# HG changeset patch
# User azomics
# Date 1595509109 14400
# Node ID 62d8985a41e25bdb427cdede2c1dd5c2cc0ab93c
# Parent 8547aedf1350120dbf31981a1d6894d8ac06d86b
"planemo upload for repository https://github.com/ImmPortDB/immport-galaxy-tools/tree/master/flowtools/profile_cl commit 5cdc32e68f9ec685f9890902c5ecc75047248361"
diff -r 8547aedf1350 -r 62d8985a41e2 getOntology.R
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/getOntology.R Thu Jul 23 08:58:29 2020 -0400
@@ -0,0 +1,29 @@
+#!/usr/bin/Rscript --vanilla
+# Cell Ontology Module for Galaxy
+# FlowCL
+######################################################################
+# Copyright (c) 2016 Northrop Grumman.
+# All rights reserved.
+######################################################################
+#
+# Version 1
+# Cristel Thomas
+#
+#
+
+suppressWarnings(suppressMessages(library(flowCL)))
+suppressWarnings(suppressMessages(library(base)))
+
+getOntology <- function(output_file, markers) {
+ res <- flowCL(markers, ResetArch = TRUE)
+ if (length(res) == 6) {
+ report <- capture.output(res$Table)
+ sink(output_file)
+ cat(report, sep = "\n")
+ sink()
+ }
+}
+
+args <- commandArgs(trailingOnly = TRUE)
+markers <- paste(args[2:length(args)], collapse="")
+getOntology(args[1], markers)
diff -r 8547aedf1350 -r 62d8985a41e2 profileCLs.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/profileCLs.py Thu Jul 23 08:58:29 2020 -0400
@@ -0,0 +1,161 @@
+#!/usr/bin/env python
+
+######################################################################
+# Copyright (c) 2016 Northrop Grumman.
+# All rights reserved.
+######################################################################
+import sys
+import os
+from argparse import ArgumentParser
+from jinja2 import Environment, FileSystemLoader
+
+profile_key = {
+ "1": "-",
+ "2": "lo",
+ "3": "+",
+ "4": "hi"
+}
+
+
+def run_flowCL(phenotype, output_txt, output_pdf, tool):
+ run_command = " ". join(["Rscript --slave --vanilla", tool, output_txt, phenotype])
+ os.system(run_command)
+ get_graph = " ".join(["mv flowCL_results/*.pdf", output_pdf])
+ os.system(get_graph)
+ return
+
+
+def generate_flowCL_query(list_markers, list_types):
+ if (len(list_markers) != len(list_types)):
+ return("pb with headers")
+ query = []
+ # go through both lists, remove fsc/ssc
+ for i in range(1, len(list_markers)):
+ if not list_markers[i].startswith("FSC") and not list_markers[i].startswith("SSC"):
+ query.append(list_markers[i].upper())
+ query.append(profile_key[list_types[i]])
+ # return concatenated string
+ return("".join(query))
+
+
+def translate_profiles(input_file, tool_dir, output, html_dir):
+ os.mkdir(html_dir)
+
+ tool = "/".join([tool_dir, "getOntology.R"])
+ html_table = "".join([html_dir, "/CLprofiles.txt"])
+ score_table = "".join(["cp ", input_file, " ", html_dir, "/scores.txt"])
+ os.system(score_table)
+
+ # read profile
+ with open(input_file, "r") as flock_profiles, open(html_table, "w") as out:
+ headers = flock_profiles.readline()
+ headers = headers.strip()
+ # get all headers except for last 2 (count + percentage)
+ markers = headers.split("\t")[:-2]
+ counter = 0
+
+ out.write("Population\tFlowCL Query\tNb Results\tLink to PDF\t")
+ out.write("Top Result Label\tTop Result Score\tTop Result CL\n")
+ queries = {}
+ # create marker query for each population
+ for lines in flock_profiles:
+ lines = lines.strip("\n")
+ pop_profile = lines.split("\t")[:-2]
+ flowcl_query = generate_flowCL_query(markers, pop_profile)
+ counter += 1
+ nb_results = "0"
+ top_label = "no_match"
+ top_score = "NA"
+ top_CL = "NA"
+ pdf_link = "NA"
+ # check if query was run before
+ if flowcl_query not in queries:
+ # create filenames for results & graphs
+ txt = "".join(["flowcl_pop", str(counter).zfill(2), ".txt"])
+ text_result = "/".join([html_dir, txt])
+ graph = "".join(["flowcl_pop", str(counter).zfill(2), ".pdf"])
