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README.md

@@ -4,6 +4,6 @@
 Recombination between homologous chromosomes is a key source of human genetic diversity. The crossovers that mediate such genetic exchanges during meiosis are also important for ensuring the accuracy of chromosome segregation. In female meiosis, such crossovers are established early in fetal development and must be maintained for decades until meiosis resumes at ovulation. Understanding the landscape of meiotic recombination, its variation across individuals, and the processes by which it goes awry represent long-standing goals of human genetics.
 
 Current approaches for inferring the landscape of recombination either rely on population patterns of linkage disequilibrium—capturing a time-averaged view of historical recombination events—or direct detection of crossovers based on genotyping of haploid gametes or families (e.g., parent-offspring trios), limiting the scale and availability of relevant datasets.
-Here we take another approach that relies on the genetic analysis of blastocysts from fertility centers . The ability to reliably trace abnormalities in genome-wide ploidy is valuable for enhancing IVF outcomes and thus preimplantation genetic testing of aneuploidy (PGT-A) became a common practice during IVF; The shallow whole-genome sequencing of human blastocysts during genetic tests accumulated to large datasets, which can be exploited to study the recombination landscape in oocytes and its relation to aneuploidy. To this end, we introduce an approach for inferring recombination from retrospective analysis of data from preimplantation genetic testing (PGT-A), which is based on low-coverage (<0.05x) whole-genome sequencing of biopsies from in vitro fertilized (IVF) embryos. 
+Here we take another approach that relies on the genetic analysis of blastocysts from fertility centers . The ability to reliably trace abnormalities in genome-wide ploidy is valuable for enhancing IVF outcomes and thus preimplantation genetic testing of aneuploidy (PGT-A) became a common practice during IVF; The shallow whole-genome sequencing of human blastocysts during genetic tests accumulated to large datasets, which can be exploited to study the recombination landscape in oocytes and its relation to aneuploidy. To this end, we introduce an approach for inferring recombination from retrospective analysis of data from preimplantation genetic testing (PGT-A), which is based on low-coverage (<0.05x) whole-genome sequencing of biopsies from in vitro fertilized (IVF) embryos.
 
 Our method overcomes the sparsity of the sequencing data by exploiting its inherent relatedness structure, knowledge of haplotypes from external population reference panels, as well as the frequent occurrence of chromosome loss (whereby the remaining chromosome is “phased” by default). Based on extensive simulation, we show that our method retains high accuracy down to coverages as low as 0.02x.  In addition, it can serve as a practical tool for karyomapping, when a single sperm is sequenced on an ad hoc basis to contrast crossovers of sibling embryos. Thus, CC holds promise to improve preimplantation genetic testing for monogenic disorders (PGT-M) during IVF.

pipeline.txt

@@ -406,4 +406,4 @@ where `--haplegendsample prefix`  _converts from BCF to hap/legend/sample format
 * The script `MAKE_REF_PANEL.py` requires one of the following: (a) bcftools v1.14 or above, (b) cyvcf2 v0.30.12 or above, (c) pysam v0.18.0 or above.
 * The script `MAKE_OBS_TAB.py` requires pysam v0.18.0 or above.
 * The script `CONTRAST_HAPLOTYPES.py` would perform faster when gmpy2 v2.1.0rc1 is present.
-* The script `PLOT_PANEL.py` requires matplotlib v3.5.1 or above.
+* The script `PLOT_PANEL.py` requires matplotlib v3.5.1 or above.