Update pgxRpi.md

docs/pgxRpi.md

@@ -1,53 +1,71 @@
 # pgxRpi, an R Library to Access Progenetix Data
 
-`pgxRpi` is an API wrapper package to access data from Progenetix database. More details about this package are in the [vignettes](https://github.com/progenetix/pgxRpi). There are several functions in this R package.
+`pgxRpi` is an API wrapper package to access data from Progenetix database. For more detailed documentation, please visit the [GitHub repository](https://github.com/progenetix/pgxRpi). 
+
+## Retrieve available filters 
+
+Filters are rules to select records based on their field values, allowing for precise queries in Progenetix. More details about filters can be found [here](https://docs.progenetix.org/common/classifications-and-ontologies/). 
+
+The following code retrieves filters with the `NCIT` prefix:
+
+```
+ncit_filters <- pgxFilter(prefix="NCIT") 
+```
 
 ## Retrieve biosample information 
 
-You can select biosamples from specific groups of interests, chosen by a filter. The description about _filters_ is [here](https://docs.progenetix.org/common/classifications-and-ontologies/).
+You can retrieve biosample information from specific groups of interest, selected using a filter.
 
 ```
-biosamples <- pgxLoader(type="biosample", filters = "NCIT:C3512",codematches = TRUE)
+biosamples <- pgxLoader(type="biosamples", filters = "NCIT:C3512")
 ```
-The returned biosample information includes biosample id, various codes for tumor types, tumor stage, survival data, associated literature or research project, etc.
 
-## Query CNV coverage data of biosamples from specific cohorts
+The returned biosample information includes details such as biosample ID, tumor types, tumor stage, and associated literature or research projects.
 
-The coverage is calculated across 1MB genomic bins, chromosomal arms, whole chromosomes, or whole genome.
+## Retrieve individual information 
 
-The CNV coverage across genomic bins can be accessed by setting `output` = "pgxmatrix". More details about the data format "pgxmatrix" see the [documentation](https://docs.progenetix.org/services/#cnv-status-matrix).
+You can retrieve information about individuals from whom samples are derived, including survival data.
 
 ```
-cnv.status <- pgxLoader(type="variant", filters = "NCIT:C3058", output="pgxmatrix", codematches = T)
+individuals <- pgxLoader(type="individuals", filters = "NCIT:C3512")
 ```
+## Visualize survival data 
 
-The CNV coverage across chromosomal arms, chromosomes, or whole genome can be accessed by setting `output` = "coverage".
+You can visualize the survival differences between younger and older patients based on the queried individual information. 
 
 ```
-cnv.status <- pgxLoader(type="variant", filters = "NCIT:C4443", output="coverage", codematches = F)
+pgxMetaplot(individuals,group_id="age_iso", condition="P65Y", pval=TRUE)
 ```
 
+<img src="../img/pgxRpi-survival-plot.png" style="margin-left: auto; margin-right:auto" />
+
 ## Query and export segment copy number variant data 
 
-You can download the copy number variant data of individual biosamples. The biosample id can be queried by pgxRpi or by Progenetix [website](http://progenetix.org/biosamples/).
-The variant data exportation supports different output formats, more information see vignettes.
+You can download the copy number variant data of individual biosamples. The biosample ID can be obtained via pgxRpi or the [Progenetix website](http://progenetix.org/biosamples/).
+
+The variant data export supports different output formats. For more information, refer to the package vignettes.
 
 ```
-variants <- pgxLoader(type="variant", biosample_id = c("pgxbs-kftva6du","pgxbs-kftva6dv","pgxbs-kftva6dx"),output = "pgxseg")
+pgxLoader(type="g_variants", biosample_id = c("pgxbs-kftva6du","pgxbs-kftva6dx"),output = "pgxseg", save_file=TRUE)
 ```
 
-## Query and visualize CNV frequencies 
+## Query CNV fraction data of biosamples from specific cohorts
 
-You can query the CNV frequency of specific filters, namely specific cohorts. There are two available data formats. One is [`.pgxseg`](https://docs.progenetix.org/services/#pgxseg-segment-cnv-frequencies), good for visualization. Another is [`.pgxmatrix`](https://docs.progenetix.org/services/#cnv-frequency-matrix), good for analysis.
+CNV fractions are calculated based on segment data across various genomic scales, such as 1MB genomic bins, chromosomal arms, whole chromosomes, or the entire genome (GRCh38).
 
 ```
-frequency <- pgxLoader(type="frequency", output ='pgxseg',
-                         filters=c("NCIT:C4038","pgx:icdom-85003"), 
-                         codematches = TRUE)
+cnv_fraction_across_chro_genome <- pgxLoader(type="cnv_fraction", filters = "NCIT:C2948")
+cnv_fraction_across_bin <- pgxLoader(type="cnv_fraction", filters = "NCIT:C2948", output="pgxmatrix")
 ```
 
-The data visualization requires the input data with `.pgxseg` format. You can plot the frequency by genome, by chromosomes, or plot like circos.
+## Query and visualize CNV frequencies 
+
+You can query the CNV frequency of specific filters. There are two available data formats. One is [`.pgxfreq`](https://docs.progenetix.org/file-formats/#pgxfreq-segment-cnv-frequencies). Another is [`.pgxmatrix`]([https://docs.progenetix.org/services/#cnv-frequency-matrix].
 
+```
+frequency <- pgxLoader(type="cnv_frequency", output ='pgxfreq',
+                         filters=c("NCIT:C4038","pgx:icdom-85003"))
+```
 ```
 pgxFreqplot(frequency, filters='pgx:icdom-85003')
 ```