Crates.io | seq_geom_xform |
lib.rs | seq_geom_xform |
version | 0.4.0 |
source | src |
created_at | 2023-02-28 03:21:31.109916 |
updated_at | 2023-04-06 05:19:43.385568 |
description | Transform/normalize complex single-cell fragment geometries into simple geometries. |
homepage | https://github.com/COMBINE-lab/seq_geom_xform |
repository | https://github.com/COMBINE-lab/seq_geom_xform |
max_upload_size | |
id | 796539 |
size | 70,795 |
This crate consists of both a library and program to aid in processing sequencing libraries with different "fragment geometries". This crate is very much under active development, and so suggestions and feedback are welcome. While we do aim to make this library and tool as general as possible, development is driven by our primary use case in supporting the most common geometries present in single-cell sequencing data.
The goal of this crate, is to consume a sequencing library and a sequence fragment geometry description specification and to then parse the library in accordance with the description. Specifically, this tool is most useful when one has a "complex" geometry (i.e. a geometry where the position or length of some sequence segment — a UMI or cellular barcode — is not fixed) and they need to transform the library into one that encodes equivalent information int a "simple" geometry (i.e. a geometry where all sequence segments are at fixed and known positions and of a precisely known length).
There has been and continues to be much work in this space (and related spaces). For example, the ReadStructures
introduced in the fgbio tools describe a similar (but distinct) grammar for conveying the structure of reads in terms of segments. As the number and complexity of sequencing protocols grew and sequences where being used in increasinly complex ways to encode technical information, methods like UMI tools
were developed, where part of their functionality consists of extracting complex barcode and UMI information from sequencing reads. A related tool is umis
, which was also developed as single-cell sequencing was growing in popularity and different technologies were being developed, and which aimed to be able to extract technical information from the reads themsevles and to place this information in an easily-parsable format in the read header or comment. Similar (though usually more restricted) functionality was also implemented directly in several of the tools developed to perform single-cell preprocessing (particularly those that aim to work over a broad range of technologies) like alevin
(and alevin-fry
), kallisto|bustools
, STARsolo
(which actually implements the ability to handle both "simple" and more "complex" geometries), zUMIs
, and UniverSC
. For more complex protocols that require optional or conditional processing of certain segements, it has not been uncommon to generate one-off scripts (as done in e.g. splitp
and the perl script that inspired it SPLITseq
). There is, then, of course, a desire to unify and simplify those parts of these descriptions and processing tasks that can be unified and simplified, and to generalize those parts that there may be a need to generalize. That desire has led to tools like fuzzysplit
— a tool for description, parsing, and extraction of general patterns from sequencing read — and ongoing work like the current tool (seq_geom_xform
) and the recent splitcode
.
The description above isn't meant to be a comprehensive accounting of all approaches or tools for this problem, but instead is meant to convey that there is a lot of work, some dedicated to this particular problem and some addressing it tangentially, that reaches back quite some time. However, if there is specific relevant work that you believe adds to description above or enhances the understanding of the history of work on this problem, please reach out and let us know.
Transform/normalize complex single-cell fragment geometries into simple geometries.
Usage: seq_xformer [OPTIONS] --geom <GEOM> --out1 <OUT1> --out2 <OUT2>
Options:
-g, --geom <GEOM> Expected input read geometry specification
-1, --read1 <READ1> read 1 files, comma delimited
-2, --read2 <READ2> read 2 files, comma delimited
-o, --out1 <OUT1> where output r1 should be written (currently uncompressed)
-w, --out2 <OUT2> where output r2 should be written (currently uncompressed)
-h, --help Print help
-V, --version Print version
The seq_xformer
program takes as input a sequence fragment geometry
description specification
and a pair of input libraries (i.e. one or more paired-end files). It will
then write the transformed sequences to the specified output files --out1
and
--out2
. These could be regular files on disk, or, if you wish, they could be
fifos
that you
have set up for some receiving program to read from. The seq_xformer
tool works
in a streaming fashion, and so read pairs will be read from the input, transformed
and directly written to the output.
The normalization of complex geometries in the context of seq_xformer
consists of
turning variable-length segments into fixed-length segments, determining the position
and content of variable position segments (most often determined by an anchor sequence),
and outputting a transformed sequence where every sequence segment is at a fixed and
known position and has a single, fixed length. Additionally, non-functional sequence
components (e.g. anchor sequences or other padding) is removed.
If an input library contains a variable-length segment (e.g. a segment that has
a minimum and maximum possible length that differ), then seq_xformer
has a
specific strategy for turning these into fixed-length segements. Specifically,
this is done by padding variable length segments so that no padded segments of
different lengths will collide. For example, suppose that we have a segment
that constitutes part of a cellular barcode, and that this segment is of some
length between 8 and 10. That is, when we see this segment, it will always have
length at least 8, and it will never have length more than 10.
In this case, seq_xformer
will transform this variable length segment in the
input into a fixed length segment of length 11 (the maximum length + 1) in the
output. This is done with the following padding strategy. If an observed
segment in the input is of the maximum length (here 10), an A
is appended
to it before it is written in the output. If an observed segment is of length
9, then AC
is appended to it. If an observed segment is of length 8, then
AAG
is appended to it. Here, you can see that, since these segments are
all padded with nucleotide strings of various length, they all end up having
a fixed length (in this case 11) in the output. Further, because observed
input segments of every distinct length have a padding sequence that differs
in the last character, then segments with a different initial lengths,
by construction, cannot collide. Currently, seq_xformer
supports segments
whose length varies by up to 4 bases. The general strategy is more scalable
(i.e. if the output length was the maximum input length + 2, then the variable
length window could be doubled, etc.). However, this length restriction is
only enforced "per-piece". So, for example, if a cellular barcode was split
across 2 separate segments, then each could have a length that varies by
up to 4 nucleotides.