Lightweight Reference-Free Variation Detection using the Burrows-Wheeler Transform

Lightweight Reference-Free Variation Detection using the Burrows-Wheeler Transfor

Detecting Mutations by eBWT

In this paper we develop a theory describing how the extended Burrows-Wheeler Transform (EBWT) of a collection of DNA fragments tends to cluster together the copies of nucleotides sequenced from a genome G. Our theory accurately predicts how many copies of any nucleotide are expected inside each such cluster, and how an elegant and precise LCP array based procedure can locate these clusters in the EBWT. Our findings are very general and can be applied to a wide range of different problems. In this paper, we consider the case of alignment-free and reference-free SNPs discovery in multiple collections of reads. We note that, in accordance with our theoretical results, SNPs are clustered in the EBWT of the reads collection, and we develop a tool finding SNPs with a simple scan of the EBWT and LCP arrays. Preliminary results show that our method requires much less coverage than state-of-the-art tools while drastically improving precision and sensitivity

Variable-order reference-free variant discovery with the Burrows-Wheeler Transform

International audienceBackground: In [Prezza et al., AMB 2019], a new reference-free and alignment-free framework for the detection of SNPs was suggested and tested. The framework, based on the Burrows-Wheeler Transform (BWT), significantly improves sensitivity and precision of previous de Bruijn graphs based tools by overcoming several of their limitations, namely: (i) the need to establish a fixed value, usually small, for the order k, (ii) the loss of important information such as k-mer coverage and adjacency of k-mers within the same read, and (iii) bad performance in repeated regions longer than k bases. The preliminary tool, however, was able to identify only SNPs and it was too slow and memory consuming due to the use of additional heavy data structures (namely, the Suffix and LCP arrays), besides the BWT. Results: In this paper, we introduce a new algorithm and the corresponding tool ebwt2InDel that (i) extend the framework of [Prezza et al., AMB 2019] to detect also INDELs, and (ii) implements recent algorithmic findings that allow to perform the whole analysis using just the BWT, thus reducing the working space by one order of magnitude and allowing the analysis of full genomes. Finally, we describe a simple strategy for effectively parallelizing our tool for SNP detection only. On a 24-cores machine, the parallel version of our tool is one order of magnitude faster than the sequential one. The tool ebwt2InDel is available at github.com/nicolaprezza/ebwt2InDel. Conclusions: Results on a synthetic dataset covered at 30x (Human chromosome 1) show that our tool is indeed able to find up to 83% of the SNPs and 72% of the existing INDELs. These percentages considerably improve the 71% of SNPs and 51% of INDELs found by the state-of-the art tool based on de Bruijn graphs. We furthermore repor

SNPs detection by eBWT positional clustering

Abstract Background Sequencing technologies keep on turning cheaper and faster, thus putting a growing pressure for data structures designed to efficiently store raw data, and possibly perform analysis therein. In this view, there is a growing interest in alignment-free and reference-free variants calling methods that only make use of (suitably indexed) raw reads data. Results We develop the positional clustering theory that (i) describes how the extended Burrows–Wheeler Transform (eBWT) of a collection of reads tends to cluster together bases that cover the same genome position (ii) predicts the size of such clusters, and (iii) exhibits an elegant and precise LCP array based procedure to locate such clusters in the eBWT. Based on this theory, we designed and implemented an alignment-free and reference-free SNPs calling method, and we devised a consequent SNPs calling pipeline. Experiments on both synthetic and real data show that SNPs can be detected with a simple scan of the eBWT and LCP arrays as, in accordance with our theoretical framework, they are within clusters in the eBWT of the reads. Finally, our tool intrinsically performs a reference-free evaluation of its accuracy by returning the coverage of each SNP. Conclusions Based on the results of the experiments on synthetic and real data, we conclude that the positional clustering framework can be effectively used for the problem of identifying SNPs, and it appears to be a promising approach for calling other type of variants directly on raw sequencing data. Availability The software ebwt2snp is freely available for academic use at: https://github.com/nicolaprezza/ebwt2snp

Acute increase in plasma osmolality as a cause of hyperkalemia in patients with renal failure.

These studies were performed in patients with chronic renal failure to understand the mechanism(s) of hyperkalemia secondary to hypertonic NaCl infusion. In 10 patients, after intravenous infusion of either 5% or 2.5% NaCl (6 mEq per kg body wt for 120 minutes in both solutions), the maximum increase in plasma potassium averaged 0.6 (range 0.3 to 1.3) mmol/liter (P less than 0.01) or 0.3 (range 0.2 to 0.6) mmol/liter (P less than 0.01), respectively. The rise of both plasma potassium and osmolality was significantly higher during 5% NaCl than during 2.5% NaCl infusion (P less than 0.01). A significant linear correlation (P less than 0.01) between plasma potassium and osmolality was observed. Urinary potassium excretion was increased to a similar extent by 5% NaCl and 2.5% NaCl infusion. The observed hyperkalemia, secondary to NaCl infusion, was independent of venous pH, plasma bicarbonate, anion gap, insulin levels, and urinary norepinephrine and epinephrine excretion, and was associated with a fall in plasma aldosterone concentration. In separate studies, nine patients were treated with desoxycorticosterone acetate (DOCA; 20 mg i.m. for three days) before receiving saline (5%) infusion. DOCA did not prevent the level increase in plasma potassium that remained significantly correlated with plasma osmolality (P less than 0.01). In conclusion, hypertonic NaCl infusion in patients with renal failure causes a clinically relevant hyperkalemia despite increased renal excretion of potassium. This hyperkalemia is independent of acid-base or hormonal mechanisms known to regulate extrarenal homeostasis of potassium, and is strictly correlated with a rise in plasma osmolality

Acute increase in plasma osmolality as a cause of hyperkalemia in patients with renal failure.

These studies were performed in patients with chronic renal failure to understand the mechanism(s) of hyperkalemia secondary to hypertonic NaCl infusion. In 10 patients, after intravenous infusion of either 5% or 2.5% NaCl (6 mEq per kg body wt for 120 minutes in both solutions), the maximum increase in plasma potassium averaged 0.6 (range 0.3 to 1.3) mmol/liter (P less than 0.01) or 0.3 (range 0.2 to 0.6) mmol/liter (P less than 0.01), respectively. The rise of both plasma potassium and osmolality was significantly higher during 5% NaCl than during 2.5% NaCl infusion (P less than 0.01). A significant linear correlation (P less than 0.01) between plasma potassium and osmolality was observed. Urinary potassium excretion was increased to a similar extent by 5% NaCl and 2.5% NaCl infusion. The observed hyperkalemia, secondary to NaCl infusion, was independent of venous pH, plasma bicarbonate, anion gap, insulin levels, and urinary norepinephrine and epinephrine excretion, and was associated with a fall in plasma aldosterone concentration. In separate studies, nine patients were treated with desoxycorticosterone acetate (DOCA; 20 mg i.m. for three days) before receiving saline (5%) infusion. DOCA did not prevent the level increase in plasma potassium that remained significantly correlated with plasma osmolality (P less than 0.01). In conclusion, hypertonic NaCl infusion in patients with renal failure causes a clinically relevant hyperkalemia despite increased renal excretion of potassium. This hyperkalemia is independent of acid-base or hormonal mechanisms known to regulate extrarenal homeostasis of potassium, and is strictly correlated with a rise in plasma osmolality