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Disambiguierung von "Langmead, Ben"

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Prefix-free parsing for building big BWTs.

, , , , , und . Algorithms Mol. Biol., 14 (1): 13:1-13:15 (2019)

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Ben Schöttker

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Ballgown bridges the gap between transcriptome assembly and expression analysis, , , , , und . Nat Biotech, 33 (3): 243--246 (März 2015)Cloud-scale RNA-sequencing differential expression analysis with Myrna., , und . Genome Biol, 11 (8): R83 (2010)differential gene expression is studied "The Myrna pipeline is complementary to existing approaches for RNA-Seq analysis - like ERANGE and Cufflinks. ERANGE attempts to recover junction reads based on the uniquely aligned reads, but only reports RPKM and does not calculate a measure of statistical significance 36 . Cufflinks is more ambitious in its attempt to fully assemble the transcriptome, but bases its differential expression statistics on the Poisson model, which we have shown may not be appropriate for biological replicates 8 . Myrna focuses on the somewhat simpler problem of differential expression analysis between genes, but uses more sophisticated statistical models and integrates the analysis in a computationally efficient pipeline. " "The version of Myrna described here does not make any special attempt to align reads across exon junctions, but this is important future work. Expression signal may be lost by failing to align junction reads; Myrna's focus on just the constitutive portions of genes avoids between-sample or between-gene biases due to this policy. Users can trade off between loss of signal due to junction reads and loss of signal due to repetitive reads by adjusting the -truncate-reads option, which trims all input reads down to a given fixed length before passing them on to the alignment step. We expect that future support for counting junction reads will not severely impact Myrna's performance characteristics; its chief impact will be to add computation to the Align stage, which is currently both the biggest bottleneck and the most easily parallelizable step. ".Rail-RNA: scalable analysis of RNA-seq splicing and coverage., , , , , , , , und . Bioinform., 33 (24): 4033-4040 (2017)Finding Maximal Exact Matches Using the r-Index., , , , , und . J. Comput. Biol., 29 (2): 188-194 (2022)Centrifuger: Lossless Compression of Microbial Genomes for Efficient and Accurate Metagenomic Sequence Classification., und . RECOMB, Volume 14758 von Lecture Notes in Computer Science, Seite 324-327. Springer, (2024)Megadepth: efficient coverage quantification for BigWigs and BAMs., , , , , und . Bioinform., 37 (18): 3014-3016 (2021)Snaptron: querying splicing patterns across tens of thousands of RNA-seq samples., , , und . Bioinform., 34 (1): 114-116 (2018)HISAT: a fast spliced aligner with low memory requirements, , und . Nat Meth, (März 2015)Fast and memory-efficient scRNA-seq k-means clustering with various distances., , , , und . BCB, Seite 24:1-24:8. ACM, (2021)KATKA: A KRAKEN-Like Tool with k Given at Query Time., , und . SPIRE, Volume 13617 von Lecture Notes in Computer Science, Seite 191-197. Springer, (2022)