Each tool has a set of Common options for input/output, profiling and debugging.

count - Count reads per gene from BAM using UMIs and mapping coordinates

Count the number of reads per gene based on the mapping co-ordinate and the UMI attached to the read

This tool is only designed to work with library preparation methods where the fragmentation occurs after amplification, as per most single cell RNA-Seq methods (e.g 10x, inDrop, Drop-seq, SCRB-seq and CEL-seq2). Since the precise mapping co-ordinate is not longer informative for such library preparations, it is simplified to the gene. This is a reasonable approach providing the number of available UMIs is sufficiently high and the sequencing depth is sufficiently low that the probability of two reads from the same gene having the same UMIs is acceptably low.

If you want to count reads per gene for library preparations which fragment prior to amplification (e.g bulk RNA-Seq), please use umi_tools dedup to remove the duplicate reads as this will use the full information from the mapping co-ordinate. Then use a read counting tool such as FeatureCounts or HTSeq to count the reads per gene.

In the rare case of bulk RNA-Seq using a library preparation method with fragmentation after amplification, one can still use count but note that it has not been tested on bulk RNA-Seq.

This tool deviates from group and dedup in that the --per-gene option is hardcoded on.

Extracting barcodes

It is assumed that the FASTQ files were processed with umi_tools extract before mapping and thus the UMI is the last word of the read name. e.g:

@HISEQ:87:00000000_AATT

where AATT is the UMI sequeuence.

If you have used an alternative method which does not separate the read id and UMI with a “_”, such as bcl2fastq which uses “:”, you can specify the separator with the option --umi-separator=<sep>, replacing <sep> with e.g “:”.

Alternatively, if your UMIs are encoded in a tag, you can specify this by setting the option –extract-umi-method=tag and set the tag name with the –umi-tag option. For example, if your UMIs are encoded in the ‘UM’ tag, provide the following options: --extract-umi-method=tag --umi-tag=UM

Finally, if you have used umis to extract the UMI +/- cell barcode, you can specify --extract-umi-method=umis

The start position of a read is considered to be the start of its alignment minus any soft clipped bases. A read aligned at position 500 with cigar 2S98M will be assumed to start at position 498.

--extract-umi-method

How are the barcodes encoded in the read?

Options are:

• read_id (default)

  Barcodes are contained at the end of the read separated as specified with --umi-separator option

• tag

  Barcodes contained in a tag(s), see --umi-tag/--cell-tag options

• umis

  Barcodes were extracted using umis (https://github.com/vals/umis)

--umi-separator=[SEPARATOR]

Separator between read id and UMI. See --extract-umi-method above. Default=``_``

--umi-tag=[TAG]

Tag which contains UMI. See --extract-umi-method above

--umi-tag-split=[SPLIT]

Separate the UMI in tag by SPLIT and take the first element

--umi-tag-delimiter=[DELIMITER]

Separate the UMI in by DELIMITER and concatenate the elements

--cell-tag=[TAG]

Tag which contains cell barcode. See –extract-umi-method above

--cell-tag-split=[SPLIT]

Separate the cell barcode in tag by SPLIT and take the first element

--cell-tag-delimiter=[DELIMITER]

Separate the cell barcode in by DELIMITER and concatenate the elements

UMI grouping options

--method

What method to use to identify group of reads with the same (or similar) UMI(s)?

All methods start by identifying the reads with the same mapping position.

The simplest methods, unique and percentile, group reads with the exact same UMI. The network-based methods, cluster, adjacency and directional, build networks where nodes are UMIs and edges connect UMIs with an edit distance <= threshold (usually 1). The groups of reads are then defined from the network in a method-specific manner. For all the network-based methods, each read group is equivalent to one read count for the gene.

• unique

  Reads group share the exact same UMI

• percentile

  Reads group share the exact same UMI. UMIs with counts < 1% of the median counts for UMIs at the same position are ignored.

• cluster

  Identify clusters of connected UMIs (based on hamming distance threshold). Each network is a read group

• adjacency

  Cluster UMIs as above. For each cluster, select the node (UMI) with the highest counts. Visit all nodes one edge away. If all nodes have been visited, stop. Otherwise, repeat with remaining nodes until all nodes have been visted. Each step defines a read group.

• directional (default)

  Identify clusters of connected UMIs (based on hamming distance threshold) and umi A counts >= (2* umi B counts) - 1. Each network is a read group.

--edit-distance-threshold

For the adjacency and cluster methods the threshold for the edit distance to connect two UMIs in the network can be increased. The default value of 1 works best unless the UMI is very long (>14bp).

--spliced-is-unique

Causes two reads that start in the same position on the same strand and having the same UMI to be considered unique if one is spliced and the other is not. (Uses the ‘N’ cigar operation to test for splicing).

