Given any count table, run DESEQ2¶
usage: run_DESEQ2.py [-h] -f INPUT_TSV -s SAMPLE_NAMES -t TREATMENT -c CONTROL [-o OUTPUT] [--count_cutoff COUNT_CUTOFF]
[--N_sample_cutoff N_SAMPLE_CUTOFF]
optional arguments:
-h, --help show this help message and exit
-o OUTPUT, --output OUTPUT
output prefix (default: auto)
--count_cutoff COUNT_CUTOFF
usually it's better for prefilter out some low-count genes/peaks (default: 0)
--N_sample_cutoff N_SAMPLE_CUTOFF
usually it's better for prefilter out some low-count genes/peaks (default: 0)
required named arguments:
-f INPUT_TSV, --input_tsv INPUT_TSV
count table, each row is a feature, each column is a sample (default: None)
-s SAMPLE_NAMES, --sample_names SAMPLE_NAMES
2 column tsv, first column, sample name matched to input_tsv column names, second column is the group
name (default: None)
-t TREATMENT, --treatment TREATMENT
treatment group name, must match group names specified in sample_names (default: None)
-c CONTROL, --control CONTROL
control group name, must match group names specified in sample_names (default: None)
Summary¶
This program performs differential analysis given a user provided count table.
Usage¶
hpcf_interactive
module load conda3
source activate /home/yli11/.conda/envs/captureC
run_DESEQ2.py -f DESEQ2.input.tsv -s samples.tsv -t HBBP1_VHL -c HBBP1_NT
Input¶
Count table: DESEQ2.input.tsv¶
each row is a feature, each column is a sample.
sample names mapping: samples.tsv¶
CaptureC_NT_BGLT3_r1_S27 BGLT3_NT
CaptureC_VHL_BGLT3_r1_S29 BGLT3_VHL
CaptureC_NT_BGLT3_r2_S28 BGLT3_NT
CaptureC_VHL_BGLT3_r2_S30 BGLT3_VHL
CaptureC_NT_HBBP1_r1_S31 HBBP1_NT
First column is sample name, must match column names in count table
Second column is group name
Output¶
Output name by default is treatment.vs.control, folder is created, and DESEQ2 raw count, norm count, stats are put as, treatment.vs.control.deseq2_result.tsv
. Examples shown below
HBBP1_VHL.vs.HBBP1_NT.plotDispEsts.pdf HBBP1_VHL.vs.HBBP1_NT.R
HBBP1_VHL.vs.HBBP1_NT.cooks_distance.pdf HBBP1_VHL.vs.HBBP1_NT.plotMA.pdf
HBBP1_VHL.vs.HBBP1_NT.deseq2_result.tsv HBBP1_VHL.vs.HBBP1_NT.pvalue_hist.pdf
Convert deseq2 result to bw files for visualization¶
bdg_to_bw.py -f HBBP1.deseq2_result.tsv --data_frame -j HBBP1_bw_files
bdg_to_bw.py -f BGLT3.deseq2_result.tsv --data_frame -j BGLT3_bw_files