+ graph_output = "/".join([html_dir, graph])
+ # run flowCL for each marker profile
+ run_flowCL(flowcl_query, text_result, graph_output, tool)
+
+ # test that text file exists if not results are all NAs:
+ if os.path.isfile(text_result):
+ with open(text_result, "r") as res:
+ for line in res:
+ if line.startswith("Score"):
+ data = line.split(") ")
+ top_score = data[2][:-2]
+ tot_results = len(data) - 2
+ nb_results = str(tot_results)
+ if tot_results == 5:
+ if len(data[6].split("+")) > 1:
+ nb_results = "5+"
+ elif line.startswith("Cell ID"):
+ prep_link = line.split(") ")[1][:-2]
+ cl = prep_link.replace("_", ":")
+ link = "".join([''])
+ top_CL = "".join([link, prep_link, ""])
+ elif line.startswith("Cell Label"):
+ top_label = line.split(") ")[1][:-2]
+ pdf_link = "".join(['PDF'])
+ tmpflowcl_query = "".join(['', flowcl_query, ''])
+
+ queries[flowcl_query] = {
+ "query": tmpflowcl_query,
+ "results": nb_results,
+ "pdf": pdf_link,
+ "label": top_label,
+ "score": top_score,
+ "CL": top_CL
+ }
+ # write query results to CLprofiles.txt
+ out.write("\t".join([pop_profile[0],
+ queries[flowcl_query]["query"],
+ queries[flowcl_query]["results"],
+ queries[flowcl_query]["pdf"],
+ queries[flowcl_query]["label"],
+ queries[flowcl_query]["score"],
+ queries[flowcl_query]["CL"]]) + "\n")
+
+ env = Environment(loader=FileSystemLoader(tool_dir + "/templates"))
+ template = env.get_template("profileCLs.template")
+
+ real_directory = html_dir.replace("/job_working_directory", "")
+ context = {'outputDirectory': real_directory}
+ overview = template.render(**context)
+ with open(output, "w") as outf:
+ outf.write(overview)
+
+
+if __name__ == "__main__":
+ parser = ArgumentParser(
+ prog="getCLs_from_profile",
+ description="runs flowCL on a each population defined by FLOCK.")
+
+ parser.add_argument(
+ '-i',
+ dest="input_file",
+ required=True,
+ help="File location for the profile.txt from FLOCK.")
+
+ parser.add_argument(
+ '-o',
+ dest="output",
+ required=True,
+ help="Name of the output html file.")
+
+ parser.add_argument(
+ '-d',
+ dest="html_dir",
+ required=True,
+ help="Path to html supporting directory.")
+
+ parser.add_argument(
+ '-t',
+ dest="tool_dir",
+ required=True,
+ help="Path to the tool directory")
+
+ args = parser.parse_args()
+
+ translate_profiles(args.input_file, args.tool_dir, args.output, args.html_dir)
diff -r 8547aedf1350 -r 62d8985a41e2 profileCLs.xml
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/profileCLs.xml Thu Jul 23 08:58:29 2020 -0400
@@ -0,0 +1,65 @@
+
+ with cell ontology
+
+ jinja2
+ bioconductor-flowcl
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ 10.1093/bioinformatics/btu807
+
+
diff -r 8547aedf1350 -r 62d8985a41e2 profile_cl/getOntology.R
--- a/profile_cl/getOntology.R Mon Feb 27 13:03:19 2017 -0500
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,28 +0,0 @@
-# Cell Ontology Module for Galaxy
-# FlowCL
-######################################################################
-# Copyright (c) 2016 Northrop Grumman.
-# All rights reserved.
-######################################################################
-#
-# Version 1
-# Cristel Thomas
-#
-#
-
-library(flowCL)
-library(base)
-
-getOntology <- function(output_file, markers) {
- res <- flowCL(markers, ResetArch = TRUE)
- if (length(res) == 6) {
- report <- capture.output(res$Table)
- sink(output_file)
- cat(report, sep = "\n")
- sink()
- }
-}
-
-args <- commandArgs(trailingOnly = TRUE)
-markers <- paste(args[3:length(args)], collapse="")
-getOntology(args[2], markers)
diff -r 8547aedf1350 -r 62d8985a41e2 profile_cl/profileCLs.py
--- a/profile_cl/profileCLs.py Mon Feb 27 13:03:19 2017 -0500
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,163 +0,0 @@
-#!/usr/bin/env python
-
-######################################################################
-# Copyright (c) 2016 Northrop Grumman.
-# All rights reserved.
