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Accelerate biotech R&D with high-throughput library screening
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modalities are easy to synthesize in combinatorial libraries, including antibodies, RNA binding therapies, viral vectors, and more. Using these methods with high-throughput library screening, biotechs are able to evaluate the fitness of hundreds of thousands of potential drug candidates against different targets or other types of selection.</p></div><div class="page_dagPadding__l0JBj"><img alt="Flowchart of a scientific workflow, from library preparation to results organization, with data and process mapping symbols using Latch Data, Registry, Workflow, and Pods" loading="lazy" width="677" height="295" decoding="async" data-nimg="1" style="color:transparent" src="/_next/static/media/library-screen-dag.46dc5047.svg"/></div></div></div><div class="page_timeLineContainer__qETpP"><div class="page_timeLine__RqlZN"><div class="page_number__aFctr page_step1__gp6aR">1</div><div class="page_line__E8unw"></div></div><div class="page_body__liOtl"><div class="page_textBlock__oWsyf text-block"><h2 class="h5 luminescent-text">Manage NGS experiments</h2><p class="p-s">Biotechs often use sequencing to count performant library members after an enrichment assay, resulting in large FASTQ files. These files are difficult to share, move around, and explore.</p><p class="p-s">Here a<!-- --> <strong class="page_textBioinformatician__sttq_"> <!-- -->bioinformatician</strong> <!-- -->populates<!-- --> <strong class="color-medium"><svg viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg" class="icon"><path d="M5.00028 16.0001C5.00027 15.4479 5.44798 15.0001 6.00027 15.0001H6.01027C6.56255 15.0001 7.01027 15.4478 7.01028 16.0001C7.01029 16.5524 6.56259 17.0001 6.0103 17.0001H6.0003C5.44802 17.0001 5.00029 16.5524 5.00028 16.0001Z" fill="currentcolor"></path><path d="M10.0003 15.0001C9.44798 15.0001 9.00027 15.4478 9.00028 16.0001C9.00029 16.5524 9.44802 17.0001 10.0003 17.0001H10.0103C10.5626 17 11.0103 16.5523 11.0103 16C11.0103 15.4478 10.5626 15 10.0103 15.0001H10.0003Z" fill="currentcolor"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M16.7601 2.99994L7.24006 3.0001C6.68193 3.00041 6.13443 3.15641 5.6601 3.45055C5.18624 3.74441 4.80366 4.16451 4.55528 4.66369L4.55456 4.66515L1.11504 11.5345C1.04172 11.6736 1.00021 11.8321 1.00021 12.0002L1.00032 18.0002C1.00033 18.7959 1.31642 19.5589 1.87903 20.1215C2.44165 20.6841 3.20472 21.0002 4.00037 21.0002L20.0004 20.9999C20.796 20.9999 21.5591 20.6838 22.1217 20.1212C22.6843 19.5585 23.0003 18.7955 23.0003 17.9998L23.0002 11.9998C23.0002 11.9871 23 11.9744 22.9995 11.9617C22.9937 11.8077 22.9531 11.6626 22.8854 11.5341L19.4456 4.66489L19.445 4.66357C19.1966 4.16434 18.8139 3.7442 18.34 3.45033C17.8657 3.1562 17.3182 3.00023 16.7601 2.99994ZM20.3811 10.9999L17.6559 5.55766L17.6546 5.55492C17.5718 5.38832 17.4442 5.24811 17.286 5.15007C17.128 5.05206 16.9457 5.00007 16.7598 4.99994L7.24043 5.0001C7.05446 5.00024 6.8722 5.05224 6.71415 5.15025C6.55604 5.2483 6.42842 5.38851 6.34563 5.55512L5.45009 