Cell population score (DEGs)¶
Calculate immune cell population score for differentially expressed genes.
$ ../../icepop/scripts/icepop_degs -h
usage: icepop_degs [-h] [-s] [-g] [-cv_organ] [-o] [--gene_count] [--logscale]
[--verbose] [-fclim FCLIM]
[filename]
Cell population score for differentially expressed genes.
positional arguments:
filename DEGs file in TSV, CSV or Excel format
optional arguments:
-h, --help show this help message and exit
-s , -species species (mouse, human)
-g , -organs organs ('no_pref','bone_marrow', etc)
-cv_organ organs ('no_pref','ln', 'lv','sp')
-o , -outfile output file in stdout, JSON, PNG/JPG/SVG format
--gene_count normalized score by gene_count
--logscale perform log scale on FC or expression
--verbose verbose output
-fclim FCLIM specify single fold change threshold
The input should be either in form of CSV, TSV or Excel files. The results can be in the form of table or plot. They are determined by the suffix of the output file.
To create plot:
$ icepop_degs input_type1_degs.tsv -fclim 2 -s mouse -o output_file.jpg
The command will produce individual plots depending on the number of samples. To create table:
$ icepop_degs input_type1_degs.tsv -fclim 2 -s mouse -o output_file.tsv
$ icepop_degs input_type1_degs.tsv -fclim 2 -s mouse -o output_file.xlsx
Suffixes of the output should either one of these: ‘svg’, ‘jpg’, ‘png’, ‘tsv’, ‘xlsx’, ‘xls’.
Circos plot for unearthing the gene features in immune cells¶
This script produces the circular plot that links feature genes among the samples.
$ ../../icepop/scripts/icepop_degs_circos_uniform -h
usage: icepop_degs_circos_uniform [-h] [-s] [-g] [-cv_organ] [-p] [-c] [-o]
[-fclim FCLIM] [-circos_dir] [--gene_count]
[--logscale] [--go] [--verbose]
[filename]
Cell population score for differentially expressed genes.
positional arguments:
filename DEGs file in TSV, CSV or Excel format
optional arguments:
-h, --help show this help message and exit
-s , -species species (mouse, human)
-g , -organs organs ('no_pref','bone_marrow', etc)
-cv_organ CV filter organs ('no_pref','ln', 'lv','sp')
-p , -pvalue p-value lower threshold
-c , -cormeth correction method
(HOLM_BONFERRONI,BENJAMINI_HOCHBERG,BONFERRONI)
-o , -outfile output file in JSON format
-fclim FCLIM specify single fold change threshold
-circos_dir directory to store circos files, please use absolute path
--gene_count normalized score by gene_count
--logscale perform log scale on FC or expression
--go perform GO (gene ontology) analysis for every cell type in
sample
--verbose verbose output
It assumes that Circos is already installed in your main path. Typical use looks like this in Bash script:
1 2 3 4 5 6 7 8 9 10 11 12 13 | INFILE=input_type1_degs.tsv
CIRCOS_DIR=your_circos_dir
CIRCOS_CONF=//anaconda/lib/python2.7/site-packages/icepop/circos_conf/
icepop_degs_circos_uniform $INFILE \
--go \
-fclim 2 \
-cv_organ sp \
-circos_dir $CIRCOS_DIR
cd $CIRCOS_DIR
cp -r $CIRCOS_CONF .
circos -param random_string='image' -conf ./etc/circos-medium.conf
|
Gene clustering and GO enrichment¶
Given a differentially expressed genes, this script perform gene clustering and calculate gene ontology (GO) enrichment.
$ ../../icepop/scripts/go_degs_cluster -h
usage: go_degs_cluster [-h] [-s] [-k] [-m] [-d] [-g] [-p] [-c] [-o] [--immune]
[filename]
GO enrichment for clustered DEGs.
positional arguments:
filename DEGs file in TSV, CSV or Excel format
optional arguments:
-h, --help show this help message and exit
-s , -species species (mouse, human)
-k number of clusters
-m , -method clustering method (complete, average, ward)
-d , -distance distance measure (euclidean, manhattan, pearsond)
-g , -organs organs ('no_pref','bone_marrow', etc)
-p , -pvalue p-value lower threshold
-c , -cormeth correction method
(HOLM_BONFERRONI,BENJAMINI_HOCHBERG,BONFERRONI)
-o , -outfile output file in JSON format
--immune only show immune GO terms
Cell population score for gene clusters¶
This script perform gene clustering and calculate cell population score for each cluster.
$ ../../icepop/scripts/icepop_degs_cluster -h
usage: icepop_degs_cluster [-h] [-s] [-k] [-m] [-d] [-g] [-o] [--gene_count]
[--logscale]
[filename]
Cell population score for clustered DEGs.
positional arguments:
filename DEGs file
optional arguments:
-h, --help show this help message and exit
-s , -species species (mouse, human)
-k number of clusters
-m , -method clustering method (complete, average, ward)
-d , -distance distance measure (euclidean, manhattan, pearsond)
-g , -organs organs ('no_pref','bone_marrow', etc)
-o , -outfile output file in JSON format
--gene_count normalized score by gene_count
--logscale perform log scale on FC or expression