-######################################################################
-from __future__ import print_function
-import sys
-import os
-from argparse import ArgumentParser
-from jinja2 import Environment, FileSystemLoader
-
-profile_key = {
- "1": "-",
- "2": "lo",
- "3": "+",
- "4": "hi"
-}
-
-
-def run_flowCL(phenotype, output_txt, output_pdf, tool):
- run_command = " ". join(["Rscript --slave --vanilla", tool, "--args", output_txt, phenotype])
- os.system(run_command)
- get_graph = " ".join(["mv flowCL_results/*.pdf", output_pdf])
- os.system(get_graph)
- return
-
-
-def generate_flowCL_query(list_markers, list_types):
- if (len(list_markers) != len(list_types)):
- return("pb with headers")
- query = []
- # go through both lists, remove fsc/ssc
- for i in range(1, len(list_markers)):
- if not list_markers[i].startswith("FSC") and not list_markers[i].startswith("SSC"):
- query.append(list_markers[i].upper())
- query.append(profile_key[list_types[i]])
- # return concatenated string
- return("".join(query))
-
-
-def translate_profiles(input_file, tool_dir, output, html_dir):
- os.mkdir(html_dir)
-
- tool = "/".join([tool_dir, "getOntology.R"])
- html_table = "".join([html_dir, "/CLprofiles.txt"])
- score_table = "".join(["cp ", input_file, " ", html_dir, "/scores.txt"])
- os.system(score_table)
-
- # read profile
- with open(input_file, "r") as flock_profiles, open(html_table, "w") as out:
- headers = flock_profiles.readline()
- headers = headers.strip()
- # get all headers except for last 2 (count + percentage)
- markers = headers.split("\t")[:-2]
- counter = 0
-
- out.write("Population\tFlowCL Query\tNb Results\tLink to PDF\t")
- out.write("Top Result Label\tTop Result Score\tTop Result CL\n")
- queries = {}
- # create marker query for each population
- for lines in flock_profiles:
- lines = lines.strip("\n")
- pop_profile = lines.split("\t")[:-2]
- flowcl_query = generate_flowCL_query(markers, pop_profile)
- counter += 1
- nb_results = "0"
- top_label = "no_match"
- top_score = "NA"
- top_CL = "NA"
- pdf_link = "NA"
- # check if query was run before
- if flowcl_query not in queries:
- # create filenames for results & graphs
- txt = "".join(["flowcl_pop", str(counter).zfill(2), ".txt"])
- text_result = "/".join([html_dir, txt])
- graph = "".join(["flowcl_pop", str(counter).zfill(2), ".pdf"])
- graph_output = "/".join([html_dir, graph])
- # run flowCL for each marker profile
- run_flowCL(flowcl_query, text_result, graph_output, tool)
-
- # test that text file exists if not results are all NAs:
- if os.path.isfile(text_result):
- with open(text_result, "r") as res:
- for line in res:
- if line.startswith("Score"):
- data = line.split(") ")
- top_score = data[2][:-2]
- tot_results = len(data) - 2
- nb_results = str(tot_results)
- if tot_results == 5:
- if len(data[6].split("+")) > 1:
- nb_results = "5+"
- elif line.startswith("Cell ID"):
- prep_link = line.split(") ")[1][:-2]
- cl = prep_link.replace("_", ":")
- link = "".join([''])
- top_CL = "".join([link, prep_link, ""])
- elif line.startswith("Cell Label"):
- top_label = line.split(") ")[1][:-2]
- pdf_link = "".join(['PDF'])
- tmpflowcl_query = "".join(['', flowcl_query, ''])
-
- queries[flowcl_query] = {
- "query": tmpflowcl_query,
- "results": nb_results,
- "pdf": pdf_link,
- "label": top_label,
- "score": top_score,
- "CL": top_CL
- }
- # write query results to CLprofiles.txt
- out.write("\t".join([pop_profile[0],
- queries[flowcl_query]["query"],
- queries[flowcl_query]["results"],
- queries[flowcl_query]["pdf"],
- queries[flowcl_query]["label"],
- queries[flowcl_query]["score"],
- queries[flowcl_query]["CL"]]) + "\n")
-
- env = Environment(loader=FileSystemLoader(tool_dir + "/templates"))
- template = env.get_template("profileCLs.template")
-
- real_directory = html_dir.replace("/job_working_directory", "")
- context = {'outputDirectory': real_directory}
- overview = template.render(**context)
- with open(output, "w") as outf:
- outf.write(overview)
-
-
-if __name__ == "__main__":
- parser = ArgumentParser(
- prog="getCLs_from_profile",
- description="runs flowCL on a each population defined by FLOCK.")
-
- parser.add_argument(
- '-i',
- dest="input_file",
- required=True,
- help="File location for the profile.txt from FLOCK.")
-
- parser.add_argument(
- '-o',
- dest="output",
- required=True,
- help="Name of the output html file.")
-
- parser.add_argument(
- '-d',
- dest="html_dir",
- required=True,
- help="Path to html supporting directory.")