5.11014L6.34427 5.55785L3.61928 11.0002L20.3811 10.9999ZM3.00023 13.0002L3.00032 18.0002C3.00032 18.2654 3.10568 18.5197 3.29322 18.7073C3.48076 18.8948 3.73512 19.0002 4.00034 19.0002L20.0003 18.9999C20.2656 18.9999 20.5199 18.8945 20.7074 18.707C20.895 18.5194 21.0003 18.2651 21.0003 17.9999L21.0002 12.9999L3.00023 13.0002Z" fill="currentcolor"></path></svg> Latch Data</strong>. They may upload files from AWS s3, BaseSpace, FTP, SRA, or local computers. They may do this from the comfort of their terminal. is a cloud native filesystem that can store and version all of your sequencing files.</p><p class="p-s">A <strong class="page_textBiologist__NAH0_"> biologist</strong> <!-- -->can then easily access, QC, organize, and explore their sequencing data. Scientists do not need anyone else to do this for them after it has uploaded.</p></div><div class="page_imageRow__W96eX"><img alt="Latch Data interface where you can store any size files of any type in the cloud based Latch platform" loading="lazy" width="578" height="214.5" decoding="async" data-nimg="1" class="page_image__gg_NO" style="color:transparent" srcSet="/_next/image?url=%2F_next%2Fstatic%2Fmedia%2Flatch-data.162bc372.png&w=640&q=75 1x, /_next/image?url=%2F_next%2Fstatic%2Fmedia%2Flatch-data.162bc372.png&w=1200&q=75 2x" src="/_next/image?url=%2F_next%2Fstatic%2Fmedia%2Flatch-data.162bc372.png&w=1200&q=75"/><img alt="Graph within Plots of the LatchBio platform displaying quality scores across all bases with color coding to reflect Sanger / Illumina 1.9 encoding standards" loading="lazy" width="628" height="436" decoding="async" data-nimg="1" class="page_image__gg_NO" style="color:transparent" srcSet="/_next/image?url=%2F_next%2Fstatic%2Fmedia%2Ffastqc.6cb943d2.png&w=640&q=75 1x, /_next/image?url=%2F_next%2Fstatic%2Fmedia%2Ffastqc.6cb943d2.png&w=1920&q=75 2x" src="/_next/image?url=%2F_next%2Fstatic%2Fmedia%2Ffastqc.6cb943d2.png&w=1920&q=75"/></div></div></div><div class="page_timeLineContainer__qETpP"><div class="page_timeLine__RqlZN"><div class="page_number__aFctr page_step2__9vuAz">2</div><div class="page_line__E8unw"></div></div><div class="page_body__liOtl"><div class="page_textBlock__oWsyf text-block"><h2 class="h5 luminescent-text">Identify Enriched Library Members</h2><p class="p-s">Pooled library screens allow for hundreds, or even thousands, of candidate genes to be screened simultaneously. A bulk measurement is then taken from the pooled sequencing product, and computationally untangled to reveal which candidates are enriched or depleted in the treatment group.</p><p class="p-s">Here a<!-- --> <strong class="page_textBioinformatician__sttq_"> <!-- -->bioinformatician</strong> <!-- -->can use the<!