processAmplicons {edgeR} | R Documentation

## Process raw fastq data from pooled genetic sequencing screens

### Description

Given a list of sample-specific index (barcode) sequences and hairpin/sgRNA-specific sequences from an amplicon sequencing screen, generate a DGEList of counts from the raw fastq file/(s) containing the sequence reads. The position of the index sequences and hairpin/sgRNA sequences is considered variable, with the hairpin/sgRNA sequences assumed to be located after the index sequences in the read.

### Usage

    processAmplicons(readfile, readfile2=NULL, barcodefile, hairpinfile,
                        allowMismatch=FALSE, barcodeMismatchBase=1,
                        hairpinMismatchBase=2, dualIndexForwardRead=FALSE,
                        verbose=FALSE, barcodesInHeader=FALSE,
                        plotPositions=FALSE)

### Arguments

`readfile` | character vector giving one or more fastq filenames
`readfile2` | character vector giving one or more fastq filenames for reverse read, default to NULL
`barcodefile` | filename containing sample-specific barcode ids and sequences
`hairpinfile` | filename containing hairpin/sgRNA-specific ids and sequences
`allowMismatch` | logical, indicates whether sequence mismatch is allowed
`barcodeMismatchBase` | numeric value of maximum number of base sequence mismatches allowed in a barcode sequence when `allowMismatch` is `TRUE`
`hairpinMismatchBase` | numeric value of maximum number of base sequence mismatches allowed in a hairpin/sgRNA sequence when `allowMismatch` is `TRUE`
`dualIndexForwardRead` | logical, indicates if forward reads contains a second barcode sequence (must be present in `barcodefile`) which should be matched
`verbose` | if `TRUE`, output program progress
`barcodesInHeader` | logical, indicates if barcode sequences should be matched in the header (sequence identifier) of each read (i.e. the first of every group of four lines in the fastq files)
`plotPositions` | logical, indicates if a density plot displaying the position of each barcode and hairpin/sgRNA sequence in the reads should be created. If `dualIndexForwardRead` is `TRUE` or `readfile2` is not `NULL`, plotPositions will generate two density plots, side by side, indicating the positions of the first barcodes and hairpins in the first plot, and second barcodes in the second.

### Details

The `processAmplicons` function allows for hairpins/sgRNAs/sample index sequences to be in variable positions within each read.

The input barcode file and hairpin/sgRNA files are tab-separated text files with at least two columns (named 'ID' and 'Sequences') containing the sample or hairpin/sgRNA ids and a second column indicating the sample index or hairpin/sgRNA sequences to be matched. If `dualIndexForwardRead` is `TRUE`, a third column 'Sequences2' is expected in the barcode file. If `readfile2` is specified, another column 'SequencesReverse' is expected in the barcode file. The barcode file may also contain a 'group' column that indicates which experimental group a sample belongs to. Additional columns in each file will be included in the respective `$samples` or `$genes` data.frames of the final codeDGEList object. These files, along with the fastq file/(s) are assumed to be in the current working directory.

To compute the count matrix, matching to the given barcodes and hairpins/sgRNAs is conducted in two rounds. The first round looks for an exact sequence match for the given barcode sequences and hairpin/sgRNA sequences through the entire read, returning the first match found. If a match isn't found, the program performs a second round of matching which allows for sequence mismatches if `allowMismatch` is set to `TRUE`. The maximum number of mismatch bases in barcode and hairpin/sgRNA are specified by the parameters `barcodeMismatchBase` and `hairpinMismatchBase` respectively.

The program outputs a `DGEList` object, with a count matrix indicating the number of times each barcode and hairpin/sgRNA combination could be matched in reads from input fastq file(s).

For further examples and data, refer to the case studies available from http://bioinf.wehi.edu.au/shRNAseq.

### Value

Returns a `DGEList` object with following components:

`counts` | read count matrix tallying up the number of reads with particular barcode and hairpin/sgRNA matches. Each row is a hairpin/sgRNA and each column is a sample
`genes` | In this case, hairpin/sgRNA-specific information (ID, sequences, corresponding target gene) may be recorded in this data.frame
`lib.size` | auto-calculated column sum of the counts matrix

### Note

This function replaced the earlier function `processHairpinReads` in edgeR 3.7.17.

This function replaces the previous `processAmplicons` function, which expected the sequences in the fastq files to have a fixed structure (as per Figure 1A of Dai et al., 2014). This function can be used, and is intended for, reads where hairpins/sgRNAs/sample index sequences can be in variable positions within each read. When `plotPositions=TRUE` a density plot of the match positions is created to allow the user to assess whether they occur in the expected postions.

### Author(s)

Oliver Voogd, Zhiyin Dai, Shian Su and Matthew Ritchie

### References

Dai Z, Sheridan JM, Gearing, LJ, Moore, DL, Su, S, Wormald, S, Wilcox, S, O'Connor, L, Dickins, RA, Blewitt, ME, Ritchie, ME(2014). edgeR: a versatile tool for the analysis of shRNA-seq and CRISPR-Cas9 genetic screens. F1000Research 3, 95. http://f1000research.com/articles/3-95

[Package edgeR version 3.36.0 Index]