-
- parser.add_argument(
- '-t',
- dest="tool_dir",
- required=True,
- help="Path to the tool directory")
-
- args = parser.parse_args()
-
- translate_profiles(args.input_file, args.tool_dir, args.output, args.html_dir)
- sys.exit(0)
diff -r 8547aedf1350 -r 62d8985a41e2 profile_cl/profileCLs.xml
--- a/profile_cl/profileCLs.xml Mon Feb 27 13:03:19 2017 -0500
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,116 +0,0 @@
-
- with cell ontology
-
- jinja2
- r
- bioconductor-flowcl
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
- 10.1093/bioinformatics/btu807
-
-
diff -r 8547aedf1350 -r 62d8985a41e2 profile_cl/static/flowtools/css/flowCL.css
--- a/profile_cl/static/flowtools/css/flowCL.css Mon Feb 27 13:03:19 2017 -0500
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,34 +0,0 @@
-/*
-** DataTables config
-*/
-div.dt-buttons {
- float: right;
-}
-th {
- font-size:16px;
- text-align: left;
-}
-body td {
- max-width: 50px;
- font-size: 14px;
- overflow: hidden;
- text-overflow: ellipsis;
-}
-.cltable thead {
- display:none;
-}
-.cltable td {
- max-width: 40px;
- word-break: break-all;
- word-wrap: break-word;
-}
-.firstcol {
- width: 160px;
-}
-.smallcols {
- width: 100px;
-}
-div.dataTables_wrapper {
- width: 95%;
- margin: 0 auto;
-}
diff -r 8547aedf1350 -r 62d8985a41e2 profile_cl/static/flowtools/js/profileCLs.js
--- a/profile_cl/static/flowtools/js/profileCLs.js Mon Feb 27 13:03:19 2017 -0500
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,85 +0,0 @@
-// Copyright (c) 2016 Northrop Grumman.
-// All rights reserved.
-
-var cl_table = './CLprofiles.txt';
-var scores_table = './scores.txt';
-
-var displayCLTable = function(){
- d3.text(cl_table, function(error, data){
- var clHdgs = [],
- clHTML = '',
- clTableData = [],
- clHeadings = [];
-
- if (error){
- alert("Problem retrieving data");
- return;
- }
- clHdgs = data.split("\n")[0].split("\t");
- data = d3.tsv.parse(data);
- clTableData = $.extend(true, [], data);
-
- clHdgs.forEach(function(d,i){
- clHeadings.push({"data" : d, "title" : d});
- });
-
- $('#clprofiles').html(clHTML);
- var clTable = $('#cltable').DataTable({
- columns: clHeadings,
- dom: '<"top"Bi>t<"bottom"lp><"clear">',
- pageLength: 25,
- order: [[ 0, "asc" ]],
- data: clTableData,
- buttons: [
- 'copy', 'pdfHtml5','csvHtml5'
- ],
- columnDefs: [
- {
- targets: [0,2,3],
- className: "smallcols"
- },
- {
- targets: 4,
- className: "dt-body-left"
- },
- {
- targets: [5,6],
- className: "firstcol"
- }]
- });
- });
-};
-
-var displayScoresTable = function(){
- d3.text(scores_table, function(error, data){
- var scoreHTML = '',
- scoreHdgs = [],
- scoreTableData = [],
- scoreHeadings = [];
- if (error){
- alert("Problem retrieving data");
- return;
- }
- scoreHdgs = data.split("\n")[0].split("\t");
- data = d3.tsv.parse(data);
-
- $('#scores').html(scoreHTML);
-
- scoreTableData = $.extend(true, [], data);
-
- scoreHdgs.forEach(function(d,i){
- scoreHeadings.push({"data" : d, "title" : d});
- });
-
- var scoreTable = $('#scoretable').DataTable({
- columns: scoreHeadings,
- pageLength: 25,
- order: [[ 0, "asc" ]],
- dom: '<"top"Bi>t<"bottom"lp><"clear">',
- data: scoreTableData,
- buttons: [
- 'copy', 'pdfHtml5','csvHtml5'
- ],
- });
- });
-};
diff -r 8547aedf1350 -r 62d8985a41e2 profile_cl/static/images/flowtools/popprofiles.png
Binary file profile_cl/static/images/flowtools/popprofiles.png has changed
diff -r 8547aedf1350 -r 62d8985a41e2 profile_cl/static/images/flowtools/profileCL.png
Binary file profile_cl/static/images/flowtools/profileCL.png has changed
diff -r 8547aedf1350 -r 62d8985a41e2 profile_cl/templates/profileCLs.template
--- a/profile_cl/templates/profileCLs.template Mon Feb 27 13:03:19 2017 -0500
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,91 +0,0 @@
-
-
-
-FLOCK Populations Ontology
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