--soft-clip-threshold

Mappers that soft clip will sometimes do so rather than mapping a spliced read if there is only a small overhang over the exon junction. By setting this option, you can treat reads with at least this many bases soft-clipped at the 3’ end as spliced. Default=4.

--multimapping-detection-method=[NH/X0/XT]

If the sam/bam contains tags to identify multimapping reads, you can specify for use when selecting the best read at a given loci. Supported tags are “NH”, “X0” and “XT”. If not specified, the read with the highest mapping quality will be selected.

--read-length

Use the read length as a criteria when deduping, for e.g sRNA-Seq.

Single-cell RNA-Seq options

--per-gene

Reads will be grouped together if they have the same gene. This is useful if your library prep generates PCR duplicates with non identical alignment positions such as CEL-Seq. Note this option is hardcoded to be on with the count command. I.e counting is always performed per-gene. Must be combined with either --gene-tag or --per-contig option.

--gene-tag

Deduplicate per gene. The gene information is encoded in the bam read tag specified

--assigned-status-tag

BAM tag which describes whether a read is assigned to a gene. Defaults to the same value as given for --gene-tag

--skip-tags-regex

Use in conjunction with the --assigned-status-tag option to skip any reads where the tag matches this regex. Default ("^[__|Unassigned]") matches anything which starts with “__” or “Unassigned”:

--per-contig

Deduplicate per contig (field 3 in BAM; RNAME). All reads with the same contig will be considered to have the same alignment position. This is useful if you have aligned to a reference transcriptome with one transcript per gene. If you have aligned to a transcriptome with more than one transcript per gene, you can supply a map between transcripts and gene using the --gene-transcript-map option

--gene-transcript-map

File mapping genes to transcripts (tab separated), e.g:

gene1   transcript1
gene1   transcript2
gene2   transcript3

--per-cell

Reads will only be grouped together if they have the same cell barcode. Can be combined with --per-gene.

SAM/BAM Options

--mapping-quality

Minimium mapping quality (MAPQ) for a read to be retained. Default is 0.

--unmapped-reads

How should unmapped reads be handled. Options are:

• discard (default)

  Discard all unmapped reads

• use

  If read2 is unmapped, deduplicate using read1 and output read1 only. Note that if read1 is unmapped, read2 will always be descarded irrepsective of whether it is mapped. WARNING: May lead to unpaired reads in output. Requires --paired

• output

  Output unmapped reads/read pairs without UMI grouping/deduplication. Only available in umi_tools group

--chimeric-pairs

How should chimeric read pairs be handled. Options are:

• discard

  Discard all chimeric read pairs

• use (default)

  Deduplicate using read1 information only. Both read1 and read2 should still be output, as long as Read2 is actaully found. Can lead to unpaired reads in output if read1 is marked as having a mapped mate, but read2 is never found.

• output

  Output chimeric read pairs without UMI grouping/deduplication. Only available in umi_tools group

--unpaired-reads

How should unpaired reads be handled. Options are:

• discard

  Discard all unpaired reads. Note: Can still lead to unpaired reads in the output if a read1 is marked as having a mapped mate, but the mate is never found.

• use (default)

  Deduplicate unpaired reads using read1 only. Note, unpaired read2s will still be discarded.

• output

  Output unpaired reads without UMI grouping/deduplication. Only available in umi_tools group

--ignore-umi

Ignore the UMI and group reads using mapping coordinates only

--subset

Only consider a fraction of the reads, chosen at random. This is useful for doing saturation analyses.

--chrom

Only consider a single chromosome. This is useful for debugging/testing purposes

--paired

BAM is paired end - output both read pairs. This will also force the use of the template length to determine reads with the same mapping coordinates.

Input/Output Format Options

The following options deal with input and output format, and are useful for outputting CRAM format. In general UMI-tools will attempt to guess the input and output formats from the file names, but thing can be over-written using the out-format and input-format options. The location of CRAM reference files will be taken from the either the an input CRAM file (if present) or from the --reference-filename option. Otherwise the reference will be embedded in the file.

--in-format=IN_FORMAT

File format of the input file. Format is usually implied from the extension of the filename, but maybe overridden with this option. Default=bam

--input-options=INPUT_OPTIONS

Format string provided to htslib for reading. Mostly useful for CRAM formatted files. See samtools documentation

--in-sam

[DEPRECATED] USE --in-format . By default, inputs are assumed to be in BAM format. Use this option to specify the use of SAM format for input.

--reference-filename=REFERENCE_FILENAME

File path or URL to the genome reference to be used when reading or writing CRAM files. Can be a path or a URL. By default, when reading a CRAM file, the reference recorded in the input file will be used unless this is specified. URL references cannot be read from input files, however. When writing, specifying a reference location is required unless specified in input.