Update UseCases.rst

docs/UseCases.rst

@@ -28,7 +28,7 @@ Do you wish to search for Regulatory Elements (REMs) related to a specific gene?
   :alt: Cell type/tissue selection
 
 
-5. The result page shows the information based on your query settings. All the REMs associated to your queried genes are listed with their location, their *Predicted function*, the *Model score*, the REM cluster they are belonging to and their activity in the cell types you selected. The *Model score* indicates how important a REM is for its associated gene over all cell types. The higher the value, the more important the REM is. The next column *Cluster of REMs (CREM) ID* contains the ID of the cluster this REM is contained in. A cluster of REMs consists of all the REMs that overlap by at least 1 bp. Click on a CREM ID to get to a table with all REMs of this CREM. We provide a more detailed description of CREMs `here <https://epiregiodb.readthedocs.io/en/latest/Description.html#cluster-of-regulatory-elements>`_. If you selected cell types in your query, the *Cell type score* and the *Cell type activity* of the REMs in these cell types will be shown as average over all the samples n in the database (for each cell type separately, not averaged over all cell types). The *Cell type score* is the absolute product of the regression coefficient and the DNase activity, indicating how important a REM is in this cell type. The higher the value, the higher the REMs expected contribution to its gene's expression in this cell type. *Cell type activity* is the DNase signal alone, indicating the chromatin accessibility in the REM region. If you need some more information on the genes themselves, click on the *Gene ID* to get to the respective Ensembl web page. By clicking on the *Gene symbol* you will receive a table with all REMs that are associated to the clicked gene. To see the REM region in the `UCSC Genome Browser <https://genome.ucsc.edu/>`_ click on the chromosome entry. Another option is to use the 'Functional enrichment analysis' button to perform an analysis of all genes in the table with `g:Profiler <https://biit.cs.ut.ee/gprofiler/gost>`_ on default settings. You can export the table as xls- or csv-file. The downloaded file's name is adapted to your query and contains the date as well as the current version of the website. 
+5. The result page shows the information based on your query settings. All the REMs associated to your queried genes are listed with their location, their *Predicted function*, the *Model score*, the REM cluster they are belonging to and their activity in the cell types you selected. The *Model score* indicates how important a REM is for its associated gene over all cell types. The higher the value, the more important the REM is. The next column *Cluster of REMs (CREM) ID* contains the ID of the cluster this REM is contained in. A cluster of REMs consists of all the REMs that are direct neighbours or that overlap with each other. Click on a CREM ID to get to a table with all REMs of this CREM. We provide a more detailed description of CREMs `here <https://epiregiodb.readthedocs.io/en/latest/Description.html#cluster-of-regulatory-elements>`_. If you selected cell types in your query, the *Cell type score* and the *Cell type DNase signal* of the REMs in these cell types will be shown as average over all the samples n in the database (for each cell type separately, not averaged over all cell types). The *Cell type score* is the absolute product of the regression coefficient and the DNase activity, indicating how important a REM is in this cell type. The higher the value, the higher the REMs expected contribution to its gene's expression in this cell type. *Cell type Dnase signal* is the DNase signal alone, indicating the chromatin accessibility in the REM region. If you need some more information on the genes themselves, click on the *Gene ID* to get to the respective Ensembl web page. By clicking on the *Gene symbol* you will receive a table with all REMs that are associated to the clicked gene. To see the REM region in the `UCSC Genome Browser <https://genome.ucsc.edu/>`_ click on the chromosome entry. Another option is to use the 'Functional enrichment analysis' button to perform an analysis of all genes in the table with `g:Profiler <https://biit.cs.ut.ee/gprofiler/gost>`_ on default settings. You can export the table as xls- or csv-file. The downloaded file's name is adapted to your query and contains the date as well as the current version of the website. 
 
 .. image:: ./images/0804GeneQueryOutput.png
   :alt: Gene Query output
@@ -192,15 +192,15 @@ STITCHIT identifies REMs by interpreting differential gene expression, meaning t
 
 Model score
 ~~~~~~~
-The *Model score* is the absolute binary logarithm of the p-value for the association between a REM and its target gene. It serves as an indicator on how important a REM is for the expression prediction of its target gene. The higher the score, the more impact the REM is supposed to have. This value is not cell type specific as it is calculated over all cell types. It allows for a comparison in between the REMs but not in between cell types. For a cell type-specific comparison, have a look at the *Cell type score*.
+The *Model score* is the normalized absolute binary logarithm of the p-value for the association between a REM and its target gene. It serves as an indicator on how important a REM is for the expression prediction of its target gene. The closer the score is to 1, the more impact the REM is supposed to have. This value is not cell type specific as it is calculated over all cell types. It allows for a comparison in between the REMs but not in between cell types. For a cell type-specific comparison, have a look at the *Cell type score*.
 
 Cluster of REMs (CREM) ID
 ~~~~~~~
-As STITCHIT determine REMs for each gene seperately and not the other way around, the identified regions can overlap. A *REM cluster* is a region of neighbouring REMs that overlap by at least one base pair (bp). There have to be a minimum of two overlapping REMs to be called a CREM. Each *REM cluster* is assigned to a unique *CREM ID*. We start counting from CREM0000001 ascending. By clicking on the *Cluster of REMs (CREM) ID* you get forwareded to a table with all REMs inside of this cluster. We show a schema of a CREM `here <https://epiregiodb.readthedocs.io/en/latest/Description.html#cluster-of-regulatory-elements>`_.
+As STITCHIT determine REMs for each gene seperately and not the other way around, the identified regions can overlap. A *REM cluster* is a region of neighbouring REMs that are directly adjacent or that overlap with each other. There has to be a minimum of two neighbouring REMs to be called a CREM. Each *REM cluster* is assigned to a unique *CREM ID*. We start counting from CREM0000001 ascending. By clicking on the *Cluster of REMs (CREM) ID* you get forwareded to a table with all REMs inside of this cluster. We show a schema of a CREM `here <https://epiregiodb.readthedocs.io/en/latest/Description.html#cluster-of-regulatory-elements>`_.
 
 Number of REMs per CREM
 ~~~~~~~
-Shows how many REMs are contained in the CREM to which the REM belongs to. If the row is empty, then the REM does not have any overlapping other REM and therefore is not considered as a cluster. 
+Shows how many REMs are contained in the CREM to which the REM belongs to. If the row is empty, then the REM does not have any adjacent or overlapping REMs and therefore is not considered as a cluster. 
 
 Cell type score
 ~~~~~~~