diff -r 8547aedf1350 -r 62d8985a41e2 profile_cl/test-data/CLprofiles.txt
--- a/profile_cl/test-data/CLprofiles.txt Mon Feb 27 13:03:19 2017 -0500
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,4 +0,0 @@
-Population FlowCL Query Nb Results Link to PDF Top Result Label Top Result Score Top Result CL
-1 CD4+CCR3-CD8-CCR7- 5+ PDF effector CD4-positive, alpha-beta T cell 0.167 CL_0001044
-2 CD4+CCR3-CD8-CCR7- 5+ PDF effector CD4-positive, alpha-beta T cell 0.167 CL_0001044
-3 CD4+CCR3-CD8+CCR7lo 5+ PDF mature CD8_alpha-negative CD11b-positive dendritic cell 2)" -0.357 CL_0001003
diff -r 8547aedf1350 -r 62d8985a41e2 profile_cl/test-data/flowcl_pop01.pdf
Binary file profile_cl/test-data/flowcl_pop01.pdf has changed
diff -r 8547aedf1350 -r 62d8985a41e2 profile_cl/test-data/flowcl_pop01.txt
--- a/profile_cl/test-data/flowcl_pop01.txt Mon Feb 27 13:03:19 2017 -0500
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,44 +0,0 @@
- [,1]
-Short marker names "CD4+CCR3-CD8-CCR7-"
-Ontology marker names "CD4 molecule, C-C chemokine receptor type 3, T cell receptor"
- "co-receptor CD8, C-C chemokine receptor type 7"
-Experiment markers "CD4,CCR3,CD8,CCR7"
-Ontology exper. names "CD4 molecule, C-C chemokine receptor type 3, T cell receptor"
- "co-receptor CD8, C-C chemokine receptor type 7"
-Successful Match? "No"
-Marker ID "1) PR_000001004, PR_000025402, PR_000001203 2) PR_000001004,"
- "PR_000025402, PR_000001203 3) PR_000001004, PR_000025402,"
- "PR_000001203 4) PR_000001004, PR_000025402 5) PR_000001004,"
- "PR_000025402 + more"
-Marker Label "1) CD4 molecule, T cell receptor co-receptor CD8, C-C chemokine"
- "receptor type 7 2) CD4 molecule, T cell receptor co-receptor CD8, C-C"
- "chemokine receptor type 7 3) CD4 molecule, T cell receptor"
- "co-receptor CD8, C-C chemokine receptor type 7 4) CD4 molecule, T"
- "cell receptor co-receptor CD8 5) CD4 molecule, T cell receptor"
- "co-receptor CD8 + more"
-Marker Key "1) { CCR3- } CD8-, CCR7-, CD4+ ( ) [ alpha-beta T cell receptor"
- "complex+, receptor-type tyrosine-protein phosphatase C isoform"
- "CD45RA+, CD3+ ] 2) { CCR3- } CD8-, CCR7-, CD4+ ( ) [ alpha-beta T"
- "cell receptor complex+, C-X-C chemokine receptor type 5+, inducible"
- "T-cell costimulator+, programmed cell death protein 1+, CD3+ ] 3) {"
- "CCR3- } CD8-, CCR7-, CD4+ ( ) [ interleukin-2 receptor subunit"
- "alpha-, receptor-type tyrosine-protein phosphatase C isoform CD45RA-,"
- "alpha-beta T cell receptor complex+, receptor-type tyrosine-protein"
- "phosphatase C isoform CD45RO+, interleukin-7 receptor subunit alpha+,"
- "CD3+, CD44 moleculehi, interleukin-2 receptor subunit betahi ] 4) {"
- "CCR3-, CCR7- } CD8-, CD4+ ( ) [ L-selectin-, interleukin-7 receptor"
- "subunit alpha-, alpha-beta T cell receptor complex+, CD69 molecule+,"
- "interleukin-2 receptor subunit alpha+, ADP-ribosyl cyclase 1+, MHC"
- "class II histocompatibility antigen alpha chain HLA-DRA+, CD3+ ] 5) {"
- "CCR3-, CCR7- } CD8-, CD4+ ( ) [ interleukin-2 receptor subunit"
- "alpha-, alpha-beta T cell receptor complex+, receptor-type"
- "tyrosine-protein phosphatase C isoform CD45RO+, interleukin-7"
- "receptor subunit alpha+, CD3+, CD44 moleculehi, interleukin-2"
- "receptor subunit betahi ] + more"
-Score (Out of 1) "1) 0.167 2) 0.125 3) 0.091 4) -0.2 5) -0.222 + more"
-Cell ID "1) CL_0001044 2) CL_0002038 3) CL_0000905 4) CL_0001043 5) CL_0000897"
- "+ more"
-Cell Label "1) effector CD4-positive, alpha-beta T cell 2) T follicular helper"
- "cell 3) effector memory CD4-positive, alpha-beta T cell 4) activated"
- "CD4-positive, alpha-beta T cell, human 5) CD4-positive, alpha-beta"
- "memory T cell + more"
diff -r 8547aedf1350 -r 62d8985a41e2 profile_cl/test-data/flowcl_pop03.pdf
Binary file profile_cl/test-data/flowcl_pop03.pdf has changed
diff -r 8547aedf1350 -r 62d8985a41e2 profile_cl/test-data/flowcl_pop03.txt
