Search bioRxiv⌕ Search

Biology subjects

Seillier, L.

Publications and source records attributed to Seillier, L..

3 recordsLinked to original sources

Haplotype Threading: Accurate Polyploid Phasing from Long Reads

Resolving genomes at haplotype level is crucial for understanding the evolutionary history of polyploid species and for designing advanced breeding strategies. As a highly complex computational problem, polyploid phasing still presents considerable challenges, especially in regions of collapsing haplotypes. We present WO_SCPLOWHATSC_SCPLOWHO_SCPLOWAPC_SCPLOWO_SCPCAP C_SCPCAPO_SCPLOWPOLYPHASEC_SCPLOW, a novel two-stage approach that addresses these challenges by (i) clustering reads using a position-dependent scoring function and (ii) threading the haplotypes through the clusters by dynamic programming. We demonstrate on a simulated data set that this results in accurate haplotypes with switch error rates that are around three times lower than those obtainable by the current state-of-the-art and even around seven times lower in regions of collapsing haplotypes. Using a real data set comprising long and short read tetraploid potato sequencing data we show that WO_SCPLOWHATSC_SCPLOWHO_SCPLOWAPC_SCPLOWO_SCPCAP C_SCPCAPO_SCPLOWPOLYPHASEC_SCPLOW is able to phase the majority of the potato genes after error correction, which enables the assembly of local genomic regions of interest at haplotype level. Our algorithm is implemented as part of the widely used open source tool WhatsHap and ready to be included in production settings.

bioinformatics↗

Easily adaptable head-free training system of macaques for tasks requiring precise measurements of eye position

We describe a modified system for training macaque monkeys without invasive head immobilization on visuomotor tasks requiring the control of eye-movements. The system combines a conventional primate chair, a chair-mounted infrared camera for measuring eye-movements and a custom-made concave reward-delivery spout firmly attached to the chair. The animal was seated head-free inside the chair but the concavity of the spout stabilized its head during task performance. Training on visual fixation and discrimination tasks was successfully performed with this system. Eye-measurements, such as fixation-precision, pupil size as well as micro-saccades were comparable to those obtained using conventional invasive head-fixation methods. The system is inexpensive ([~]$40 USD material cost), easy to fabricate in a workshop (technical drawings are included), and readily adjustable between animals without the need to immobilize or sedate them for these adjustments.\n\nHighlightsO_LIWe developed an approach to train macaque monkeys head-free on visuomotor tasks requiring measurements of eye position\nC_LIO_LIThe setup is inexpensive, easy to build, and readily adjusted to the animal without the need for sedation\nC_LIO_LIThe system was tested for training on a visual fixation and a visual discrimination task\nC_LIO_LIEye measurements (fixation precision, pupil size, microsaccades) were comparable to those from head-fixed animals\nC_LI

neuroscience↗

Using confidence inferred from pupil-size to dissect perceptual task-strategy: support for a bounded decision-formation process

During perceptual decisions subjects often rely more strongly on early rather than late sensory evidence even in tasks when both are equally informative about the correct decision. This early psychophysical weighting has been explained by an integration-to-bound decision process, in which the stimulus is ignored after the accumulated evidence reaches a certain bound, or confidence level. Here, we derive predictions about how the average temporal weighting of the evidence depends on a subjects decision-confidence in this model. To test these predictions empirically, we devised a method to infer decision-confidence from pupil size in monkeys performing a disparity discrimination task. Our animals data confirmed the integration-to-bound predictions, with different internal decision-bounds accounting for differences between animals. However, the data could not be explained by two alternative accounts for early psychophysical weighting: attractor dynamics either within the decision area or due to feedback to sensory areas, or a feedforward account due to neuronal response adaptation. This approach also opens the door to using confidence more broadly when studying the neural basis of decision-making.

neuroscience↗