Question: normalize on chip-seq data
0
gravatar for catherine12243
5.0 years ago by
United States
catherine12243120 wrote:

I have two replicates of chip-seq data. And I run bowtie and call peaks using MACS separately.

MACS2 callpeak -t R1.bam -c Input1.bam -f BAM -g dm -n macs2_R1 -s 50 --call-summits --bw 151

MACS2 callpeak -t R2.bam -c Input2.bam -f BAM -g dm -n macs2_R2 -s 50 --call-summits --bw 149

 

 

Now I want to combine them together for further analysis.

Do I need to normalize them before combine together? I put input when running MACS, I thought MACS has done normalization when calling peaks.

If I should do normalization firstly, and people always say "Normalization by sequencing depth (i.e. total read count)" or "divided by total reads". How to do this? I don't have "total reads" after running thru MACS. 

How can I do to combine these two sets of peaks?

Thank you!!

chip-seq normalization • 3.6k views
ADD COMMENTlink modified 4.8 years ago by Qi Zhao40 • written 5.0 years ago by catherine12243120

May be you are looking for algorithms like MAnorm

http://genomebiology.com/2012/13/3/r16

 

ADD REPLYlink written 5.0 years ago by Manvendra Singh2.1k

I tried to use MAnorm, but I couldn't install the pre-request packages for MAnorm : R.basic and MASS                                                                                                                                                                                   
I used: source("http://www.braju.com/R/hbLite.R")                                                                                                                                                    
                   hbLite(c("R.basic","MASS"))

ADD REPLYlink modified 5.0 years ago • written 5.0 years ago by catherine12243120

MAnorm is a good choice.

catherine12243,

R.basic package has already been deprecated; "Many of these functions have now been moved to R.utils and aroma.light." posted form http://www.braju.com/R/ .

you can install R.utils and aroma.light instead by following command:

source("http://bioconductor.org/biocLite.R")
biocLite("aroma.light") 

install.packages(c("R.oo","R.utils","MASS"))

ADD REPLYlink written 4.8 years ago by Qi Zhao40
0
gravatar for Ming Tang
5.0 years ago by
Ming Tang2.5k
Houston/MD Anderson Cancer Center
Ming Tang2.5k wrote:

1. you can call peaks separately and then use the common peaks as final peaks.

2. you can also just merge the bam files by samtools merge Best Way To Merge A Many Thousand Small Bam Files Into One Big Bam File?

and then used the merged bam file and the input bam files for calling peaks. MACS should do the depth normalization by itself.

3. you have replicates, try pepr https://code.google.com/p/pepr-chip-seq/

and mutiGPS http://mahonylab.org/software/multigps/

ADD COMMENTlink written 5.0 years ago by Ming Tang2.5k

If I just use the common peaks (your method1), is the summit height reliable?

ADD REPLYlink modified 5.0 years ago • written 5.0 years ago by catherine12243120
0
gravatar for Qi Zhao
4.8 years ago by
Qi Zhao40
China
Qi Zhao40 wrote:

MAnorm is a good choice.

catherine12243,

R.basic package has already been deprecated; "Many of these functions have now been moved to R.utils and aroma.light." posted form http://www.braju.com/R/ .

you can install R.utils and aroma.light instead by following command:

source("http://bioconductor.org/biocLite.R")
biocLite("aroma.light") 

install.packages(c("R.oo","R.utils","MASS"))

 

ADD COMMENTlink written 4.8 years ago by Qi Zhao40
Please log in to add an answer.

Help
Access

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.
Powered by Biostar version 2.3.0
Traffic: 1313 users visited in the last hour