Yes the ChIP is from my data! Would you say the data for genotype Y is okay?
I recently performed a p300 ChIP-seq on two different genotypes.
I aligned my reads using STAR aligner, and made UCSC .bedGraph files that I loaded on IGV viewer. I noticed that the reads for one of my genotypes - genotypeX (red - combined replicates; purple and pink - individual replicates) look very blocky. The reads for the other genotype - genotype Y (black - combined replicates; green, blue - individual replicates) look better!?
Hnrnpa0 is a known target of p300 which is why I chose it as an example.
What could be the reason why the reads look 'blocky'?
How can I troubleshoot this?
Could it be due to duplications or just very bad ChIP?
I attempted to run samtools markdup. I had the following line of commands set up for one my genotype replicates:
Convert my sam files to bam format:
samtools view -b genotypeX_R1.sam > genotypeX_R1.bam
Then I followed the samtools markdup steps as follows:
samtools sort genotypeX_R1.bam -o sorted_genotypeX_R1.bamsamtools index sorted_genotypeX_R1.bamsamtools markdup -r sorted_genotypeX_R1.bam marked_duplicates_genotypeX_R1.bamsamtools flagstat marked_duplicates_genotypeX_R1.bam
Are these the right set of commands to use to mark up duplicates in my files?
I was introduced to bioinformatics recently and am still struggling to figure out/trouble shoot errors that come up in my analysis workflow. 80% of the time I have no idea how to approach or what I am doing to solve any issues with my data. :(
Thank you so much for your time and help! Appreciate it!
2 answers
If this screenshot is representative for the dataset then it means that the ChIP failed, as there is no peaks and just noise. Call peaks with macs2, a failed ChIP will manifest in very few to no peaks.
No, from this screenshot it all looks like pure noise.
it is ChIP-seq data, you should use a DNA aligner. STAR is for RNA-seq which aligns the reads to the transcriptome rather than the genome.
STAR aligns to the genome, with a GTF to guide splicing if wanted (during indexing). There is nothing intrinsically wrong with this here if the index was built without a GTF, despite bowtie2 or bwa are more typical choices for these data indeed. @OP you can try another aligner such as bowtie2 to be sure though.
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