liguowang / spiker Goto Github PK

Dear developers, thanks for creating this very useful package.
I am encountering a problem when using your split_bam.py script.

The script runs well and it is able to output the final report.txt as well as the unsorted and sorted bams for both and human reads. For the exogenous reads it is only able to output the unsorted bam file, while the sorting step fails and the following error is prompted by samtools:

[main_samview] fail to read the header from "<SAMLPLE_NAME>_exogenous.sorted.bam".

It seems that when splitting the merged bam file something goes wrong with the compilation of the exogenous reads.

Is it possible to fix the issue?

Hi, I ran the command shown on the website:

split_bam.py --threads=8 -i Input.sorted.bam -o Input &

Then got a error message as follows:

Traceback (most recent call last):
File "/home/petitming/miniconda3/envs/python3/bin/split_bam.py", line 231, in
main()
File "/home/petitming/miniconda3/envs/python3/bin/split_bam.py", line 228, in main
divided_bam(bam_file = options.bam_file, outfile = options.out_prefix, q_cut= options.map_qual, chr_prefix= options.chr_prefix, threads = options.n_thread)
File "/home/petitming/miniconda3/envs/python3/bin/split_bam.py", line 184, in divided_bam
aligned_read.reference_id = lookup_refid(human_header, read1_chr)
File "pysam/libcalignedsegment.pyx", line 1252, in pysam.libcalignedsegment.AlignedSegment.reference_id.set
File "pysam/libcalignmentfile.pyx", line 509, in pysam.libcalignmentfile.AlignmentHeader.is_valid_tid
TypeError: an integer is required

My python version is Python 3.6.15.
Is is possible to fix the issue?
Thank you so much!

Hi,

Thanks a lot for providing such a powerful tool for us! Recently we performed CUT&Tag experiments and I wondered whether this pipeline could be used to analyze CUT&Tag data?

Hao

Hi,

Thanks for developing a great tool to analyze ChIP-seq data with spike-in. I compared the peak numbers obtained by spiker.py and MACS2, but I found that the number of peaks called by spiker.py is less than MACS2, even though I chose scale factors that were almost equal to 1. However, the lost peaks are real enrichment in IGV. My codes are listed below:

spiker.py -t S2-0_S16.bam -c ../C-Input_S13.bam -g mm --cleanup --spikeIn --csf 1.0001 --tsf 0.9999 -o ../../peaks/after_spike/S2-0_raw 2> ../../peaks/after_spike/log

macs2 callpeak -c ../C-Input_S13.rmdup.bam -t S2-0_S16.rmdup.bam -f BAM -B -g mm -n S2-0_S16 --outdir ../../peaks/ 2> macs2.log

And the peak numbers are:

• 36957 for MACS2
• 26524 for spiker

The lost peaks in igv as example:

Thank you!

I have two files, an Input.bam for control and an H3K27ac.bam for calling peaks.
My case is that only the H3K27ac.bam contains spike-in reads but Input.bam does not.
I already used split_bam.py to separate reads for H3K27ac.bam.
Can I still use spiker.py to call peaks?
If yes, what scaling factor should I set for the control file?
Thank you so much for the help!

Hi developers,

Thanks a lot for providing a powerful tool to analyze spike-in chip-seq data. In your paper, I noticed that you always use only one antibody (such as histone modification), however, recently we performed spike-in chip-seq experiment using two antibodies, one (transcription factor) for human, and the other (H2Av, drosophila-specific antibody) for drosophila. Hence, I wondered whether Spiker could be utilized to analyze our data.