Update output.rst

docs/source/output.rst

@@ -3,8 +3,8 @@ Results and Output of DROP
 
 DROP is intended to help researchers use RNA-Seq data in order to detect genes with aberrant expression,
 aberrant splicing and mono-allelic expression. By simplifying the workflow process we hope to provide
-easy to read and interpret HTML files and output files. This section explains the relevant
-results files. The paths of the output files correspond to the ones from the demo (that can be run with the following code snippet)::
+easy-to-read HTML files and output files. This section explains the results files. The paths of the output
+files correspond to the ones from the demo (that can be run with the following code snippet)::
 
     #install drop
     mamba create -n drop_env -c conda-forge -c bioconda drop
@@ -26,20 +26,20 @@ tab at the top of the screen. The Overview tab contains links to the:
 
 * Counts Summaries for each aberrant expression group
     * number of local and external samples
-    * QC relating to reads and size factors for each sample
+    * Mapped reads and size factors for each sample
     * histograms showing the mean count distribution with different conditions
     * expressed genes within each sample and as a dataset
 * Outrider Summaries for each aberrant expression group
     * aberrantly expressed genes per sample
     * correlation between samples before and after the autoencoder
-    * biological coefficient of variation plot
+    * biological coefficient of variation
     * aberrant samples
     * results table
 * Files for each aberrant expression group
     * OUTRIDER datasets 
         * Follow the `OUTRIDER vignette <https://www.bioconductor.org/packages/devel/bioc/vignettes/OUTRIDER/inst/doc/OUTRIDER.pdf>`_ for individual OUTRIDER object file (ods) analysis.
     * Results tables
-        * ``results.tsv`` this tsv file contains only the significant genes and samples that meet the cutoffs defined in the config file for ``padjCutoff`` and ``zScoreCutoff``
+        * ``results.tsv`` this text file contains only the significant genes and samples that meet the cutoffs defined in the config file for ``padjCutoff`` and ``zScoreCutoff``
 
 Local result files
 ##################
@@ -60,18 +60,18 @@ tab at the top of the screen. The Overview tab contains links to the:
     * histograms showing the junction expression before and after filtering and variability
 * FRASER Summaries for each aberrant splicing group
     * the number of samples, introns, and splice sites 
-    * how batch correction is done and the resulting lack of batch effects
-    * result table
+    * correlation between samples before and after the autoencoder
+    * results table
 * Files for each aberrant splicing group
     * FRASER datasets (fds)
         * Follow the `FRASER vignette <https://www.bioconductor.org/packages/devel/bioc/vignettes/FRASER/inst/doc/FRASER.pdf>`_ for individual FRASER object file (fds) analysis.
     * Results tables
-        * ``results_per_junction.tsv`` this tsv file contains only significant junctions that meet the cutoffs defined in the config file they are aggregated at the junction level. 
+        * ``results_per_junction.tsv`` this text file contains only significant junctions that meet the cutoffs defined in the config file. 
 
 Local result files
 ##################
 Additionally the ``aberrantSplicing`` module creates the following file ``Output/processed_results/aberrant_splicing/results/{annotation}/fraser/{drop_group}/results.tsv``.
-This tsv file contains only significant junctions that meet the cutoffs defined in the config file, they are aggregated at the gene level. Any sample/gene pair is represented by only the most significant junction.
+This text file contains only significant junctions that meet the cutoffs defined in the config file, aggregated at the gene level. Any sample/gene pair is represented by only the most significant junction.
 
 Mono-allelic Expression
 +++++++++++++++++++++++
@@ -82,17 +82,17 @@ Looking at the resulting ``Output/html/drop_demo_index.html`` we can see the ``M
 tab at the top of the screen. The Overview tab contains links to the:  
 
 * Results for each mae group
-    * the number of samples, unique genes, and aberrant events
+    * number of samples, genes, and mono-allelically expressed heterozygous SNVs
     * a cascade plot that shows additional filters
     * histogram of inner cohort frequency
-    * summary of cascade plots and results table
+    * summary of the cascade plot and results table
 * Files for each mae group
     * Allelic counts
         * a directory containing the allelic counts of heterozygous variants
     * Results data tables of each sample (.Rds)
         * Rds objects containing the full results table regardless of MAE status
     * Significant MAE results tables
-        * a link to the results tsv file.
+        * a link to the results file
         * Only contains significant MAE for the alternative allele results and results that pass the config file cutoffs
 * Quality Control
     * QC Overview
@@ -103,8 +103,8 @@ Local result files
 Additionally the ``mae`` module creates the following files:
 
 * ``Output/processed_results/mae/{drop_group}/MAE_results_all_{annotation}.tsv.gz``
-    * this file is the tsv results of all heterozygous variants regardless of significance
+    * this file contains the MAE results of all heterozygous SNVs regardless of significance
 * ``Output/processed_results/mae/{drop_group}/MAE_results_{annotation}.tsv``
     * this is the file linked in the HTML document and described above
 * ``Output/processed_results/mae/{drop_group}/MAE_results_{annotation}_rare.tsv``
-    * this file is the subsetted tsv of ``MAE_results_{annotation}.tsv`` with only the variants that pass the rare cutoffs. If ``add_AF`` is set to true in config file must meet minimum AF set by ``max_AF``. Additionally, the inner-cohort frequency must meet ``maxVarFreqCohort`` cutoff
+    * this file is a subset of ``MAE_results_{annotation}.tsv`` with only the variants that pass the allele frequency cutoffs. If ``add_AF`` is set to ``true`` in config file must meet minimum AF set by ``max_AF``. Additionally, the inner-cohort frequency must meet the ``maxVarFreqCohort`` cutoff