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https://github.com/genepattern/combat_seq

Batch effect adjustment based on negative binomial regression for RNA sequencing count data. Credits: https://github.com/zhangyuqing/ComBat-seq
https://github.com/genepattern/combat_seq

batch-effects genepattern-module negative-binomial-regression rna-seq

Last synced: about 2 months ago
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Batch effect adjustment based on negative binomial regression for RNA sequencing count data. Credits: https://github.com/zhangyuqing/ComBat-seq

Host: GitHub
URL: https://github.com/genepattern/combat_seq
Owner: genepattern
License: other
Created: 2022-06-27T16:47:26.000Z (over 2 years ago)
Default Branch: develop
Last Pushed: 2024-01-05T21:48:19.000Z (12 months ago)
Last Synced: 2024-01-05T22:51:49.085Z (12 months ago)
Topics: batch-effects, genepattern-module, negative-binomial-regression, rna-seq
Language: R
Homepage:
Size: 57 MB
Stars: 0
Watchers: 5
Forks: 0
Open Issues: 0
Metadata Files:
- Readme: README.md
- License: LICENSE

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README

        # About ComBat-Seq

## Overview

ComBat-Seq is a batch effect adjustment tool for bulk RNA-seq count data. Improved model based on ComBat. 


#### Parameters

To run ComBat Seq, these inputs are used: 

  1. **input matrix (required)**

      - The input matrix is a counts matrix with dimensions gene x sample. The input counts matrix. Can be a .GCT or a .tsv (tab separated value) file. Rows should be genes, column should be samples, and the value are counts. File format documentation for GCT files: https://www.genepattern.org/file-formats-guide Some sample inputs can be found here: https://github.com/genepattern/ComBat_Seq/tree/develop/data

      - The input matrix should have corresponding sample names for the first row, and corresponding genes for the first column. 
 

##### Example input matrix:

| Name      | Sample 1 Name | Sample 2 Name | Sample 3 Name | Sample 4 Name | Sample 5 Name | ... | Sample m Name |

| ----------- | ----------- | ----------- | ----------- | ----------- | ----------- | ----------- |  ----------- | 

| Gene 1 Name     | 30       | 49       | 554       | 394      | 345     |  ... | 33|

| Gene 2 Name  | 839        | 485        | 123        | 223        | 339        |  ... | 234 |

| ... | ... | ... | ... | ... | ... | ... | ... |

| Gene n Name | 423 | 442 | 123 | 553 | 754 | ... | 22|

  2. **batch information (required)**

      - Batch information contain information on batches. It is a table that looks like the following:

      - The file can be a .CLS file contaning only batch information, or a .tsv (tab separated file) containing batch, group, and any other additional information as long as it follows the format below. 


##### Example batch information file

| Samples      | Sample 1 Name | Sample 2 Name | Sample 3 Name | Sample 4 Name | Sample 5 Name | ... | Sample m Name

| ----------- | ----------- | ----------- | ----------- | ----------- | ----------- | ----------- | ----------- |

| Batch      | 1       | 1       | 2       | 2      | 2     |  ... | 4 |

| Group   | Group 1 info        | Group 1 info        | Group 1 info        | Group 1 info        | Group 1 info        |  ... | Group 3 info |

| ... | ... | ... | ... | ... | ... | ... | ... | 





 

      

  3. covariates (optional)

      - Row names for covariates to use for this run of ComBat Seq. 

  4. **output prefix (required)**

      - Prefix for output filenames. 

#### Advanced Parameters

  5. Shrink

      - Whether to apply empirical Bayes estimation on dispersion.

  6. gene subset n

      - Number of genes to use in empirical Bayes estimation, only useful when shrink = Yes

  7. covariance matrix

      - If you wish to specify multiple biological variables. Model matrix for other covariates to include in the linear model besides batch and condition of interest.

## Documentation

  - ComBat-Seq author: Yuqing Zhang. Original GitHub Repo: https://github.com/zhangyuqing/ComBat-seq

  - Docker image used: genepattern/combat_seq:v1

## Citation

Yuqing Zhang, Giovanni Parmigiani, W Evan Johnson, ComBat-seq: batch effect adjustment for RNA-seq count data, NAR Genomics and Bioinformatics, Volume 2, Issue 3, 1 September 2020, lqaa078, https://doi.org/10.1093/nargab/lqaa078

## Contact

  - Edwin Huang: [email protected]