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Genomic breakpoints were detected from mate-pair data using a custom pipeline and the locations of these breakpoints were used as input to readDepth.
Genome annotation was performed using a custom pipeline.
The reads were analyzed from that point on using a custom pipeline written in Python 2.7 and C++.
The fastx_toolkit software package was also used to remove Illumina reads under 50bp, while the 454 and Ion Torrent reads were cleaned using a custom pipeline [ 18].
Functional annotation was performed at the peptide level using a custom pipeline [ 8] that defines protein products and assigns transcript names.
Mutations were found using a custom pipeline written in Python (www.python.org) using the Biopython (biopython.org) and pysam (github.com/pysam-developers/pysam) modules.
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We used a custom pipeline to annotate the improved high-quality draft assembly of WH6 as previously described [ 78].
This study used a custom pipeline to identify repeated subsequences from 1 to 250 bases long in 6793306 sequences and 3681160063 nucleotides from 88 genera of vascular plants.
We used a custom pipeline that leveraged remapping protocols using the aligner BWA [ 13] against the closely related reference sequence USA300-FPR3757 as well as de novo assembly with Abyss [ 14] to successfully call polymorphisms ranging from single nucleotide variants (SNV) to large structural rearrangements.
The 454 reads were contigged using a custom perl pipeline and Blat [50] to bin homologous sequences, then cap3 [51] to align sequences in contigs.
Processing and annotation of sequences based on identity to known transcribed RNAs or as novel miRNAs was performed using a custom bioinformatics pipeline described in detail in Supplementary Methods S1.
More suggestions(15)
using a custom Python
using a custom Reaktor
using a custom cap
using a custom icon
using a custom micromanipulator
using a custom algorithm
using a custom index
using a custom stamp
using a custom application
using a custom implementation
using a custom device
using a custom one-time-use
using a custom benchmark
using a custom light
using a computational pipeline
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