> For the complete documentation index, see [llms.txt](https://help.bioinsight.illumina.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://help.bioinsight.illumina.com/correlation-engine/reference/faq/basespace-chip-seq.md).

# BaseSpace ChIP-Seq Output Conversion to Bioset

This guide explains how to transform the output of the BaseSpace Sequence Hub ChIP-Seq application into bioset files for import into Correlation Engine.

Two output files can be used, depending on the experiment type:

* **Histone binding experiments** — use `ChIP-Seq_peaks.xls`
* **Transcription factor binding experiments** — use `ChIP-Seq_peaks.narrowPeak`

![](https://1165879419-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FWolK2fDgPCCcGurM8A73%2Fuploads%2Fgit-blob-1a5291a465ef684eeb5d9cc24a91d4772ffc73c2%2F0%20\(3\).png?alt=media)

***

## Histone Binding

### Source File

`ChIP-Seq_peaks.xls` contains a header area offset with `#` characters and a data section with the following columns. Rename and extract as indicated:

| Original Header   | Renamed Header    |
| ----------------- | ----------------- |
| `chr`             | `chr`             |
| `start`           | `start`           |
| `end`             | `end`             |
| `=-LOG10(pvalue)` | `p-value`         |
| `fold_enrichment` | `Enrichment fold` |
| `=-LOG10(qvalue)` | `q-value`         |

Columns `length`, `abs_summit`, `pileup`, and `name` are not needed.

### Transform p-values and q-values

The p-value and q-value columns contain `-log₁₀` transformed values. Multiply by -1 and un-log (10^x) to recover original values:

```
p-value = 10^(-1 × -LOG10(pvalue_column))
```

### Add Header Information

Add a free-text header to the top of the file:

```
Bioset summary = <study title>
Bioset description = <test group> + <ChIP target> ChIP vs. input
Organism = <species>
Data pre-processing = FASTQ files were downloaded from SRA. No other preprocessing was performed.
Analysis summary = ChIP-Seq identification using BaseSpace ChIPSeq v1.0.2. Aligned to <genome> using BWA, processed with MACS2. Parameter settings: [Fragment size = 200, Q-value cutoff = 0.01, Fold enrichment = 10,30, Sample normalization = Down Sample].
Test group = <test group name> (total replicates = N)
Control group = <control group name> (total replicates = N)
Platform(s) = <genome build>
Internal ID - <GSE number>_<number>
```

Q-value cut-offs are applied during ChIP-Seq processing (typically q < 0.01). No additional cutoffs are needed before upload.

### Example Bioset Data

![](https://1165879419-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FWolK2fDgPCCcGurM8A73%2Fuploads%2Fgit-blob-9518dee6621ff3ef39824af8800742310b371a19%2F1%20\(1\).png?alt=media)

| chr   | start    | end      | Enrichment fold | q-value  | p-value   |
| ----- | -------- | -------- | --------------- | -------- | --------- |
| chr7  | 4681591  | 4681891  | 34.34           | 4.92E-97 | 3.97E-105 |
| chr17 | 61851121 | 61851429 | 28.33           | 2.10E-96 | 1.90E-104 |

***

## Transcription Factor Binding

### Source File

`ChIP-Seq_peaks.narrowPeak` contains peak calls without column headers. The column order is:

![](https://1165879419-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FWolK2fDgPCCcGurM8A73%2Fuploads%2Fgit-blob-987a4799414b6956b6555c1f168836c4f474bc5b%2F2.png?alt=media)

1. Chromosome
2. Start
3. End
4. Name
5. Integer display score
6. Strand
7. Fold change
8. –log₁₀(p-value)
9. –log₁₀(q-value)
10. Relative summit position

### Extract and Rename Columns

Bring together columns 1, 2, 3, 7, 8, 9 with these headers:

| Column | Header            |
| ------ | ----------------- |
| 1      | `chr`             |
| 2      | `start`           |
| 3      | `end`             |
| 7      | `Enrichment fold` |
| 8      | `p-value`         |
| 9      | `q-value`         |

Transform p-values and q-values from –log₁₀ to original values (multiply by -1 and un-log). Draw settings information from `ChIP-Seq_peaks.xls` for the header section. Add header information as described for histone biosets above (genome build can be found in `<SRR_ID_S#>.summary.csv` statistics files).

***

## Genome Build Lift-Over

CE annotates genomes using one target build per species. If your data was aligned to a different build, use the lift-over support available during upload. Supported lift-overs:

| Species | Accepted Builds              | Lift-Over Target |
| ------- | ---------------------------- | ---------------- |
| Human   | hg19, hg18, hg17, hg16, hg15 | hg18             |
| Mouse   | mm9, mm8, mm7, mm6, mm5      | mm9              |
| Rat     | rn4 (NCBI RGSC v3.4)         | rn4              |
| Worm    | ce6, ce4, ce2                | ce6              |
| Fly     | dm3, dm2, dm1                | dm3              |
| Yeast   | sacCer2, sacCer1             | sacCer2          |
| Monkey  | rheMac2                      | rheMac2          |
| Chicken | galGal3                      | galGal3          |
| Chimp   | panTro2                      | panTro2          |
| Cow     | bosTau4                      | bosTau4          |
| Fish    | danRer6                      | danRer6          |
| Dog     | canFam2                      | canFam2          |

***

## Import Settings

1. Select the appropriate data type (Protein-DNA Binding or Histone Modification) and species.
2. Indicate whether multiple samples were aggregated for analysis (aggregate) or single IP + input were used (single).
3. Select **Enrichment fold** as the ranking column; rank **descending**.
4. Select the original genome build used for alignment (CE will lift-over to the target build).

### Tagging Recommendations

| Tag Type  | Recommended Value                                                        |
| --------- | ------------------------------------------------------------------------ |
| Biosource | Cell line or tissue name                                                 |
| Tissue    | Anatomical tissue                                                        |
| Gene      | Antibody target gene (for TF or histone studies)                         |
| Gene Mode | `ChIP antibody target`                                                   |
| Biodesign | `Normal vs. normal`, `Disease vs. disease`, or `Treatment vs. treatment` |

{% hint style="info" %}
CE does not normally ingest protein-DNA studies with designs other than ChIP vs. input or ChIP vs. IgG.
{% endhint %}


---

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