-- --> <strong class="color-medium"><svg viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg" class="icon"><path fill-rule="evenodd" clip-rule="evenodd" d="M6 2C3.8 2 2 3.8 2 6c0 1.9 1.3 3.4 3 3.9V12h2V9.9c1.7-.5 3-2 3-3.9 0-2.2-1.8-4-4-4zm0 6c-1.1 0-2-.9-2-2s.9-2 2-2 2 .9 2 2-.9 2-2 2zm7-1h3c.3 0 .5.1.7.3.2.2.3.4.3.7v4h2V8c0-.8-.3-1.6-.9-2.1-.5-.6-1.3-.9-2.1-.9h-3c-.6 0-1 .5-1 1s.4 1 1 1zm8.9 8.4L20.6 18l1.3 2.6c.2.4.1 1.1-.5 1.4-.4.1-1 0-1.3-.5L19 19.3c0-.2-.2-.3-.4-.3H18v2c0 .6-.4 1-1 1-.5 0-1-.4-1-1v-6c0-.5.5-1 1-1 .6 0 1 .5 1 1v2h.6c.2 0 .4-.1.4-.3l1.1-2.1c.3-.6.9-.7 1.3-.5.6.3.7.9.5 1.3zM13 14h-3c-.6 0-1 .4-1 1v6c0 .6.4 1 1 1h3c1.1 0 2-.9 2-2v-4c0-1.1-.9-2-2-2zm0 6h-2v-4h2v4zm-6-4H4.5c-.3 0-.5.2-.5.5s.2.5.5.5H6c1.1 0 2 .9 2 2v1c0 1.1-.9 2-2 2H3c-.5 0-1-.4-1-1s.5-1 1-1h2.5c.3 0 .5-.2.5-.5s-.2-.5-.5-.5H4c-1.1 0-2-.9-2-2v-1c0-1.1.9-2 2-2h3c.5 0 1 .4 1 1s-.5 1-1 1z" fill="currentcolor"></path></svg> Latch SDK</strong> <!-- -->to create production-grade QC and barcode counting workflows to process library members from raw sequencing files. They can easily iterate on the parameters and errors with biologists with full control over code.</p><div class="page_imageRow__W96eX"><img alt="Screenshot of LatchBio platform SDK produced interface showing lists of antibody panning enrichment counts for bioinformatics analysis" loading="lazy" width="273" height="259" decoding="async" data-nimg="1" class="page_image__gg_NO" style="color:transparent" srcSet="/_next/image?url=%2F_next%2Fstatic%2Fmedia%2Fpanning-workflow-example.5e17ede8.png&w=384&q=75 1x, /_next/image?url=%2F_next%2Fstatic%2Fmedia%2Fpanning-workflow-example.5e17ede8.png&w=640&q=75 2x" src="/_next/image?url=%2F_next%2Fstatic%2Fmedia%2Fpanning-workflow-example.5e17ede8.png&w=640&q=75"/></div><p class="p-s">Here as a<!-- --> <strong class="page_textBiologist__NAH0_">biologist</strong>, thank your bioinformatician. You now have a simple interface to analyze your enrichment data yourself.</p></div></div></div><div class="page_timeLineContainer__qETpP"><div class="page_timeLine__RqlZN"><div class="page_number__aFctr page_step3__FAd6y">3</div><div class="page_line__E8unw"></div></div><div class="page_body__liOtl"><div class="page_textBlock__oWsyf text-block"><h2 class="h5 luminescent-text">Compare Library Performance across Conditions</h2><p class="p-s">When working with large-scale library screens under different selection conditions, it can be challenging to choose a “winner” given experimental variability. Statistical analysis is used to guide further investigation by narrowing in on lead candidates.</p></div><div class="page_imageRow__W96eX"><img alt="Flow cytometry dot plots in the LatchBio platform from three rounds of selection showing GFP expression levels in cell populations" loading="lazy" width="636" height="463.5" decoding="async" data-nimg="1" class="page_image__gg_NO" style="color:transparent" srcSet="/_next/image?url=%2F_next%2Fstatic%2Fmedia%2Fcomparison-graphs.4299af66.png&w=640&q=75 1x, /_next/image?url=%2F_next%2Fstatic%2Fmedia%2Fcomparison-graphs.4299af66.png&w=1920&q=75 2x" src="/_next/image?url=%2F_next%2Fstatic%2Fmedia%2Fcomparison-graphs.4299af66.png&w=1920&q=75"/></div><div class="page_textBlock__oWsyf text-block"><p class="p-s">A<!-- --> <strong class="page_textBioinformatician__sttq_"> <!-- -->bioinformatician</strong> <!-- -->can use<!