--- a/profile_cl/test-data/flowcl_pop03.txt Mon Feb 27 13:03:19 2017 -0500
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- [,1]
-Short marker names "CD4+CCR3-CD8+CCR7lo"
-Ontology marker names "CD4 molecule, C-C chemokine receptor type 3, T cell receptor"
- "co-receptor CD8, C-C chemokine receptor type 7"
-Experiment markers "CD4,CCR3,CD8,CCR7"
-Ontology exper. names "CD4 molecule, C-C chemokine receptor type 3, T cell receptor"
- "co-receptor CD8, C-C chemokine receptor type 7"
-Successful Match? "No"
-Marker ID "1) PR_000001004 2) PR_000001004 3) PR_000001004 4) PR_000001004 5)"
- "PR_000001004, PR_000025402 + more"
-Marker Label "1) CD4 molecule 2) CD4 molecule 3) CD4 molecule 4) CD4 molecule 5)"
- "CD4 molecule, T cell receptor co-receptor CD8 + more"
-Marker Key "1) { CD8+, CCR3-, CCR7lo } CD4+ ( ) [ CD19 molecule-, CD34 molecule-,"
- "CD34 molecule-, neural cell adhesion molecule 1-, membrane-spanning"
- "4-domains subfamily A member 1-, lymphocyte antigen 75-, T-cell"
- "surface glycoprotein CD8 alpha chain-, CD83 molecule+, integrin"
- "alpha-M+, MHC class II protein complexhi, CD86 moleculehi, CD80"
- "moleculehi, integrin alpha-Xhi ] 2) { CD8+, CCR3-, CCR7lo } CD4+ ( )"
- "[ CD19 molecule-, CD34 molecule-, CD34 molecule-, neural cell"
- "adhesion molecule 1-, membrane-spanning 4-domains subfamily A member"
- "1-, lymphocyte antigen 75-, T-cell surface glycoprotein CD8 alpha"
- "chain-, integrin alpha-M+, MHC class II protein complexlo, CD86"
- "moleculelo, CD80 moleculelo, integrin alpha-Xhi ] 3) { CD8+, CCR3-,"
- "CCR7lo } CD4+ ( ) [ CD19 molecule-, CD34 molecule-, CD34 molecule-,"
- "neural cell adhesion molecule 1-, membrane-spanning 4-domains"
- "subfamily A member 1-, integrin alpha-M-, T-cell surface glycoprotein"
- "CD8 alpha chain-, receptor-type tyrosine-protein phosphatase C"
- "isoform CD45R+, lymphocyte antigen 6G+, integrin alpha-Xlo ] 4) {"
- "CD8+, CCR3-, CCR7lo } CD4+ ( ) [ CD19 molecule-, CD34 molecule-, CD34"
- "molecule-, neural cell adhesion molecule 1-, membrane-spanning"
- "4-domains subfamily A member 1-, integrin alpha-M-, receptor-type"
- "tyrosine-protein phosphatase C isoform CD45R+, lymphocyte antigen"
- "6G+, T-cell surface glycoprotein CD8 alpha chain+, integrin alpha-Xlo"
- "] 5) { CCR3-, CCR7lo } CD4+, CD8+ ( ) [ alpha-beta T cell receptor"
- "complexlo, CD69 molecule+ ] + more"
-Score (Out of 1) "1) -0.357 2) -0.385 3) -0.455 4) -0.455 5) -0.5 + more"
-Cell ID "1) CL_0001003 2) CL_0000997 3) CL_0002455 4) CL_0002456 5) CL_0002429"
- "+ more"
-Cell Label "1) mature CD8_alpha-negative CD11b-positive dendritic cell 2)"
- "immature CD8_alpha-negative CD11b-positive dendritic cell 3)"
- "CD8_alpha-negative plasmactyoid dendritic cell 4) CD8_alpha-positive"
- "plasmactyoid dendritic cell 5) CD69-positive double-positive"
- "thymocyte + more"
diff -r 8547aedf1350 -r 62d8985a41e2 profile_cl/test-data/input.flowscore
--- a/profile_cl/test-data/input.flowscore Mon Feb 27 13:03:19 2017 -0500
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-Population_ID FSC SSC CD4 CCR3 CD8 CCR7 Count Percentage
-1 1 1 3 1 1 1 1000 5
-2 1 1 3 1 1 1 1000 5
-3 1 1 3 1 3 2 1000 5
diff -r 8547aedf1350 -r 62d8985a41e2 profile_cl/test-data/out.html
--- a/profile_cl/test-data/out.html Mon Feb 27 13:03:19 2017 -0500
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diff -r 8547aedf1350 -r 62d8985a41e2 profile_cl/test-data/scores.txt
--- a/profile_cl/test-data/scores.txt Mon Feb 27 13:03:19 2017 -0500
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-Population_ID FSC SSC CD4 CCR3 CD8 CCR7 Count Percentage
-1 1 1 3 1 1 1 1000 5
-2 1 1 3 1 1 1 1000 5
-3 1 1 3 1 3 2 1000 5
diff -r 8547aedf1350 -r 62d8985a41e2 static/images/flowtools/popprofiles.png
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diff -r 8547aedf1350 -r 62d8985a41e2 static/images/flowtools/profileCL.png
