From 4d2b4aa5a97cc8f640a7b934298c871dbaea18d2 Mon Sep 17 00:00:00 2001 From: Hui Lan Date: Sat, 5 Nov 2022 22:16:57 +0800 Subject: Make correlation_per_group_fixed_number.R work, and update its upstream scripts (i.e., assign_tissue.py and refine_tissue.py). --- brain.documentation/QUICKSTART.rst | 9 ++++++--- 1 file changed, 6 insertions(+), 3 deletions(-) (limited to 'brain.documentation') diff --git a/brain.documentation/QUICKSTART.rst b/brain.documentation/QUICKSTART.rst index 4a5d95f..280def8 100644 --- a/brain.documentation/QUICKSTART.rst +++ b/brain.documentation/QUICKSTART.rst @@ -7,7 +7,7 @@ B R A I N :Version: 0.1.6 of 2022-10-09 -*Revision history: 9 June 2017, 22 June 2017, 4 July 2017, 11 July 2017 (created Section Drawing sub-networks), 18 July 2017 (created Section Uploading peak files), 10 October 2017 ('Enter a set of genes' under Section Exploring the network; created Section uRNA), 24 Jan 2018 (Enter 'AT1G24260 AGL9;SEP3 tissue specific tau 1.9' under Section Exploring the network), 3 August 2019 (design considerations), 5 August 2019 (updated create_edges0.py, added a section FAQs), 7 August 2019 (files needed for drawing a scatterplot online), 11 August 2019 (added information for correlation_per_group_fixed_number.R), 22 November 2019 (review and revise the entire content of this documentation), 4 April 2020 (use html_network.py to generate static html pages that contain a gene's regulators and regulatees; use cron job to copy these files to the web application), 6 February 2021 (write a section describing the running environment for brain), 9 October 2022 (remove PARAMETER_FOR from PARAMETER_FOR_BUILDRMATRIX_RENEW_INTERVAL, update section Automating downloading and updating the network)* +*Revision history: 9 June 2017, 22 June 2017, 4 July 2017, 11 July 2017 (created Section Drawing sub-networks), 18 July 2017 (created Section Uploading peak files), 10 October 2017 ('Enter a set of genes' under Section Exploring the network; created Section uRNA), 24 Jan 2018 (Enter 'AT1G24260 AGL9;SEP3 tissue specific tau 1.9' under Section Exploring the network), 3 August 2019 (design considerations), 5 August 2019 (updated create_edges0.py, added a section FAQs), 7 August 2019 (files needed for drawing a scatterplot online), 11 August 2019 (added information for correlation_per_group_fixed_number.R), 22 November 2019 (review and revise the entire content of this documentation), 4 April 2020 (use html_network.py to generate static html pages that contain a gene's regulators and regulatees; use cron job to copy these files to the web application), 6 February 2021 (write a section describing the running environment for brain), 9 October 2022 (remove PARAMETER_FOR from PARAMETER_FOR_BUILDRMATRIX_RENEW_INTERVAL, update section Automating downloading and updating the network), 5 November 2022 (update assign_tissue.py, refine_tissue.py, correlation_per_group_fixed_number.R)* .. contents:: @@ -1033,7 +1033,7 @@ Assign tissue names to RNA-seq samples We can assign each column (RNA-seq sample) in TPM.txt with a tissue name. If the RNA-seq sample's tissue is known, use it. Otherwise, predict it. The tissue information is used for displaying scatterplots, and for computing tissue-specific correlation coefficients (tissue.specific.correlation_). Follow the following three steps to get tissue names for RNA-seq samples: -- python assign_tissue.py > ../Data/temp/experiment.and.tissue.1.txt. +- python assign_tissue.py. This script writes to ../Data/temp/experiment.and.tissue.1.txt. - python refine_tissue.py > ../Data/information/experiment.and.tissue.2.txt @@ -1041,7 +1041,10 @@ We can assign each column (RNA-seq sample) in TPM.txt with a tissue name. If th - python update_rnaseq_info_json.py -This script will update Data/information/rnaseq_info_database.json, which is used to display scatterplots. It will also call knn_classify.R to predict tissues for unknown RNA-seq samples. The result is saved in Data/information/experiment.and.tissue.txt. + This script will update Data/information/rnaseq_info_database.json, + which is used to display scatterplots. It will also call + knn_classify.R to predict tissues for unknown RNA-seq samples. The + result is saved in Data/information/experiment.and.tissue.txt. Correlation and sample size -- cgit v1.2.1