-- --> <strong class="color-medium"><svg viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg" class="icon"><path fill-rule="evenodd" clip-rule="evenodd" d="M10.937 1.29117C11.2586 1.10116 11.6253 1.00006 12 1.00005C12.3748 1.00005 12.7415 1.10113 13.0631 1.29113L13.0653 1.29246L16.9543 3.57285C17.2759 3.7634 17.5399 4.03548 17.7222 4.35926C17.9045 4.68288 17.9997 5.04808 18.0001 5.41848L18.0002 9.98042C18.0001 10.068 17.9947 10.1554 17.9841 10.242C18.0062 10.2536 18.0281 10.2655 18.0498 10.2779L18.0521 10.2792L21.941 12.4796C22.2612 12.6626 22.5283 12.9265 22.7147 13.2458C22.9011 13.5651 22.9999 13.9282 23.0003 14.2984L23.0003 18.7013C23 19.0716 22.9012 19.4346 22.7148 19.7539C22.5285 20.0732 22.2613 20.3371 21.9411 20.5202L21.9373 20.5224L18.0523 22.7207L18.0502 22.7219C17.7303 22.9043 17.3683 23 17.0004 23C16.6325 23 16.2705 22.9043 15.9506 22.7219L15.9485 22.7207L12.0635 20.5225L12.0596 20.5203C12.0397 20.5089 12.0199 20.4972 12.0004 20.4852C11.9808 20.4972 11.9611 20.5089 11.9411 20.5203L11.9373 20.5225L8.05228 22.7209L8.05019 22.7221C7.73027 22.9045 7.3683 23.0001 7.00041 23.0001C6.63251 23.0001 6.27053 22.9045 5.95059 22.7221L5.94854 22.7209L2.06346 20.5227L2.05961 20.5205C1.73942 20.3375 1.47226 20.0736 1.28588 19.7543C1.09946 19.435 1.00073 19.0719 1.00034 18.7017L1.00026 14.2988C1.00064 13.9285 1.09936 13.5655 1.28577 13.2462C1.47213 12.9269 1.73929 12.663 2.05947 12.4799L2.06332 12.4777L5.95056 10.2781C5.97224 10.2658 5.99411 10.2538 6.01617 10.2423C6.00564 10.156 6.00028 10.069 6.00019 9.98162L6.00011 5.41969C6.00047 5.04929 6.09566 4.68308 6.27795 4.35946C6.46032 4.03568 6.72428 3.76359 7.0459 3.57304L7.04978 3.57074L10.937 1.29117ZM11.0003 18.6998L11.0003 14.3007C11.0002 14.2851 10.996 14.2689 10.9875 14.2543C10.979 14.2397 10.9662 14.2264 10.9493 14.2166L10.9484 14.2161L7.05946 12.0157C7.04208 12.0058 7.02162 12.0001 7.00022 12.0001C6.97883 12.0001 6.95836 12.0057 6.94098 12.0157L6.93713 12.0179L3.05119 14.2167C3.03435 14.2266 3.02152 14.2399 3.01303 14.2544C3.00446 14.2691 3.00032 14.285 3.00026 14.3006L3.00034 18.6999C3.00039 18.7154 3.00454 18.7313 3.0131 18.746C3.0216 18.7605 3.03443 18.7738 3.05127 18.7837L3.05221 18.7842L6.94114 20.9846C6.95852 20.9945 6.97899 21.0001 7.00038 21.0001C7.02177 21.0001 7.04224 20.9945 7.05962 20.9846L7.06347 20.9824L10.9485 18.7841L10.9494 18.7835C10.9662 18.7737 10.9791 18.7604 10.9876 18.7459C10.9961 18.7312 11.0003 18.7154 11.0003 18.6998ZM13.0003 18.6997C13.0004 18.7153 13.0045 18.7311 13.0131 18.7458C13.0216 18.7604 13.0344 18.7737 13.0513 18.7835L13.0522 18.784L16.9411 20.9844C16.9585 20.9944 16.979 21 17.0004 21C17.0218 21 17.0422 20.9944 17.0596 20.9844L17.0635 20.9822L20.9485 18.7839L20.9494 18.7834C20.9662 18.7735 20.9791 18.7602 20.9876 18.7457C20.9961 18.731 21.0003 18.7152 21.0003 18.6996L21.0003 14.3005C21.0002 14.2849 20.996 14.2688 20.9875 14.2541C20.979 14.2396 20.9662 14.2263 20.9493 14.2164L20.9484 14.2159L17.0595 12.0155C17.0421 12.0056 17.0216 12 17.0002 12C16.9788 12 16.9584 12.0056 16.941 12.0155L16.9371 12.0177L13.0512 14.2166C13.0344 14.2264 13.0215 14.2397 13.013 14.2543C13.0045 14.2689 13.0003 14.2848 13.0003 14.3004L13.0003 18.6997ZM12.0001 3.00005C11.9856 3.00005 11.9699 3.00386 11.9542 3.01315L11.9504 3.01545L8.06449 5.29423C8.04891 5.30367 8.03294 5.31895 8.02054 5.34097C8.00784 5.36351 8.00018 5.39098 8.00011 5.42039L8.00019 9.97986C8.00026 