Cell Ranger7.1 (latest), printed on 05/28/2023
Cell Ranger provides pre-built human, mouse, and barnyard (human & mouse) reference packages for read alignment and gene expression quantification in cellranger count. Build notes are available here.
Cell Ranger allows users to create a custom reference package using cellranger mkref. To make a custom reference, you will need a reference genome sequence (FASTA file) and gene annotations (GTF file). A tutorial, Build a Custom Reference (cellranger mkref), is available to walk you through the steps.
Custom references built with previous versions of cellranger mkref can be used with the latest versions of cellranger count or cellranger multi. However, references built with the latest cellranger mkref may not be compatible with all older versions of the pipelines.
Cell Ranger supports the use of customer-generated references under the following conditions:
Example use cases:
To create a custom reference:
GTF files downloaded from sites like ENSEMBL and UCSC often contain transcripts
and genes which need to be filtered from your final annotation. Cell Ranger
provides mkgtf, a simple utility to filter genes based on their key-value
pairs in the GTF attribute column. The command syntax requires input and output GTF file names and
--attribute values specifying gene biotypes to filter from the GTF file (replace values in red):
cellranger mkgtf input.gtf output.gtf --attribute=key:allowable_value
In the command above, the
allowable_value can be any of the accepted biotypes listed below:
For example, the following filtering was applied to generate the GTF file for the GRCh38 Cell Ranger reference package:
cellranger mkgtf Homo_sapiens.GRCh38.ensembl.gtf Homo_sapiens.GRCh38.ensembl.filtered.gtf \ --attribute=gene_biotype:protein_coding \ --attribute=gene_biotype:lncRNA \ --attribute=gene_biotype:antisense \ --attribute=gene_biotype:IG_LV_gene \ --attribute=gene_biotype:IG_V_gene \ --attribute=gene_biotype:IG_V_pseudogene \ --attribute=gene_biotype:IG_D_gene \ --attribute=gene_biotype:IG_J_gene \ --attribute=gene_biotype:IG_J_pseudogene \ --attribute=gene_biotype:IG_C_gene \ --attribute=gene_biotype:IG_C_pseudogene \ --attribute=gene_biotype:TR_V_gene \ --attribute=gene_biotype:TR_V_pseudogene \ --attribute=gene_biotype:TR_D_gene \ --attribute=gene_biotype:TR_J_gene \ --attribute=gene_biotype:TR_J_pseudogene \ --attribute=gene_biotype:TR_C_gene
This generated a filtered GTF file
Homo_sapiens.GRCh38.ensembl.filtered.gtf from the original
unfiltered GTF file
Homo_sapiens.GRCh38.ensembl.gtf. In the output
file, other biotypes such as
gene_biotype:pseudogene are excluded
from the GTF annotation.
To create custom references, use the cellranger mkref command,
passing it one or more matching sets of FASTA and GTF files. This utility copies
your FASTA and GTF, indexes these in several formats, and outputs a folder with
the name you pass to
--genome. Input GTF files are typically
filtered with mkgtf prior to mkref.
|Required. Unique genome name(s), used to name output folder. Should contain only alphanumeric characters and optionally period, hyphen, and underscore characters [a-zA-Z0-9_-]+. Specify multiple genomes by specifying the |
|Required. Path(s) to FASTA file containing your genome reference.
Specify multiple genomes by specifying the |
|Required. Path(s) to GTF file(s) containing annotated genes for your
genome reference. Specify multiple genomes with
|Optional. Maximum memory (GB) used during STAR genome index generation. Defaults to 16. Please note, the amount of memory specified must be greater than the number of gigabases in the input reference FASTA file.|
|Optional. Reference version string to include with reference.|
|Optional. Number of threads used during STAR genome index generation. Defaults to 1.|
|Optional. Show list of all arguments and options.|
|Optional. Show version.|
cellranger mkref --genome=output_genome --fasta=input.fa --genes=input.gtf
Indexing a typical human 3Gb FASTA file often takes up to 8 core hours and requires 32 GB of memory.
