This is an open project that aims to provide updated and quality controlled genome coordinates for the MNEc2M chip. It contains scripts and data files related to the remapping of probe sequences.
This project is designed to be open and welcomes contributions and discussion from the community in order to develop the best product possible. The data contained herein is available under the CC-BY 4.0 license and the code is available under the MIT license. People who contribute to the project will be noted on this page and will be included on any scientific publications that directly result from this work.
To download the final EquCab3 coordinate lists for all equine SNP arrays, click here.
We are currently in the process of developing software that will remap your SNP array coordinates for you. In the meantime, the Python script MNEc2to3.py is included here. It uses the remap tables from the link above to update SNP coordinates and handles strand flips and translocations for VCF files only. For detailed usage instructions, run the following command:
python3 MNEc2to3.py --help
As described in a previous publication, the equine community banded together to develop a high density SNP chip based on variants discovered in >20 different horse breeds. The initial discovery effort found over 22 million sites that were likely polymorphic and went through several filtering steps to identify a subset of 2 million and 670K SNPs (a proper subset of the 2M) that were put on a commercially available array.
To be as exhaustive as possible, the initial SNP discovery effort included all the autosomes cataloged by EquCab2 as well as ChrX and two artificially built chromosomes we referred to as chrUn1 and chrUn2. These contained contigs that were yet unmapped as of EquCab2, many of which were successfully mapped in EquCab3. Therefore in this remapping process we are dealing with three different reference genomes:
The main focus and the primary unit of data considered here is the probe sequence that is actually being hybridized by the array. In other words, what we are mapping are the probe sequences that were put on the actual array in relation to their coordinates from EquCab2 to EquCab3. Each SNP on the chip is interrogated by the array by hybridizing a probe to genomic DNA. This probe was designed using the MNEc_Ec2 reference genome.
The simplest use case here is to extract the probe sequence used by the MNEc chip and BLAST it to the new genome build. The first
script in the scripts/ directory called 01_make_probeseq.py does just that. The script takes an input a Fasta file as well as
a VCF file containing the MNEc SNP coordinates and outputs a FASTA file containing probe sequences. The Fasta file and VCF are not
included in this project due to limitations of GitHub hosting. But the probe sequences generated from the MNEc_Ec2 reference
genome used in the array design are available in data/MNEc2M_probeseq.fa.gz.
From here, the probe sequences were BLASTED against three different reference genomes: MNEc_Ec2 (as a sanity check), EquCab2 (as
another sanity check), and EquCab3. The code used to do this is in scripts/02_do_blast.sh. Briefly, the script builds some
custom blast databases with megablast indexes and then performs a BLAST on each of the MNEc 2M probe sequences and only retains
100%matches (of the 71mer).
Again, some of the input files are
not available because of their size, but each of the blast output files can be found in data/:
data/MNEc2M.blast.EquCab2.txt.gz,data/MNEc2M.blast.EquCab3.txt.gz, and data/MNEc2M.blast.MNEc_Ec2.txt.gz. These will be the
most useful files for doing the remapping analysis and the updated probe quality control assessment.
Note: The output of the BLAST program (and the headers of the blast files above) are:
MNEc Coordinate | BLASTED Chromosome | % Identity | Blasted start | Blasted endThe final step in the workflow is performed by scripts/03_process_BLAST.py. This script borrows some annotations about the
SNPs from PonyTools and iterates over the results produced by BLAST in order to add
some information about the mapping. The results from this script are in data/MNEc2M.probe_blast_counts.csv.gz. The table looks