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diff -r 8547aedf1350 -r 62d8985a41e2 templates/profileCLs.template
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diff -r 8547aedf1350 -r 62d8985a41e2 test-data/CLprofiles.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/CLprofiles.txt Thu Jul 23 08:58:29 2020 -0400
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+Population FlowCL Query Nb Results Link to PDF Top Result Label Top Result Score Top Result CL
+1 CD4+CCR3-CD8-CCR7- 5+ PDF effector CD4-positive, alpha-beta T cell 0.167 CL_0001044
+2 CD4+CCR3-CD8-CCR7- 5+ PDF effector CD4-positive, alpha-beta T cell 0.167 CL_0001044
+3 CD4+CCR3-CD8+CCR7lo 5+ PDF mature CD8_alpha-negative CD11b-positive dendritic cell 2)" -0.357 CL_0001003
diff -r 8547aedf1350 -r 62d8985a41e2 test-data/flowcl_pop01.pdf
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diff -r 8547aedf1350 -r 62d8985a41e2 test-data/flowcl_pop01.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/flowcl_pop01.txt Thu Jul 23 08:58:29 2020 -0400
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+ [,1]
+Short marker names "CD4+CCR3-CD8-CCR7-"
+Ontology marker names "CD4 molecule, C-C chemokine receptor type 3, T cell receptor"
+ "co-receptor CD8, C-C chemokine receptor type 7"
+Experiment markers "CD4,CCR3,CD8,CCR7"
+Ontology exper. names "CD4 molecule, C-C chemokine receptor type 3, T cell receptor"
+ "co-receptor CD8, C-C chemokine receptor type 7"
+Successful Match? "No"
+Marker ID "1) PR_000001004, PR_000025402, PR_000001203 2) PR_000001004,"
+ "PR_000025402, PR_000001203 3) PR_000001004, PR_000025402,"
+ "PR_000001203 4) PR_000001004, PR_000025402 5) PR_000001004,"
+ "PR_000025402 + more"
+Marker Label "1) CD4 molecule, T cell receptor co-receptor CD8, C-C chemokine"
+ "receptor type 7 2) CD4 molecule, T cell receptor co-receptor CD8, C-C"
+ "chemokine receptor type 7 3) CD4 molecule, T cell receptor"
+ "co-receptor CD8, C-C chemokine receptor type 7 4) CD4 molecule, T"
+ "cell receptor co-receptor CD8 5) CD4 molecule, T cell receptor"
+ "co-receptor CD8 + more"
+Marker Key "1) { CCR3- } CD8-, CCR7-, CD4+ ( ) [ alpha-beta T cell receptor"
+ "complex+, receptor-type tyrosine-protein phosphatase C isoform"
+ "CD45RA+, CD3+ ] 2) { CCR3- } CD8-, CCR7-, CD4+ ( ) [ alpha-beta T"
+ "cell receptor complex+, C-X-C chemokine receptor type 5+, inducible"
+ "T-cell costimulator+, programmed cell death protein 1+, CD3+ ] 3) {"
+ "CCR3- } CD8-, CCR7-, CD4+ ( ) [ interleukin-2 receptor subunit"
+ "alpha-, receptor-type tyrosine-protein phosphatase C isoform CD45RA-,"
+ "alpha-beta T cell receptor complex+, receptor-type tyrosine-protein"
+ "phosphatase C isoform CD45RO+, interleukin-7 receptor subunit alpha+,"
+ "CD3+, CD44 moleculehi, interleukin-2 receptor subunit betahi ] 4) {"
+ "CCR3-, CCR7- } CD8-, CD4+ ( ) [ L-selectin-, interleukin-7 receptor"
+ "subunit alpha-, alpha-beta T cell receptor complex+, CD69 molecule+,"
+ "interleukin-2 receptor subunit alpha+, ADP-ribosyl cyclase 1+, MHC"
+ "class II histocompatibility antigen alpha chain HLA-DRA+, CD3+ ] 5) {"
+ "CCR3-, CCR7- } CD8-, CD4+ ( ) [ interleukin-2 receptor subunit"
+ "alpha-, alpha-beta T cell receptor complex+, receptor-type"
+ "tyrosine-protein phosphatase C isoform CD45RO+, interleukin-7"
+ "receptor subunit alpha+, CD3+, CD44 moleculehi, interleukin-2"
+ "receptor subunit betahi ] + more"
+Score (Out of 1) "1) 0.167 2) 0.125 3) 0.091 4) -0.2 5) -0.222 + more"
+Cell ID "1) CL_0001044 2) CL_0002038 3) CL_0000905 4) CL_0001043 5) CL_0000897"
+ "+ more"
+Cell Label "1) effector CD4-positive, alpha-beta T cell 2) T follicular helper"
+ "cell 3) effector memory CD4-positive, alpha-beta T cell 4) activated"
+ "CD4-positive, alpha-beta T cell, human 5) CD4-positive, alpha-beta"
+ "memory T cell + more"
diff -r 8547aedf1350 -r 62d8985a41e2 test-data/flowcl_pop03.pdf