A successful mkref run should conclude with a message similar to this:
Creating new reference folder at output_genome ...done Writing genome FASTA file into reference folder... ...done Computing hash of genome FASTA file... ...done Writing genes GTF file into reference folder... WARNING: The following transcripts appear on multiple chromosomes in the GTF: This can indicate a problem with the reference or annotations. Only the first chromosome will be counted. ...done Computing hash of genes GTF file... ...done Writing genes index file into reference folder (may take over 10 minutes for a 3Gb genome)... ...done Writing genome metadata JSON file into reference folder... ...done Generating STAR genome index (may take over 8 core hours for a 3Gb genome)... ...done. >>> Reference successfully created! <<<
── output_genome ├── fasta │ ├── genome.fa │ └── genome.fa.fai ├── genes │ └── genes.gtf.gz ├── reference.json └── star ├── chrLength.txt ├── chrNameLength.txt ├── chrName.txt ├── chrStart.txt ├── exonGeTrInfo.tab ├── exonInfo.tab ├── geneInfo.tab ├── Genome ├── genomeParameters.txt ├── SA ├── SAindex ├── sjdbInfo.txt ├── sjdbList.fromGTF.out.tab ├── sjdbList.out.tab └── transcriptInfo.tab
The most common use case is to create a reference for only one species. In this case, there is one set of matched FASTA and GTF files typically obtained from Ensembl, NCBI, or UCSC.
cellranger mkref --genome=GRCh38 --fasta=GRCh38.fa --genes=GRCh38-filtered-ensembl.gtf
When possible, please obtain genome sequence (FASTA) and gene annotations (GTF) from the same source: Use Ensembl FASTA files with Ensembl GTF files. Chromosome or sequence names in the FASTA file must match the chromosome or sequence names in the GTF file.
As noted in the STAR manual, the most comprehensive genome sequence and annotations are recommended:
To create a reference for multiple species, run the mkref command
with multiple FASTA and GTF files. This is similar to the single species case
above, but note that the order of the arguments matters. The arguments are
grouped by the order they appear; for instance, the first
option listed corresponds to the first
--genes options listed. Please use or create this type of reference
when analyzing barnyard validation experiments for estimating multiplet rates.
cellranger mkref --genome=GRCh38 --fasta=GRCh38.fa --genes=GRCh38-filtered-ensembl.gtf \ --genome=mm10 --fasta=mm10.fa --genes=mm10-filtered-ensembl.gtf
Provided that you follow the format described above, it is fairly simple to add
custom gene definitions to an existing reference. First, add the additional
FASTA sequence records to the
fasta/genome.fa file. Next, update the GTF file,
genes/genes.gtf, with the gene annotation record(s). An example is described in the cellranger mkref tutorial for adding a marker gene to the FASTA and GTF files.
Depending on your experimental set-up, consider including UTR sequence, and in particular the 3' UTR, to the marker gene. Since 10x Genomics gene expression assays capture transcripts by poly-A and 3' gene expression assays utilize the 3' ends of transcripts to create sequencing library inserts, reads are expected to align towards the 3' end of a transcript, including into the UTR.|
If the UTR sequence is not unique (i.e., recapitulates a sequence in another transcript), it should be included to discount all reads aligning to it and the other locus. Otherwise, in this scenario, the counts at the other locus could be artificially inflated, while reducing counts for the marker gene (more information here).
The GTF file format is essentially a list of records, one per line, each comprising nine tab-delimited non-empty fields.
|1||Chromosome||Must refer to a chromosome/contig in the genome fasta.|
|3||Feature||cellranger count only uses rows where this line is
|4||Start||Start position on the reference (1-based inclusive).|
|5||End||End position on the reference (1-based inclusive).|
|7||Strand||Strandedness of this feature on the reference:
|9||Attributes||A semicolon-delimited list of key-value pairs of the form
After adding the necessary records to your FASTA file and the additional lines to your GTF file, run cellranger mkref as normal.
The single-nuclei RNA-seq assay captures unspliced pre-mRNA as well as mature
mRNA. However, after
cellranger count only counts reads aligned to exons. Since the pre-mRNA will generate intronic reads, it may be useful to count these reads as well. Previously, it was recommended to create a custom “pre-mRNA” reference package, listing each gene transcript locus as an exon, in order to count intronic reads. In Cell Ranger 5.0, there is a new
include-introns option for counting intronic reads that should be used instead, and the usage of pre-mRNA references is deprecated.
A read may align to multiple transcripts and genes, but Cell Ranger only considers a read confidently mapped to the transcriptome if it is mapped to a single gene (after converting the
xf tag value to binary, 1-bit means the read is confidently mapped to the transcriptome).
To assess whether reads mapped to multiple genes, examine the
GN tags in the output BAM file, which are generated by Cell Ranger after alignment with STAR. Uniquely mapped reads will have one gene ID for
GX and one gene name for
GN , while multi-mapped reads will list multiple gene IDs and names.