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:

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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