID, Metascape, TopGO).'''
: The extracted Gene Symbols are input into external enrichment analysis tools such as '''DAVID, MetaScape'''.
<li> [https://david.ncifcrf.gov　DAVID] </li>
<li> [https://metascape.org/gp/index.html#/main/step1　Metascape] </li>
<li> [https://bioconductor.org/packages/release/bioc/html/topGO.html　TopGO (R package)] </li>
<li> [https://bioconductor.org/packages/release/bioc/html/clusterProfiler.html　ClusterProfiler (R package)] </li>
<br><br>
1.4. '''Reference'''
<li>[https://doi.org/10.1093/nar/gkac194 B.T. Sherman, M. Hao, J. Qiu, X. Jiao, M.W. Baseler, H.C. Lane, T. Imamichi and W. Chang. DAVID: a web server for functional enrichment analysis and functional annotation of gene lists (2021 update). Nucleic Acids Research. 23 March 2022.]</li>
<li>[https://doi.org/10.1038/s41467-019-09234-6 Zhou et al. Nature Commun. 2019 10(1):1523.]</li>
<li>[https://bioconductor.org/packages/release/bioc/html/topGO.html Alexa A, Rahnenfuhrer J (2024). topGO: Enrichment Analysis for Gene Ontology. R package version 2.58.0.]</li>
<li>[https://doi.org/10.1038/s41596-024-01020-z Xu S, Hu E, Cai Y, Xie Z, Luo X, Zhan L, Tang W, Wang Q, Liu B, Wang R, Xie W, Wu T, Xie L, Yu G (2024). “Using clusterProfiler to characterize multiomics data.” Nature Protocols. ISSN 1750-2799]</li>
<br><br>
----
==== 2. GWAS-LD enrichment analysis on refTSS-LD ====
: As well as the other enrichment tools, refTSS provides simple enrichment analysis service, [[GWAS-LD_enrichment|refTSS-LD]]. This service provides GWAS-LD enrichment analysis.


# TSS tag counts are calculated against the refTSSv4 TSS reference using TSS sequencing data (e.g., CAGE, RAMPAGE, etc.). The `featureCounts` function in the Subread package can be useful for this process.
: <html>
# Normalization and statistical testing were performed by standard packages such as DESeq2 and edgeR. For example, edgeR is used for statistical significance calculations between treated and control samples.
<p style="text-align: center;"><img src="https://github.com/suimye/test_github/assets/296176/15be287f-be9a-437e-b0b0-10cedceaf619" style="zoom:60%;"></p>
# The IDs of TSSs showing significant expression changes are extracted from the differential expression analysis results.
</html>
# The TSS IDs are input into the ID conversion tool on the refTSS website.
: From the menu, select refTSS-LD and paste the TSS IDs into the box.
: <html>
<p style="text-align: center;"><img src="https://github.com/suimye/test_github/assets/296176/1cf69b4d-d103-4ea5-a824-443c602fb4b0" style="zoom:60%;"></p>
</html>
: The table shows the results of the GWAS-LD analysis conducted using the example data. Results are sorted by order of FDR. The enriched TSS IDs are displayed in the "hits" column, allowing for inspection of which TSSs are concentrated in LD blocks grouped by traits.


<html>
<p style="text-align: center;"><img src="https://github.com/suimye/test_github/assets/296176/7d0d22ab-4622-4d9f-819d-0c0df08e42db" style="zoom:60%;"></p>
</html>


# The extracted Gene Symbols are input into external enrichment analysis tools such as '''DAVID, MetaScape, and ClusterProfiler'''.
----

Latest revision as of 17:06, 15 November 2024


One of the standard approaches in downstream analysis of gene expression is enrichment analysis that can be useful for evaluating biological function under condition. In this use-case, two scenarios of annotation enrichment analyses are introduced for refTSS users.

  • Gene enrichment analyses
GO and KEGG pathway annotation enrichment analysis are commonly used for examination of the over-representation of gene annotations. Here we introduce the workflow of general annotation enrichment analysis using refTSSs.
  • GWAS-LD enrichment analysis
Novel enrichment service called refTSS-LD was lunched on refTSS4. refTSS-LD provides GWAS-LD enrichment analysis using refTSS IDs.


For checking both approaches, there is an example input file of TSS ID lists from CAGE analysis of neural crest cell differentiation experiments with iPS cells (day0_vs_day18).


1. Gene annotation enrichment analysis

Annotation enrichment analysis examines the over-representation of genes of interest with biological annotations such as GO and KEGG pathways. To apply TSS analysis using refTSS to gene annotation enrichment, TSS IDs must be converted to gene IDs or symbols for input into annotation enrichment tools. refTSS4 has newly launched a simple web tool for converting TSS IDs to gene symbols to support refTSS users.

1.1. TSS expression analysis and extraction of statistically significant TSSIDs.

TSS sequencing is useful method for evaluation of gene expression value using TSS tags. refTSS4 introduces how to perform differential analysis of TSS on Tutorial of TSS differential analysis .

1.2. ID conversion from TSSID to Official Gene symbols.

Conversion of differentially expressed TSSID to ID conversion tools

1.3. External enrichment tools (e.g., DAVID, Metascape, TopGO).

The extracted Gene Symbols are input into external enrichment analysis tools such as DAVID, MetaScape.
  • DAVID
  • Metascape
  • TopGO (R package)
  • ClusterProfiler (R package)



    • 1.4. Reference

  • B.T. Sherman, M. Hao, J. Qiu, X. Jiao, M.W. Baseler, H.C. Lane, T. Imamichi and W. Chang. DAVID: a web server for functional enrichment analysis and functional annotation of gene lists (2021 update). Nucleic Acids Research. 23 March 2022.
  • Zhou et al. Nature Commun. 2019 10(1):1523.
  • Alexa A, Rahnenfuhrer J (2024). topGO: Enrichment Analysis for Gene Ontology. R package version 2.58.0.
  • Xu S, Hu E, Cai Y, Xie Z, Luo X, Zhan L, Tang W, Wang Q, Liu B, Wang R, Xie W, Wu T, Xie L, Yu G (2024). “Using clusterProfiler to characterize multiomics data.” Nature Protocols. ISSN 1750-2799



    • 2. GWAS-LD enrichment analysis on refTSS-LD

    As well as the other enrichment tools, refTSS provides simple enrichment analysis service, refTSS-LD. This service provides GWAS-LD enrichment analysis.

    From the menu, select refTSS-LD and paste the TSS IDs into the box.

    The table shows the results of the GWAS-LD analysis conducted using the example data. Results are sorted by order of FDR. The enriched TSS IDs are displayed in the "hits" column, allowing for inspection of which TSSs are concentrated in LD blocks grouped by traits.


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