可变多聚腺苷酸化（Alternative polyadenylation）

workflow

Background

Alternative polyadenylation (APA) leading to the production of two mRNA isoforms with different 3ʹ untranslated regions (3ʹ UTRs)The dynamic usage of the 3’untranslated region (3’UTR) resulting from alternative polyadenylation (APA) is emerging as a pervasive mechanism for regulating mRNA diversity, stability and translation.

Data Processing

DaPars

step1. Generate region annotation: python DaPars_Extract_Anno.py -b gene.bed -s symbol_map.txt -o extracted_3UTR.bed

DaPars will use the extracted distal polyadenylation sites to infer the proximal polyadenylation sites based on the alignment wiggle files of two samples. The output in this step will be used by the next step.

python DaPars_Extract_Anno.py -b hg19_refseq_whole_gene.bed -s hg19_4_19_2012_Refseq_id_from_UCSC.txt -o hg19_refseq_extracted_3UTR.bed

input

hg19_refseq_whole_gene.bed (bed12 format)

chr1	66999824	67210768	NM_032291	0	+	67000041	67208778	25	227,64,25,72,57,55,176,12,12,25,52,86,93,75,501,128,127,60,112,156,133,203,65,165,2013,	0,91705,98928,101802,105635,108668,109402,126371,133388,136853,137802,139139,142862,145536,147727,155006,156048,161292,185152,195122,199606,205193,206516,207130,208931,
chr1	33546713	33585995	NM_052998	0	+	33547850	33585783	12	182,121,212,177,174,173,135,166,163,113,215,351,	0,275,488,1065,2841,10937,12169,13435,15594,16954,36789,38931,
chr1	16767166	16786584	NM_001145278	0	+	16767256	16785385	104,101,105,82,109,178,76,1248,	0,2960,7198,7388,8421,11166,15146,18170,

hg19_4_19_2012_Refseq_id_from_UCSC.txt

#name	name2
NM_032291	SGIP1
NM_052998	ADC

output

hg19_refseq_extracted_3UTR.bed

chr14	50792327	50792946	NM_001003805|ATP5S|chr14|+	0	+
chr9	95473645	95477745	NM_001003800|BICD2|chr9|-	0	-
chr11	92623657	92629635	NM_001008781|FAT3|chr11|+	0	+

step2. Main function to get final result

python DaPars_main.py configure_file

Run this function to get the final result. The configure file is the only parameter for DaPars_main.py, which stores all the parameters.

input

configure_file

The format of the configure is:

#The following file is the result of step 1.

Annotated_3UTR=hg19_refseq_extracted_3UTR.bed

#A comma-separated list of BedGraph files of samples from condition 1

Group1_Tophat_aligned_Wig=Condition_A_chrX.wig
#Group1_Tophat_aligned_Wig=Condition_A_chrX_r1.wig,Condition_A_chrX_r2.wig if multiple files in one group

#A comma-separated list of BedGraph files of samples from condition 2

Group2_Tophat_aligned_Wig=Condition_B_chrX.wig

Output_directory=DaPars_Test_data/

Output_result_file=DaPars_Test_data

#At least how many samples passing the coverage threshold in two conditions
Num_least_in_group1=1

Num_least_in_group2=1

Coverage_cutoff=30

#Cutoff for FDR of P-values from Fisher exact test.

FDR_cutoff=0.05

PDUI_cutoff=0.5

Fold_change_cutoff=0.59

output

step3. Filter diff-APA events

FDR_cutoff, PDUI_cutoff, Fold_change_cutoff → Pass filer (Y nor N)

training_class