10.0093 8.00793 10.0367 8.02062 10.0593C8.03303 10.0813 8.04899 10.0966 8.06457 10.106L8.06548 10.1066L11.9544 12.3869C11.9701 12.3962 11.9858 12.4001 12.0002 12.4001C12.0147 12.4001 12.0304 12.3962 12.0461 12.387L12.0499 12.3847L15.9349 10.1064L15.9358 10.1059C15.9514 10.0964 15.9674 10.0812 15.9798 10.0591C15.9924 10.0366 16.0001 10.0092 16.0002 9.97988L16.0001 5.42051C16 5.39117 15.9923 5.36333 15.9797 5.34083C15.9673 5.31882 15.9513 5.30354 15.9357 5.2941L15.9348 5.29355L12.0459 3.01316C12.0302 3.00387 12.0145 3.00005 12.0001 3.00005Z" fill="currentcolor"></path></svg> Latch Pods</strong> <!-- -->to write flexible, custom jupyter or Rstudio notebooks to plot enrichment counts. Build an application to compile your results and expose it directly to your scientists without worrying about hosting or infrastructure.</p><p class="p-s">The <strong class="page_textBiologist__NAH0_">biologist</strong> <!-- -->can then easily interact with plots, allowing them to change filters and parameters on custom-built applications. For example, an application may display top performing library members from multiple enrichment experiments.</p></div></div></div><div class="page_timeLineContainer__qETpP"><div class="page_timeLine__RqlZN"><div class="page_number__aFctr page_step4__hnjcD">4</div></div><div class="page_body__liOtl"><div class="page_textBlock__oWsyf text-block"><h2 class="h5 luminescent-text">Organize Enrichment Data for Longitudinal Analysis</h2><p class="p-s">When evaluating libraries of candidate therapeutics against numerous conditions, the complexity of the associated sequencing data can quickly become unwieldy. It is critical to clearly register your past experimental data in an organized manner, to enable searching of previous results, contextualization of new data, and synthesis of new conclusions.</p></div><div class="page_textBlock__oWsyf text-block"><p class="p-s"><strong class="color-medium"><svg viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg" class="icon"><path fill-rule="evenodd" clip-rule="evenodd" d="M15.7253 5.03849C16.2563 4.88677 16.8098 5.19426 16.9615 5.72529L20.9615 19.7253C21.1133 20.2563 20.8058 20.8098 20.2747 20.9615C19.7437 21.1133 19.1902 20.8058 19.0385 20.2747L15.0385 6.27473C14.8868 5.7437 15.1943 5.19021 15.7253 5.03849Z" fill="currentcolor"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M12 5C12.5523 5 13 5.44772 13 6V20C13 20.5523 12.5523 21 12 21C11.4477 21 11 20.5523 11 20V6C11 5.44772 11.4477 5 12 5Z" fill="currentcolor"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M8 7C8.55228 7 9 7.44772 9 8V20C9 20.5523 8.55228 21 8 21C7.44772 21 7 20.5523 7 20V8C7 7.44772 7.44772 7 8 7Z" fill="currentcolor"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M4 3C4.55228 3 5 3.44772 5 4V20C5 20.5523 4.55228 21 4 21C3.44772 21 3 20.5523 3 20V4C3 3.44772 3.44772 3 4 3Z" fill="currentcolor"></path></svg> Latch Registry</strong> <!-- -->is like Notion or Google Sheets but designed for sample sheets. Registry lets you impose structure and organization on files, associating experimental inputs and outputs with metadata.