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diff -r 8547aedf1350 -r 62d8985a41e2 test-data/flowcl_pop03.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/flowcl_pop03.txt Thu Jul 23 08:58:29 2020 -0400
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+ [,1]
+Short marker names "CD4+CCR3-CD8+CCR7lo"
+Ontology marker names "CD4 molecule, C-C chemokine receptor type 3, T cell receptor"
+ "co-receptor CD8, C-C chemokine receptor type 7"
+Experiment markers "CD4,CCR3,CD8,CCR7"
+Ontology exper. names "CD4 molecule, C-C chemokine receptor type 3, T cell receptor"
+ "co-receptor CD8, C-C chemokine receptor type 7"
+Successful Match? "No"
+Marker ID "1) PR_000001004 2) PR_000001004 3) PR_000001004 4) PR_000001004 5)"
+ "PR_000001004, PR_000025402 + more"
+Marker Label "1) CD4 molecule 2) CD4 molecule 3) CD4 molecule 4) CD4 molecule 5)"
+ "CD4 molecule, T cell receptor co-receptor CD8 + more"
+Marker Key "1) { CD8+, CCR3-, CCR7lo } CD4+ ( ) [ CD19 molecule-, CD34 molecule-,"
+ "CD34 molecule-, neural cell adhesion molecule 1-, membrane-spanning"
+ "4-domains subfamily A member 1-, lymphocyte antigen 75-, T-cell"
+ "surface glycoprotein CD8 alpha chain-, CD83 molecule+, integrin"
+ "alpha-M+, MHC class II protein complexhi, CD86 moleculehi, CD80"
+ "moleculehi, integrin alpha-Xhi ] 2) { CD8+, CCR3-, CCR7lo } CD4+ ( )"
+ "[ CD19 molecule-, CD34 molecule-, CD34 molecule-, neural cell"
+ "adhesion molecule 1-, membrane-spanning 4-domains subfamily A member"
+ "1-, lymphocyte antigen 75-, T-cell surface glycoprotein CD8 alpha"
+ "chain-, integrin alpha-M+, MHC class II protein complexlo, CD86"
+ "moleculelo, CD80 moleculelo, integrin alpha-Xhi ] 3) { CD8+, CCR3-,"
+ "CCR7lo } CD4+ ( ) [ CD19 molecule-, CD34 molecule-, CD34 molecule-,"
+ "neural cell adhesion molecule 1-, membrane-spanning 4-domains"
+ "subfamily A member 1-, integrin alpha-M-, T-cell surface glycoprotein"
+ "CD8 alpha chain-, receptor-type tyrosine-protein phosphatase C"
+ "isoform CD45R+, lymphocyte antigen 6G+, integrin alpha-Xlo ] 4) {"
+ "CD8+, CCR3-, CCR7lo } CD4+ ( ) [ CD19 molecule-, CD34 molecule-, CD34"
+ "molecule-, neural cell adhesion molecule 1-, membrane-spanning"
+ "4-domains subfamily A member 1-, integrin alpha-M-, receptor-type"
+ "tyrosine-protein phosphatase C isoform CD45R+, lymphocyte antigen"
+ "6G+, T-cell surface glycoprotein CD8 alpha chain+, integrin alpha-Xlo"
+ "] 5) { CCR3-, CCR7lo } CD4+, CD8+ ( ) [ alpha-beta T cell receptor"
+ "complexlo, CD69 molecule+ ] + more"
+Score (Out of 1) "1) -0.357 2) -0.385 3) -0.455 4) -0.455 5) -0.5 + more"
+Cell ID "1) CL_0001003 2) CL_0000997 3) CL_0002455 4) CL_0002456 5) CL_0002429"
+ "+ more"
+Cell Label "1) mature CD8_alpha-negative CD11b-positive dendritic cell 2)"
+ "immature CD8_alpha-negative CD11b-positive dendritic cell 3)"
+ "CD8_alpha-negative plasmactyoid dendritic cell 4) CD8_alpha-positive"
+ "plasmactyoid dendritic cell 5) CD69-positive double-positive"
+ "thymocyte + more"
diff -r 8547aedf1350 -r 62d8985a41e2 test-data/input.flowscore
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/input.flowscore Thu Jul 23 08:58:29 2020 -0400
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+Population_ID FSC SSC CD4 CCR3 CD8 CCR7 Count Percentage
+1 1 1 3 1 1 1 1000 5
+2 1 1 3 1 1 1 1000 5
+3 1 1 3 1 3 2 1000 5
diff -r 8547aedf1350 -r 62d8985a41e2 test-data/out.html
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/out.html Thu Jul 23 08:58:29 2020 -0400
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diff -r 8547aedf1350 -r 62d8985a41e2 test-data/scores.txt
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/scores.txt Thu Jul 23 08:58:29 2020 -0400
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+Population_ID FSC SSC CD4 CCR3 CD8 CCR7 Count Percentage
+1 1 1 3 1 1 1 1000 5
+2 1 1 3 1 1 1 1000 5
+3 1 1 3 1 3 2 1000 5