From 1a628cb233fbee7f3079969d741a002a2f332dd8 Mon Sep 17 00:00:00 2001 From: Vicente Yepez <30469316+vyepez88@users.noreply.github.com> Date: Fri, 22 Apr 2022 16:57:14 +0200 Subject: [PATCH] Update output.rst --- docs/source/output.rst | 28 ++++++++++++++-------------- 1 file changed, 14 insertions(+), 14 deletions(-) diff --git a/docs/source/output.rst b/docs/source/output.rst index fae9ac62..c4b0e2a6 100644 --- a/docs/source/output.rst +++ b/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 `_ 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 `_ 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