like:
In [135]: info.head(n=20)
Out[135]:
MNEcID AffySNPID ProbeSetID chrom pos AlleleA AlleleB REF ALT in670 legacy id MNEc_Ec2 EquCab3 EquCab2
0 MNEc.2.10.9554699.VIP Affx-101861294 AX-104415554 chr10 9554699 C G C G False True chr10.9554699 1 1 1
1 MNEc.2.10.9554699.VIP Affx-101861294 AX-103524731 chr10 9554699 C G C G False True chr10.9554699 1 1 1
2 MNEc.2.2.13074277.VIP Affx-103007064 AX-103861101 chr2 13074277 T C C T False True chr2.13074277 1 1 1
3 MNEc.2.2.13074277.VIP Affx-103007064 AX-102948897 chr2 13074277 T C C T False True chr2.13074277 1 1 1
4 MNEc.2.21.30666626.VIP Affx-102471109 AX-104189538 chr21 30666626 A G G A False True chr21.30666626 1 1 1
5 MNEc.2.21.30666626.VIP Affx-102471109 AX-104916861 chr21 30666626 A G G A False True chr21.30666626 1 1 1
6 MNEc.2.23.22999655.VIP Affx-101668032 AX-104553122 chr23 22999655 A C C A False True chr23.22999655 1 1 1
7 MNEc.2.23.22999655.VIP Affx-101668032 AX-104971885 chr23 22999655 A C C A False True chr23.22999655 1 1 1
8 MNEc.2.18.66493737.VIP Affx-102760722 AX-104041705 chr18 66493737 T C T C True True chr18.66493737 1 1 1
9 MNEc.2.18.66493737.VIP Affx-102760722 AX-103119925 chr18 66493737 T C T C True True chr18.66493737 1 1 1
10 MNEc.2.6.6431969.BIEC2-985609 Affx-101987248 AX-104524509 chr6 6431969 A G A G True True chr6.6431969 1 1 1
11 MNEc.2.6.6431969.BIEC2-985609 Affx-101987248 AX-103467496 chr6 6431969 A G A G True True chr6.6431969 1 1 1
12 MNEc.2.6.6437698.BIEC2-985637 Affx-102389295 AX-104231007 chr6 6437698 A G G A True True chr6.6437698 1 1 1
13 MNEc.2.6.6562393.BIEC2-985785 Affx-101867915 AX-104411696 chr6 6562393 A G A G True True chr6.6562393 1 1 1
14 MNEc.2.6.6562393.BIEC2-985785 Affx-101867915 AX-103521326 chr6 6562393 A G A G True True chr6.6562393 1 1 1
15 MNEc.2.6.6671817.BIEC2-985848 Affx-101434215 AX-104672882 chr6 6671817 T C C T True True chr6.6671817 1 1 1
16 MNEc.2.6.6671817.BIEC2-985848 Affx-101434215 AX-103715826 chr6 6671817 T C C T True True chr6.6671817 1 1 1
17 MNEc.2.6.6698388.BIEC2-985859 Affx-102562234 AX-102951995 chr6 6698388 A G G A True True chr6.6698388 1 1 1
18 MNEc.2.6.6698388.BIEC2-985859 Affx-102562234 AX-102951996 chr6 6698388 A G G A True True chr6.6698388 1 1 1
19 MNEc.2.20.33196687.MHCClIIDRB2-38 Affx-102831127 AX-104005803 chr20 33196687 T C T C False True chr20.33196687 2 2 2The first three columns (MNEcID,AffySNPID,ProbeSetID) are IDs from the Chip and the corresponding Affymetrix probe and SNP IDs. The next six columns chrom,pos,AlleleA,AlleleB,REF,ALT are the original MNEc_Ec2 coordinates and allele information. The next three columns in670,legacy,id contain some very useful information:
The last three columns: MNEc_Ec2,EquCab3,EquCab2 contain the number of times the probe sequence for each SNP BLASTED to each
reference genome. You can see this is mostly 1 here which is a good indication. You could confidently find the updated coordinates
in EquCab3 by searching for the ID in the BLAST output file.
However, for the last SNP we see that, in each genome, the probe sequence blasted to two places. However we also see that the SNP was a legacy SNP. The SNP was included on the chip regardless of its initial quality control status due to requirements for backwards compatibility with the previous generation chips. These are the columns that will indicate successful remapping of probe sequence from EquCab2 to EquCab3.
In [148]: info.EquCab3.mean()
Out[148]: 1.0436152098740357
In [149]: info.EquCab3.median()
Out[149]: 1.0On average probes had a unique mapping from EquCab2 to EquCab3.
| # probe BLAST matches | Frequency |
|---|---|
| 1 | 1690599 |
| 2 | 22125 |
| 3 | 13865 |
| 4 | 5866 |
| 5 | 373 |
| 6 | 116 |
| 7 | 49 |
| 8 | 30 |
| 9 | 12 |
| 10 | 12 |
| 11 | 7 |
| 12 | 5 |
| 13 | 7 |
| 14 | 5 |
| 16 | 1 |
| 17 | 5 |
| 19 | 3 |
| 20 | 2 |
| 21 | 3 |
| 27 | 4 |
| 35 | 2 |
| 112 | 2 |
| 125 | 2 |
| 152 | 2 |
| 181 | 2 |
| 224 | 2 |
| 254 | 2 |
| 266 | 2 |
| 294 | 2 |
| 319 | 2 |
| 415 | 2 |
Discussion can happen by opening a GitHub issue here. This lets us track progress and discuss issues using tools build into Github.