text: user285: Control sample chip read stat
  56234445 + 0 in total (QC-passed reads + QC-failed reads)
  0 + 0 secondary
  0 + 0 supplementary
  0 + 0 duplicates
  55173337 + 0 mapped (98.11% : N/A)
  56234445 + 0 paired in sequencing
  28078024 + 0 read1
  28156421 + 0 read2
  53808040 + 0 properly paired (95.69% : N/A)
  54626508 + 0 with itself and mate mapped
  546829 + 0 singletons (0.97% : N/A)
  162718 + 0 with mate mapped to a different chr
  112602 + 0 with mate mapped to a different chr (mapQ>=5)
  
  IgG sample chip seq read stat
  32745255 + 0 in total (QC-passed reads + QC-failed reads)
  0 + 0 secondary
  0 + 0 supplementary
  0 + 0 duplicates
  31546173 + 0 mapped (96.34% : N/A)
  32745255 + 0 paired in sequencing
  16362391 + 0 read1
  16382864 + 0 read2
  30934194 + 0 properly paired (94.47% : N/A)
  31269484 + 0 with itself and mate mapped
  276689 + 0 singletons (0.84% : N/A)
  79786 + 0 with mate mapped to a different chr
  49658 + 0 with mate mapped to a different chr (mapQ>=5)
  
  knockout sample Rep 1 stat
  28044731 + 0 in total (QC-passed reads + QC-failed reads)
  0 + 0 secondary
  0 + 0 supplementary
  0 + 0 duplicates
  27459222 + 0 mapped (97.91% : N/A)
  28044731 + 0 paired in sequencing
  14014483 + 0 read1
  14030248 + 0 read2
  26685254 + 0 properly paired (95.15% : N/A)
  27162846 + 0 with itself and mate mapped
  296376 + 0 singletons (1.06% : N/A)
  116684 + 0 with mate mapped to a different chr
  88965 + 0 with mate mapped to a different chr (mapQ>=5)
  
  Knockout sample rep 2 stat
  32410094 + 0 in total (QC-passed reads + QC-failed reads)
  0 + 0 secondary
  0 + 0 supplementary
  0 + 0 duplicates
  31774629 + 0 mapped (98.04% : N/A)
  32410094 + 0 paired in sequencing
  16196814 + 0 read1
  16213280 + 0 read2
  30802808 + 0 properly paired (95.04% : N/A)
  31561218 + 0 with itself and mate mapped
  213411 + 0 singletons (0.66% : N/A)
  89688 + 0 with mate mapped to a different chr
  63838 + 0 with mate mapped to a different chr (mapQ>=5)
  
  Do i need to down-sample with respect to the IgG for control sample which has lot more reads at the same time Knockout sample 1 has less read. So is it good to go for further analysis or i need to down sample them ?
  Any suggestion is really appreciated
  
  user-1: No, downsampling in general has no use as it reduces power. Peak callers such as macs2 will internally scale data to account for sequencing depth differences.
  The IgG itself is only useful for peak calling as it somewhat corrects for the unspecificity of the antibody to precipitate any kind of protein rather than the protein of interest. I hear people say, and personally agree with this by experience with my own experiments, that of course IgG pulls down notably fewer DNA that the target antibody, therefore the library requires notably PCR to produce enough material for sequencing. And this then makes it questionable how representative IgG is as a control. I personally prefer chromatin input to account for the intrinsic sequence/GC bias of the underlying genomic region in the sequencing/mapping. To my knowledge there are currently few established tools to really take these controls into account for downstream analysis such as differential testing via interaction terms because the library composition is simply so different from the IPs making normalization difficult.
  Your focus imho should be rather to properly normalize your samples to correct for differences is signal/noise ratio, see for example my post over at biostars on how one could do that beyond naive per-million scaling.
  