</p></div><div class="page_imageRow__W96eX"><img alt="Screenshot of the Latch Registry interface showing various records and enrichment scores for different biological samples" loading="lazy" width="586" height="327" decoding="async" data-nimg="1" class="page_image__gg_NO" style="color:transparent" srcSet="/_next/image?url=%2F_next%2Fstatic%2Fmedia%2Fdata-organization.1474da28.png&w=640&q=75 1x, /_next/image?url=%2F_next%2Fstatic%2Fmedia%2Fdata-organization.1474da28.png&w=1200&q=75 2x" src="/_next/image?url=%2F_next%2Fstatic%2Fmedia%2Fdata-organization.1474da28.png&w=1200&q=75"/></div><div class="page_textBlock__oWsyf text-block"><p class="p-s">A<!-- --> <strong class="page_textBioinformatician__sttq_"> <!-- -->bioinformatician</strong> <!-- -->team can build type-validated tables in<!-- --> <strong class="color-medium"><svg viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg" class="icon"><path fill-rule="evenodd" clip-rule="evenodd" d="M15.7253 5.03849C16.2563 4.88677 16.8098 5.19426 16.9615 5.72529L20.9615 19.7253C21.1133 20.2563 20.8058 20.8098 20.2747 20.9615C19.7437 21.1133 19.1902 20.8058 19.0385 20.2747L15.0385 6.27473C14.8868 5.7437 15.1943 5.19021 15.7253 5.03849Z" fill="currentcolor"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M12 5C12.5523 5 13 5.44772 13 6V20C13 20.5523 12.5523 21 12 21C11.4477 21 11 20.5523 11 20V6C11 5.44772 11.4477 5 12 5Z" fill="currentcolor"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M8 7C8.55228 7 9 7.44772 9 8V20C9 20.5523 8.55228 21 8 21C7.44772 21 7 20.5523 7 20V8C7 7.44772 7.44772 7 8 7Z" fill="currentcolor"></path><path fill-rule="evenodd" clip-rule="evenodd" d="M4 3C4.55228 3 5 3.44772 5 4V20C5 20.5523 4.55228 21 4 21C3.44772 21 3 20.5523 3 20V4C3 3.44772 3.44772 3 4 3Z" fill="currentcolor"></path></svg> Registry</strong> <!-- -->The bioinformatics are able to enforce accurate data entry, easily clean tables in code, and ingest them into bioinformatics workflows for batch processing.</p><p class="p-s">The <strong class="page_textBiologist__NAH0_">biologist</strong> <!-- -->can then go in and fill in the samplesheet metadata in a single place. They are easily able to view past experiments in a table that displays both experimental metadata and files in single location.</p></div></div></div></div></div></div><footer class="footer_background__HDMS9"><div class="container_container__7U8A5 footer_container__LsEE4"><nav id="footer-nav" class="footer_nav__tK6HE" aria-label="Footer"><div class="footer_topRow__NczJa"><div><a href="/" class="logo_logoHover__oE6YQ logo_logo__Xq_4T" aria-label="Landing Page"><svg viewBox="0 0 130 40" xmlns="http://www.w3.org/2000/svg"><path fill-rule="evenodd" clip-rule="evenodd" d="M105.27 13.776C105.27 13.3846 105.388 13.002 105.611 12.6765C105.833 12.351 106.149 12.0973 106.518 11.9475C106.887 11.7977 107.294 11.7585 107.686 11.8349C108.078 11.9113 108.439 12.0998 108.721 12.3766C109.004 12.6534 109.197 13.006 109.275 13.3899C109.353 13.7738 109.313 14.1718 109.16 14.5334C109.007 14.8951 108.748 15.2042 108.415 15.4217C108.083 15.6391 107.692 15.7552 107.292 15.7552C106.757 15.7498 106.246 15.5396 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