To celebrate 400 stars ⭐️on GitHub, Cutadapt 4.1 ✂️is now available. It can find rightmost adapter occurrences (closing a 5 year old issue) and allows you to use search parameters together with "file:a.fa" https://t.co/UXop6GztN0
Proud to present our cover art created by @Ella_Maru studio on the March issue of @NatureNeuro! We tried to illustrate how genetic barcodes can be used to reveal the relations between “simple” progenitor cells and “complex” differentiated cells in the brain. Take a look 👀
I’ve published type annotations for pysam https://t.co/xyoxJUw6hd (for use with Mypy, PyCharm etc.) Hopefully to be integrated into pysam https://t.co/AQx662EX6H
Cutadapt 3.5 released; it can write statistics in JSON format:
https://t.co/7koNoXswJR
Pro tip: Use jq to extract the info you need, such as the number of found adapters:
jq '.adapters_read1[0].total_matches' file.cutadapt.json
Cutadapt 2.8 just released. It comes with a --revcomp option: This checks both the read and its reverse complement for an adapter and swaps it if necessary. Changelog at https://t.co/f2HcH5Fu7J
@StevenNHart Cutadapt’s demultiplexing is based on adapter trimming: The best matching adapter determines which output the read is sent to. At the moment, you cannot have adapters that don’t affect demultiplexing, so it’s best to run it twice.
Cutadapt 2 is out! Focus was on speed and removing ancient features. But most importantly, I’ve added an animated progress bar ;-)
https://t.co/1Cfx4EWhS9
[ 8<-------]
[ 8=-------]
[ 8<------]
Our read-based phasing tool WhatsHap is now available in version 0.18 (pip/PyPI+bioconda packages). New HapCHAT phasing algorithm integrated https://t.co/NT1PhdAqHo and bugfixes https://t.co/20Ti6pgtpg @tobiasmarschal@m_d_patterson
Now comes the fun part: I’ll finally remove colorspace support (happy you if you don’t know what that is) and switch to Python 3 only for the next release. #Python3
Excited to announce that we are hiring a Software Engineer dedicated to WhatsHap (https://t.co/6cfyxtEcHV), see job ad (https://t.co/ILG2tb4aei). Funded by DFG's Research Software Sustainability program (https://t.co/xEOiX6hlkt).
@thatdnaguy A reader process splits data into 4 MB chunks and sends them to worker processes, which parse the FASTQ and trim reads. Main process collects, orders and writes results. No temp files.