original_text: 285: <p><strong>Control sample chip read stat</strong></p>
  <pre><code>56234445 + 0 in total (QC-passed reads + QC-failed reads)
  0 + 0 secondary
  0 + 0 supplementary
  0 + 0 duplicates
  55173337 + 0 mapped (98.11% : N/A)
  56234445 + 0 paired in sequencing
  28078024 + 0 read1
  28156421 + 0 read2
  53808040 + 0 properly paired (95.69% : N/A)
  54626508 + 0 with itself and mate mapped
  546829 + 0 singletons (0.97% : N/A)
  162718 + 0 with mate mapped to a different chr
  112602 + 0 with mate mapped to a different chr (mapQ&gt;=5)
  </code></pre>
  <p><strong>IgG sample chip seq read stat</strong></p>
  <pre><code>32745255 + 0 in total (QC-passed reads + QC-failed reads)
  0 + 0 secondary
  0 + 0 supplementary
  0 + 0 duplicates
  31546173 + 0 mapped (96.34% : N/A)
  32745255 + 0 paired in sequencing
  16362391 + 0 read1
  16382864 + 0 read2
  30934194 + 0 properly paired (94.47% : N/A)
  31269484 + 0 with itself and mate mapped
  276689 + 0 singletons (0.84% : N/A)
  79786 + 0 with mate mapped to a different chr
  49658 + 0 with mate mapped to a different chr (mapQ&gt;=5)
  </code></pre>
  <p><strong>knockout sample Rep 1 stat</strong></p>
  <pre><code>28044731 + 0 in total (QC-passed reads + QC-failed reads)
  0 + 0 secondary
  0 + 0 supplementary
  0 + 0 duplicates
  27459222 + 0 mapped (97.91% : N/A)
  28044731 + 0 paired in sequencing
  14014483 + 0 read1
  14030248 + 0 read2
  26685254 + 0 properly paired (95.15% : N/A)
  27162846 + 0 with itself and mate mapped
  296376 + 0 singletons (1.06% : N/A)
  116684 + 0 with mate mapped to a different chr
  88965 + 0 with mate mapped to a different chr (mapQ&gt;=5)
  </code></pre>
  <p><strong>Knockout sample rep 2 stat</strong></p>
  <pre><code>32410094 + 0 in total (QC-passed reads + QC-failed reads)
  0 + 0 secondary
  0 + 0 supplementary
  0 + 0 duplicates
  31774629 + 0 mapped (98.04% : N/A)
  32410094 + 0 paired in sequencing
  16196814 + 0 read1
  16213280 + 0 read2
  30802808 + 0 properly paired (95.04% : N/A)
  31561218 + 0 with itself and mate mapped
  213411 + 0 singletons (0.66% : N/A)
  89688 + 0 with mate mapped to a different chr
  63838 + 0 with mate mapped to a different chr (mapQ&gt;=5)
  </code></pre>
  <p>Do i need to down-sample with respect to the IgG for control sample which has lot more reads at the same time Knockout sample 1 has less read. So is it good to go for further analysis or i need to down sample them ?</p>
  <p>Any suggestion is really appreciated</p>
   -1: <p>No, downsampling in general has no use as it reduces power. Peak callers such as <code>macs2</code> will internally scale data to account for sequencing depth differences.</p>
  <p>The IgG itself is only useful for peak calling as it somewhat corrects for the unspecificity of the antibody to precipitate any kind of protein rather than the protein of interest. I hear people say, and personally agree with this by experience with my own experiments, that of course IgG pulls down notably fewer DNA that the target antibody, therefore the library requires notably PCR to produce enough material for sequencing. And this then makes it questionable how representative IgG is as a control. I personally prefer chromatin input to account for the intrinsic sequence/GC bias of the underlying genomic region in the sequencing/mapping. To my knowledge there are currently few established tools to really take these controls into account for downstream analysis such as differential testing via interaction terms because the library composition is simply so different from the IPs making normalization difficult.</p>
  <p>Your focus imho should be rather to properly normalize your samples to correct for differences is signal/noise ratio, see for example <a href="https://www.biostars.org/p/413626/#414440" rel="nofollow noreferrer">my post over at biostars</a> on how one could do that beyond naive per-million scaling.</p>
  